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Sample records for characteristic imaging features

  1. Feature Recognition of Froth Images Based on Energy Distribution Characteristics

    WU Yanpeng

    2014-09-01

    Full Text Available This paper proposes a determining algorithm for froth image features based on the amplitude spectrum energy statistics by applying Fast Fourier Transformation to analyze the energy distribution of various-sized froth. The proposed algorithm has been used to do a froth feature analysis of the froth images from the alumina flotation processing site, and the results show that the consistency rate reaches 98.1 % and the usability rate 94.2 %; with its good robustness and high efficiency, the algorithm is quite suitable for flotation processing state recognition.

  2. Primary diaphyseal osteosarcoma in long bones: Imaging features and tumor characteristics

    Wang, Cheng-Sheng; Yin, Qi-Hua; Liao, Jin-Sheng; Lou, Jiang-Hua; Ding, Xiao-Yi; Zhu, Yan-Bo; Chen, Ke-Min

    2012-01-01

    Objective: This study aims to assess retrospectively the imaging features of diaphyseal osteosarcoma and compare its characteristics with that of metaphyseal osteosarcoma. Materials and methods: Eighteen pathologically confirmed diaphyseal osteosarcomas were reviewed. Images of X-ray (n = 18), CT (n = 12) and MRI (n = 15) were evaluated by two radiologists. Differences among common radiologic findings of X-ray, CT and MRI, and between diaphyseal osteosarcomas and metaphyseal osteosarcomas in terms of tumor characteristics were compared. Results: The common imaging features of diaphyseal osteosarcoma were bone destruction, lamellar periosteal reaction with/without Codman triangle, massive soft tissue mass/swelling, neoplastic bone and/or calcification. CT and MRI had a higher detection rate in detecting bone destruction (P = 0.001) as compared with that of X-ray. X-ray and CT resulted in a higher percentage in detecting periosteal reaction (P = 0.018) and neoplastic bone and/or calcification (P = 0.043) as compared with that of MRI. There was no difference (P = 0.179) in detecting soft tissue mass among three imaging modalities. When comparing metaphyseal osteosarcoma to diaphyseal osteosarcoma, the latter had the following characteristics: a higher age of onset (P = 0.022), a larger extent of tumor (P = 0.018), a more osteolytic radiographic pattern (P = 0.043). Conclusion: As compared with metaphyseal osteosarcoma, diaphysial osteosarcoma is a special location of osteosarcoma with a lower incidence, a higher age of onset, a larger extent of tumor, a more osteolytic radiographic pattern. The osteoblastic and mixed types are diagnosed easily, but the osteolytic lesion should be differentiated from Ewing sarcoma. X-ray, CT and MRI can show imaging features from different aspects with different detection rates.

  3. Image Features Based on Characteristic Curves and Local Binary Patterns for Automated HER2 Scoring

    Ramakrishnan Mukundan

    2018-02-01

    Full Text Available This paper presents novel feature descriptors and classification algorithms for the automated scoring of HER2 in Whole Slide Images (WSI of breast cancer histology slides. Since a large amount of processing is involved in analyzing WSI images, the primary design goal has been to keep the computational complexity to the minimum possible level and to use simple, yet robust feature descriptors that can provide accurate classification of the slides. We propose two types of feature descriptors that encode important information about staining patterns and the percentage of staining present in ImmunoHistoChemistry (IHC-stained slides. The first descriptor is called a characteristic curve, which is a smooth non-increasing curve that represents the variation of percentage of staining with saturation levels. The second new descriptor introduced in this paper is a local binary pattern (LBP feature curve, which is also a non-increasing smooth curve that represents the local texture of the staining patterns. Both descriptors show excellent interclass variance and intraclass correlation and are suitable for the design of automatic HER2 classification algorithms. This paper gives the detailed theoretical aspects of the feature descriptors and also provides experimental results and a comparative analysis.

  4. Hydatid disease of the Central Nervous System: imaging characteristics and general features

    Abbassioun, K.; Amirjamshidi, A.; Sabouri Deylamie, M.

    2003-01-01

    Background: Hydatid disease primarily affects the liver and typically demonstrates characteristic imaging findings. Secondary involvement due to hematogenous dissemination may be seen in almost any locations, e.g., lung, kidney, spleen, bone and central nervous system. Objectives: To review the different aspects of hydatidosis of the central nervous system briefly and discuss the pathognomonic features and rare varieties of radiological findings useful in preoperative diagnosis of the disease in the human central nervous system. Materials and Methods: In a retrospective study, the records of almost 100 cases of central nervous system hydatidosis were analyzed . The available images were reviewed by independent observers, either a radiologist or a neurosurgeon, and reported separately. Results: In skull x-ray films, nonspecific changes denoted increased intracranial pressure, skull asymmetry and curvilinear calcification in rare instances. Computed tomography and magnetic resonance imaging demonstrated the round or oval, well-defined cystic mass with an attenuation or signal intensity similar to that of cerebrospinal fluid, with no associated perifocal edema, and no contrast enhancement as the pathognomonic findings of brain hydatidosis. Similar findings were detected in hydatid cysts involving the orbit, spinal column and spinal cord with some variations. Such findings as mild perifocal edema, non homogenous contrast enhancement, non-uniform shapes, calcification and multiplicity or septations have been the atypical radiological findings. Conclusion: In endemic areas, familiarity with typical and atypical radiological manifestations of hydatid disease of the central nervous system, will be helpful in making prompt and correct preoperative diagnosis leading to a better surgical outcome

  5. Imaging features of aggressive angiomyxoma

    Jeyadevan, N.N.; Sohaib, S.A.A.; Thomas, J.M.; Jeyarajah, A.; Shepherd, J.H.; Fisher, C.

    2003-01-01

    AIM: To describe the imaging features of aggressive angiomyxoma in a rare benign mesenchymal tumour most frequently arising from the perineum in young female patients. MATERIALS AND METHODS: We reviewed the computed tomography (CT) and magnetic resonance (MR) imaging features of patients with aggressive angiomyxoma who were referred to our hospital. The imaging features were correlated with clinical information and pathology in all patients. RESULTS: Four CT and five MR studies were available for five patients (all women, mean age 39, range 24-55). Three patients had recurrent tumour at follow-up. CT and MR imaging demonstrated a well-defined mass-displacing adjacent structures. The tumour was of low attenuation relative to muscle on CT. On MR, the tumour was isointense relative to muscle on T1-weighted image, hyperintense on T2-weighted image and enhanced avidly after gadolinium contrast with a characteristic 'swirled' internal pattern. MR imaging demonstrates the extent of the tumour and its relation to the pelvic floor. Recurrent tumour has a similar appearance to the primary lesion. CONCLUSION: The MR appearances of aggressive angiomyxomas are characteristic, and the diagnosis should be considered in any young woman presenting with a well-defined mass arising from the perineum. Jeyadevan, N. N. etal. (2003). Clinical Radiology58, 157--162

  6. Multispectral Image Feature Points

    Cristhian Aguilera

    2012-09-01

    Full Text Available This paper presents a novel feature point descriptor for the multispectral image case: Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge Oriented Histogram (EOH descriptor. Finally, points of interest from multispectral images are matched by finding nearest couples using the information from the descriptor. The provided experimental results and comparisons with similar methods show both the validity of the proposed approach as well as the improvements it offers with respect to the current state-of-the-art.

  7. Distal intersection tenosynovitis of the wrist: a lesser-known extensor tendinopathy with characteristic MR imaging features

    Parellada, Antoni J.; Gopez, Angela G.; Morrison, William B.; Sweet, Stephanie; Leinberry, Charles F.; Reiter, Sean B.; Kohn, Mark

    2007-01-01

    the constraining effect of the extensor retinaculum. These anatomical features determine the presence of characteristic MR imaging findings. (orig.)

  8. Distal intersection tenosynovitis of the wrist: a lesser-known extensor tendinopathy with characteristic MR imaging features

    Parellada, Antoni J. [DII - Diagnostic Imaging, Inc., Philadelphia, PA (United States); Frankford Hospitals - Torresdale Campus, Department of Radiology, Philadelphia, PA (United States); Gopez, Angela G.; Morrison, William B. [Thomas Jefferson University, Department of Radiology, Philadelphia, PA (United States); Sweet, Stephanie [Thomas Jefferson University, Philadelphia Hand Center, Philadelphia, PA (United States); Leinberry, Charles F. [Thomas Jefferson University, Department of Orthopedic Surgery - Hand Surgery, Philadelphia, PA (United States); Reiter, Sean B.; Kohn, Mark [DII - Diagnostic Imaging, Inc., Philadelphia, PA (United States)

    2007-03-15

    , as well as the constraining effect of the extensor retinaculum. These anatomical features determine the presence of characteristic MR imaging findings. (orig.)

  9. Imaging features of thalassemia

    Tunaci, M.; Tunaci, A.; Engin, G.; Oezkorkmaz, B.; Acunas, G.; Acunas, B. [Dept. of Radiology, Istanbul Univ. (Turkey); Dincol, G. [Dept. of Internal Medicine, Istanbul Univ. (Turkey)

    1999-07-01

    Thalassemia is a kind of chronic, inherited, microcytic anemia characterized by defective hemoglobin synthesis and ineffective erythropoiesis. In all thalassemias clinical features that result from anemia, transfusional, and absorptive iron overload are similar but vary in severity. The radiographic features of {beta}-thalassemia are due in large part to marrow hyperplasia. Markedly expanded marrow space lead to various skeletal manifestations including spine, skull, facial bones, and ribs. Extramedullary hematopoiesis (ExmH), hemosiderosis, and cholelithiasis are among the non-skeletal manifestations of thalassemia. The skeletal X-ray findings show characteristics of chronic overactivity of the marrow. In this article both skeletal and non-skeletal manifestations of thalassemia are discussed with an overview of X-ray findings, including MRI and CT findings. (orig.)

  10. Imaging features of thalassemia

    Tunaci, M.; Tunaci, A.; Engin, G.; Oezkorkmaz, B.; Acunas, G.; Acunas, B.; Dincol, G.

    1999-01-01

    Thalassemia is a kind of chronic, inherited, microcytic anemia characterized by defective hemoglobin synthesis and ineffective erythropoiesis. In all thalassemias clinical features that result from anemia, transfusional, and absorptive iron overload are similar but vary in severity. The radiographic features of β-thalassemia are due in large part to marrow hyperplasia. Markedly expanded marrow space lead to various skeletal manifestations including spine, skull, facial bones, and ribs. Extramedullary hematopoiesis (ExmH), hemosiderosis, and cholelithiasis are among the non-skeletal manifestations of thalassemia. The skeletal X-ray findings show characteristics of chronic overactivity of the marrow. In this article both skeletal and non-skeletal manifestations of thalassemia are discussed with an overview of X-ray findings, including MRI and CT findings. (orig.)

  11. Imaging features of kaposiform lymphangiomatosis

    Goyal, Pradeep; Alomari, Ahmad I.; Shaikh, Raja; Chaudry, Gulraiz; Kozakewich, Harry P.; Perez-Atayde, Antonio R.; Trenor, Cameron C.; Fishman, Steven J.; Greene, Arin K.

    2016-01-01

    Kaposiform lymphangiomatosis is a rare, aggressive lymphatic disorder. The imaging and presenting features of kaposiform lymphangiomatosis can overlap with those of central conducting lymphatic anomaly and generalized lymphatic anomaly. To analyze the imaging findings of kaposiform lymphangiomatosis disorder and highlight features most suggestive of this diagnosis. We retrospectively identified and characterized 20 children and young adults with histopathological diagnosis of kaposiform lymphangiomatosis and radiologic imaging referred to the vascular anomalies center between 1995 and 2015. The median age at onset was 6.5 years (range 3 months to 27 years). The most common presenting features were respiratory compromise (dyspnea, cough, chest pain; 55.5%), swelling/mass (25%), bleeding (15%) and fracture (5%). The thoracic cavity was involved in all patients; all patients had mediastinal involvement followed by lung parenchymal disease (90%) and pleural (85%) and pericardial (50%) effusions. The most common extra-thoracic sites of disease were the retroperitoneum (80%), bone (60%), abdominal viscera (55%) and muscles (45%). There was characteristic enhancing and infiltrative soft-tissue thickening in the mediastinum and retroperitoneum extending along the lymphatic distribution. Kaposiform lymphangiomatosis has overlapping imaging features with central conducting lymphatic anomaly and generalized lymphatic anomaly. Presence of mediastinal or retroperitoneal enhancing and infiltrative soft-tissue disease along the lymphatic distribution, hemorrhagic effusions and moderate thrombocytopenia (50-100,000/μl) should favor diagnosis of kaposiform lymphangiomatosis. (orig.)

  12. Pulmonary vasculitis: imaging features

    Seo, Joon Beom; Im, Jung Gi; Chung, Jin Wook; Goo, Jin Mo; Park, Jae Hyung; Yeon, Kyung Mo; Song, Jae Woo

    1999-01-01

    Vasculitis is defined as an inflammatory process involving blood vessels, and can lead to destruction of the vascular wall and ischemic damage to the organs supplied by these vessels. The lung is commonly affected. A number of attempts have been made to classify and organize pulmonary vasculitis, but because the clinical manifestations and pathologic features of the condition overlap considerably, these afforts have failed to achieve a consensus. We classified pulmonary vasculitis as belonging to either the angitiis-granulomatosis group, the diffuse pulmonary hemorrhage with capillaritis group, or 'other'. Characteristic radiographic and CT findings of the different types of pulmonary vasculitis are illustrated, with a brief discussion of the respective disease entities

  13. Intracranial metastatic mucinous adrenocarcinoma with characteristic features on diffusion-weighted imaging and in vivo magnetic resonance spectroscopy

    Guruprasad, Ashwathnarayan S.; Chandrashekar, Hoskote S.; Jayakumar, Peruvumba N.; Srikanth, Subbamma G.; Shankar, Susarla K.

    2004-01-01

    Intracranial abscesses and metastases are common lesions that might not be differentiated on routine MR I alone. In vivo proton spectroscopy and diffusion-weighted imaging have been used as complementary investigations for improved tissue characterization. In the present report we illustrate the role of mucin and its contribution to signal characteristics on diffusion-weighted imaging in a metastatic mucinous adenocarcinoma Copyright (2004) Blackwell Publishing Asia Pty Ltd

  14. Abdominal tuberculosis: Imaging features

    Pereira, Jose M. [Department of Radiology, Hospital de S. Joao, Porto (Portugal)]. E-mail: jmpjesus@yahoo.com; Madureira, Antonio J. [Department of Radiology, Hospital de S. Joao, Porto (Portugal); Vieira, Alberto [Department of Radiology, Hospital de S. Joao, Porto (Portugal); Ramos, Isabel [Department of Radiology, Hospital de S. Joao, Porto (Portugal)

    2005-08-01

    Radiological findings of abdominal tuberculosis can mimic those of many different diseases. A high level of suspicion is required, especially in high-risk population. In this article, we will describe barium studies, ultrasound (US) and computed tomography (CT) findings of abdominal tuberculosis (TB), with emphasis in the latest. We will illustrate CT findings that can help in the diagnosis of abdominal tuberculosis and describe imaging features that differentiate it from other inflammatory and neoplastic diseases, particularly lymphoma and Crohn's disease. As tuberculosis can affect any organ in the abdomen, emphasis is placed to ileocecal involvement, lymphadenopathy, peritonitis and solid organ disease (liver, spleen and pancreas). A positive culture or hystologic analysis of biopsy is still required in many patients for definitive diagnosis. Learning objectives:1.To review the relevant pathophysiology of abdominal tuberculosis. 2.Illustrate CT findings that can help in the diagnosis.

  15. Abdominal tuberculosis: Imaging features

    Pereira, Jose M.; Madureira, Antonio J.; Vieira, Alberto; Ramos, Isabel

    2005-01-01

    Radiological findings of abdominal tuberculosis can mimic those of many different diseases. A high level of suspicion is required, especially in high-risk population. In this article, we will describe barium studies, ultrasound (US) and computed tomography (CT) findings of abdominal tuberculosis (TB), with emphasis in the latest. We will illustrate CT findings that can help in the diagnosis of abdominal tuberculosis and describe imaging features that differentiate it from other inflammatory and neoplastic diseases, particularly lymphoma and Crohn's disease. As tuberculosis can affect any organ in the abdomen, emphasis is placed to ileocecal involvement, lymphadenopathy, peritonitis and solid organ disease (liver, spleen and pancreas). A positive culture or hystologic analysis of biopsy is still required in many patients for definitive diagnosis. Learning objectives:1.To review the relevant pathophysiology of abdominal tuberculosis. 2.Illustrate CT findings that can help in the diagnosis

  16. Localized scleroderma: imaging features

    Liu, P.; Uziel, Y.; Chuang, S.; Silverman, E.; Krafchik, B.; Laxer, R.

    1994-01-01

    Localized scleroderma is distinct from the diffuse form of scleroderma and does not show Raynaud's phenomenon and visceral involvement. The imaging features in 23 patients ranging from 2 to 17 years of age (mean 11.1 years) were reviewed. Leg length discrepancy and muscle atrophy were the most common findings (five patients), with two patients also showing modelling deformity of the fibula. One patient with lower extremity involvement showed abnormal bone marrow signals on MR. Disabling joint contracture requiring orthopedic intervention was noted in one patient. In two patients with ''en coup de sabre'' facial deformity, CT and MR scans revealed intracranial calcifications and white matter abnormality in the ipsilateral frontal lobes, with one also showing migrational abnormality. In a third patient, CT revealed white matter abnormality in the ipsilateral parietal lobe. In one patient with progressive facial hemiatrophy, CT and MR scans showed the underlying hypoplastic left maxillary antrum and cheek. Imaging studies of areas of clinical concern revealed positive findings in half our patients. (orig.)

  17. Localized scleroderma: imaging features

    Liu, P. (Dept. of Diagnostic Imaging, Hospital for Sick Children, Toronto, ON (Canada)); Uziel, Y. (Div. of Rheumatology, Hospital for Sick Children, Toronto, ON (Canada)); Chuang, S. (Dept. of Diagnostic Imaging, Hospital for Sick Children, Toronto, ON (Canada)); Silverman, E. (Div. of Rheumatology, Hospital for Sick Children, Toronto, ON (Canada)); Krafchik, B. (Div. of Dermatology, Dept. of Pediatrics, Hospital for Sick Children, Toronto, ON (Canada)); Laxer, R. (Div. of Rheumatology, Hospital for Sick Children, Toronto, ON (Canada))

    1994-06-01

    Localized scleroderma is distinct from the diffuse form of scleroderma and does not show Raynaud's phenomenon and visceral involvement. The imaging features in 23 patients ranging from 2 to 17 years of age (mean 11.1 years) were reviewed. Leg length discrepancy and muscle atrophy were the most common findings (five patients), with two patients also showing modelling deformity of the fibula. One patient with lower extremity involvement showed abnormal bone marrow signals on MR. Disabling joint contracture requiring orthopedic intervention was noted in one patient. In two patients with ''en coup de sabre'' facial deformity, CT and MR scans revealed intracranial calcifications and white matter abnormality in the ipsilateral frontal lobes, with one also showing migrational abnormality. In a third patient, CT revealed white matter abnormality in the ipsilateral parietal lobe. In one patient with progressive facial hemiatrophy, CT and MR scans showed the underlying hypoplastic left maxillary antrum and cheek. Imaging studies of areas of clinical concern revealed positive findings in half our patients. (orig.)

  18. Imaging features of musculoskeletal tuberculosis

    Vuyst, Dimitri De; Vanhoenacker, Filip; Bernaerts, Anja; Gielen, Jan; Schepper, Arthur M. de

    2003-01-01

    The purpose of this article is to review the imaging characteristics of musculoskeletal tuberculosis. Skeletal tuberculosis represents one-third of all cases of tuberculosis occurring in extrapulmonary sites. Hematogenous spread from a distant focus elsewhere in the body is the cornerstone in the understanding of imaging features of musculoskeletal tuberculosis. The most common presentations are tuberculous spondylitis, arthritis, osteomyelitis, and soft tissue involvement. The diagnostic value of the different imaging techniques, which include conventional radiography, CT, and MR imaging, are emphasized. Whereas conventional radiography is the mainstay in the diagnosis of tuberculous arthritis and osteomyelitis, MR imaging may detect associated bone marrow and soft tissue abnormalities. MR imaging is generally accepted as the imaging modality of choice for diagnosis, demonstration of the extent of the disease of tuberculous spondylitis, and soft tissue tuberculosis. Moreover, it may be very helpful in the differential diagnosis with pyogenic spondylodiscitis, as it may easily demonstrate anterior corner destruction, the relative preservation of the intervertebral disk, multilevel involvement with or without skip lesions, and a large soft tissue abscess, as these are all arguments in favor of a tuberculous spondylitis. On the other hand, CT is still superior in the demonstration of calcifications, which are found in chronic tuberculous abscesses. (orig.)

  19. Wilson’s disease: Atypical imaging features

    Venugopalan Y Vishnu

    2016-10-01

    Full Text Available Wilson’s disease is a genetic movement disorder with characteristic clinical and imaging features. We report a 17- year-old boy who presented with sialorrhea, hypophonic speech, paraparesis with repeated falls and recurrent seizures along with cognitive decline. He had bilateral Kayser Flescher rings. Other than the typical features of Wilson’s disease in cranial MRI, there were extensive white matter signal abnormalities (T2 and FLAIR hyperintensities and gyriform contrast enhancement which are rare imaging features in Wilson's disease. A high index of suspicion is required to diagnose Wilson’s disease when atypical imaging features are present.

  20. Diffusion-weighted imaging features of breast tumours and the surrounding stroma reflect intrinsic heterogeneous characteristics of molecular subtypes in breast cancer

    Fan, Ming

    2017-12-16

    Breast cancer heterogeneity is the main obstacle preventing the identification of patients with breast cancer with poor prognoses and treatment responses; however, such heterogeneity has not been well characterized. The purpose of this retrospective study was to reveal heterogeneous patterns in the apparent diffusion coefficient (ADC) signals in tumours and the surrounding stroma to predict molecular subtypes of breast cancer. A dataset of 126 patients with breast cancer, who underwent preoperative diffusion-weighted imaging (DWI) on a 3.0-T image system, was collected. Breast images were segmented into regions comprising the tumour and surrounding stromal shells in which features that reflect heterogeneous ADC signal distribution were extracted. For each region, imaging features were computed, including the mean, minimum, variance, interquartile range (IQR), range, skewness, kurtosis and entropy of ADC values. Univariate and stepwise multivariate logistic regression modelling was performed to identify the magnetic resonance imaging features that optimally discriminate luminal A, luminal B, human epidermal growth factor 2 (HER2)-enriched and basal-like molecular subtypes. The performance of the predictive models was evaluated using the area under the receiver operating characteristic curve (AUC). Univariate logistic regression analysis showed that the skewness in the tumour boundary achieved an AUC of 0.718 for discrimination between luminal A and non-luminal A tumours, whereas the IQR of the ADC value in the tumour boundary had an AUC of 0.703 for classification of the HER2-enriched subtype. Imaging features in the tumour boundary and the proximal peritumoral stroma corresponded to a higher overall prediction performance than those in other regions. A multivariate logistic regression model combining features in all the regions achieved an overall AUC of 0.800 for the classification of the four tumour subtypes. These findings suggest that features in the tumour

  1. Diffusion-weighted imaging features of breast tumours and the surrounding stroma reflect intrinsic heterogeneous characteristics of molecular subtypes in breast cancer

    Fan, Ming; He, Ting; Zhang, Peng; Cheng, Hu; Zhang, Juan; Gao, Xin; Li, Lihua

    2017-01-01

    Breast cancer heterogeneity is the main obstacle preventing the identification of patients with breast cancer with poor prognoses and treatment responses; however, such heterogeneity has not been well characterized. The purpose of this retrospective study was to reveal heterogeneous patterns in the apparent diffusion coefficient (ADC) signals in tumours and the surrounding stroma to predict molecular subtypes of breast cancer. A dataset of 126 patients with breast cancer, who underwent preoperative diffusion-weighted imaging (DWI) on a 3.0-T image system, was collected. Breast images were segmented into regions comprising the tumour and surrounding stromal shells in which features that reflect heterogeneous ADC signal distribution were extracted. For each region, imaging features were computed, including the mean, minimum, variance, interquartile range (IQR), range, skewness, kurtosis and entropy of ADC values. Univariate and stepwise multivariate logistic regression modelling was performed to identify the magnetic resonance imaging features that optimally discriminate luminal A, luminal B, human epidermal growth factor 2 (HER2)-enriched and basal-like molecular subtypes. The performance of the predictive models was evaluated using the area under the receiver operating characteristic curve (AUC). Univariate logistic regression analysis showed that the skewness in the tumour boundary achieved an AUC of 0.718 for discrimination between luminal A and non-luminal A tumours, whereas the IQR of the ADC value in the tumour boundary had an AUC of 0.703 for classification of the HER2-enriched subtype. Imaging features in the tumour boundary and the proximal peritumoral stroma corresponded to a higher overall prediction performance than those in other regions. A multivariate logistic regression model combining features in all the regions achieved an overall AUC of 0.800 for the classification of the four tumour subtypes. These findings suggest that features in the tumour

  2. Featured Image | Galaxy of Images

    2,600 images. more info The Book of the Fair The first Ferris Wheel, the creation of bridge builder George W. Ferris, was erected at the World’s Columbian Exposition in Chicago in 1893. To commemorate

  3. MR imaging features of craniodiaphyseal dysplasia

    Marden, Franklin A. [Mallinckrodt Institute of Radiology, Washington University Medical Center, 510 South Kingshighway Blvd., MO 63110, St. Louis (United States); Department of Radiology, St. Louis Children' s Hospital, Children' s Place, MO 63110, St. Louis (United States); Wippold, Franz J. [Mallinckrodt Institute of Radiology, Washington University Medical Center, 510 South Kingshighway Blvd., MO 63110, St. Louis (United States); Department of Radiology, St. Louis Children' s Hospital, Children' s Place, MO 63110, St. Louis (United States); Department of Radiology/Nuclear Medicine, F. Edward Hebert School of Medicine, Uniformed Services University of the Health Sciences, MD 20814, Bethesda (United States)

    2004-02-01

    We report the magnetic resonance (MR) imaging findings in a 4-year-old girl with characteristic radiographic and computed tomography (CT) features of craniodiaphyseal dysplasia. MR imaging exquisitely depicted cranial nerve compression, small foramen magnum, hydrocephalus, and other intracranial complications of this syndrome. A syrinx of the cervical spinal cord was demonstrated. We suggest that MR imaging become a routine component of the evaluation of these patients. (orig.)

  4. Renal angiomyoadenomatous tumour: Imaging features

    Sahni, V. Anik; Hirsch, Michelle S.; Silverman, Stuart G.

    2012-01-01

    Renal angiomyoadenomatous tumour is a rare, recently described neoplasm with a distinctive histological appearance. Although reported in the pathology literature, to our knowledge, no prior reports have described its imaging appearance. We describe the computed tomography and magnetic resonance imaging features of an incidentally detected renal angiomyoadenomatous tumour that appeared as a well-marginated, solid T2-hypointense enhancing mass, in a 50-year-old woman. It is indistinguishable from a variety of benign and malignant renal neoplasms. PMID:23093565

  5. Machine parameters and characteristic features

    Le Duff, J.

    1979-01-01

    The design and operating characteristics of LEP are presented. Its probable performance, possible improvements and cost are discussed and some comparisons are drawn with machines currently in operation. (W.D.L.)

  6. Textural features for image classification

    Haralick, R. M.; Dinstein, I.; Shanmugam, K.

    1973-01-01

    Description of some easily computable textural features based on gray-tone spatial dependances, and illustration of their application in category-identification tasks of three different kinds of image data - namely, photomicrographs of five kinds of sandstones, 1:20,000 panchromatic aerial photographs of eight land-use categories, and ERTS multispectral imagery containing several land-use categories. Two kinds of decision rules are used - one for which the decision regions are convex polyhedra (a piecewise-linear decision rule), and one for which the decision regions are rectangular parallelpipeds (a min-max decision rule). In each experiment the data set was divided into two parts, a training set and a test set. Test set identification accuracy is 89% for the photomicrographs, 82% for the aerial photographic imagery, and 83% for the satellite imagery. These results indicate that the easily computable textural features probably have a general applicability for a wide variety of image-classification applications.

  7. Textural features for radar image analysis

    Shanmugan, K. S.; Narayanan, V.; Frost, V. S.; Stiles, J. A.; Holtzman, J. C.

    1981-01-01

    Texture is seen as an important spatial feature useful for identifying objects or regions of interest in an image. While textural features have been widely used in analyzing a variety of photographic images, they have not been used in processing radar images. A procedure for extracting a set of textural features for characterizing small areas in radar images is presented, and it is shown that these features can be used in classifying segments of radar images corresponding to different geological formations.

  8. Imaging features of iliopsoas bursitis

    Wunderbaldinger, P. [Department of Radiology, University of Vienna (Austria); Center of Molecular Imaging Research, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA (United States); Bremer, C. [Department of Radiology, University of Muenster (Germany); Schellenberger, E. [Center of Molecular Imaging Research, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA (United States); Department of Radiology, Martin-Luther University of Halle-Wittenberg, Halle (Germany); Cejna, M.; Turetschek, K.; Kainberger, F. [Department of Radiology, University of Vienna (Austria)

    2002-02-01

    The aim of this study was firstly to describe the spectrum of imaging findings seen in iliopsoas bursitis, and secondly to compare cross-sectional imaging techniques in the demonstration of the extent, size and appearance of the iliopsoas bursitis as referenced by surgery. Imaging studies of 18 patients (13 women, 5 men; mean age 53 years) with surgically proven iliopsoas bursitis were reviewed. All patients received conventional radiographs of the pelvis and hip, US and MR imaging of the hip. The CT was performed in 5 of the 18 patients. Ultrasound, CT and MR all demonstrated enlarged iliopsoas bursae. The bursal wall was thin and well defined in 83% and thickened in 17% of all cases. The two cases with septations on US were not seen by CT and MRI. A communication between the bursa and the hip joint was seen, and surgically verified, in all 18 patients by MR imaging, whereas US and CT failed to demonstrate it in 44 and 40% of the cases, respectively. Hip joint effusion was seen and verified by surgery in 16 patients by MRI, whereas CT (4 of 5) and US (n=12) underestimated the number. The overall size of the bursa corresponded best between MRI and surgery, whereas CT and US tended to underestimate the size. Contrast enhancement of the bursal wall was seen in all cases. The imaging characteristics of iliopsoas bursitis are a well-defined, thin-walled cystic mass with a communication to the hip joint and peripheral contrast enhancement. The most accurate way to assess iliopsoas bursitis is with MR imaging; thus, it should be used for accurate therapy planning and follow-up studies. In order to initially prove an iliopsoas bursitis, US is the most cost-effective, easy-to-perform and fast alternative. (orig.)

  9. Imaging features of iliopsoas bursitis

    Wunderbaldinger, P.; Bremer, C.; Schellenberger, E.; Cejna, M.; Turetschek, K.; Kainberger, F.

    2002-01-01

    The aim of this study was firstly to describe the spectrum of imaging findings seen in iliopsoas bursitis, and secondly to compare cross-sectional imaging techniques in the demonstration of the extent, size and appearance of the iliopsoas bursitis as referenced by surgery. Imaging studies of 18 patients (13 women, 5 men; mean age 53 years) with surgically proven iliopsoas bursitis were reviewed. All patients received conventional radiographs of the pelvis and hip, US and MR imaging of the hip. The CT was performed in 5 of the 18 patients. Ultrasound, CT and MR all demonstrated enlarged iliopsoas bursae. The bursal wall was thin and well defined in 83% and thickened in 17% of all cases. The two cases with septations on US were not seen by CT and MRI. A communication between the bursa and the hip joint was seen, and surgically verified, in all 18 patients by MR imaging, whereas US and CT failed to demonstrate it in 44 and 40% of the cases, respectively. Hip joint effusion was seen and verified by surgery in 16 patients by MRI, whereas CT (4 of 5) and US (n=12) underestimated the number. The overall size of the bursa corresponded best between MRI and surgery, whereas CT and US tended to underestimate the size. Contrast enhancement of the bursal wall was seen in all cases. The imaging characteristics of iliopsoas bursitis are a well-defined, thin-walled cystic mass with a communication to the hip joint and peripheral contrast enhancement. The most accurate way to assess iliopsoas bursitis is with MR imaging; thus, it should be used for accurate therapy planning and follow-up studies. In order to initially prove an iliopsoas bursitis, US is the most cost-effective, easy-to-perform and fast alternative. (orig.)

  10. Imaging features of juxtacortical chondroma in children

    Miller, Stephen F.

    2014-01-01

    Juxtacortical chondroma is a rare benign bone lesion in children. Children usually present with a mildly painful mass, which prompts diagnostic imaging studies. The rarity of this condition often presents a diagnostic challenge. Correct diagnosis is crucial in guiding surgical management. To describe the characteristic imaging findings of juxtacortical chondroma in children. We identified all children who were diagnosed with juxtacortical chondroma between 1998 and 2012. A single experienced pediatric radiologist reviewed all diagnostic imaging studies, including plain radiographs, CT, MR and bone scans. Seven children (5 boys and 2 girls) with juxtacortical chondroma were identified, ranging in age from 6 years to 16 years (mean 12.3 years). Mild pain and a palpable mass were present in all seven children. Plain radiographs were available in 6/7, MR in 7/7, CT in 4/7 and skeletal scintigraphy in 5/7 children. Three lesions were located in the proximal humerus, with one each in the distal radius, distal femur, proximal tibia and scapula. Radiographic and CT features deemed highly suggestive of juxtacortical chondroma included cortical scalloping, underlying cortical sclerosis and overhanging margins. MRI features consistent with juxtacortical chondroma included isointensity to skeletal muscle on T1, marked hyperintensity on T2 and peripheral rim enhancement after contrast agent administration. One of seven lesions demonstrated intramedullary extension, and 2/7 showed adjacent soft-tissue edema. Juxtacortical chondroma is an uncommon benign lesion in children with characteristic features on plain radiographs, CT and MR. Recognition of these features is invaluable in guiding appropriate surgical management. (orig.)

  11. Imaging features of juxtacortical chondroma in children

    Miller, Stephen F. [St. Jude Children' s Research Hospital, Department of Radiological Sciences, Memphis, TN (United States)

    2014-01-15

    Juxtacortical chondroma is a rare benign bone lesion in children. Children usually present with a mildly painful mass, which prompts diagnostic imaging studies. The rarity of this condition often presents a diagnostic challenge. Correct diagnosis is crucial in guiding surgical management. To describe the characteristic imaging findings of juxtacortical chondroma in children. We identified all children who were diagnosed with juxtacortical chondroma between 1998 and 2012. A single experienced pediatric radiologist reviewed all diagnostic imaging studies, including plain radiographs, CT, MR and bone scans. Seven children (5 boys and 2 girls) with juxtacortical chondroma were identified, ranging in age from 6 years to 16 years (mean 12.3 years). Mild pain and a palpable mass were present in all seven children. Plain radiographs were available in 6/7, MR in 7/7, CT in 4/7 and skeletal scintigraphy in 5/7 children. Three lesions were located in the proximal humerus, with one each in the distal radius, distal femur, proximal tibia and scapula. Radiographic and CT features deemed highly suggestive of juxtacortical chondroma included cortical scalloping, underlying cortical sclerosis and overhanging margins. MRI features consistent with juxtacortical chondroma included isointensity to skeletal muscle on T1, marked hyperintensity on T2 and peripheral rim enhancement after contrast agent administration. One of seven lesions demonstrated intramedullary extension, and 2/7 showed adjacent soft-tissue edema. Juxtacortical chondroma is an uncommon benign lesion in children with characteristic features on plain radiographs, CT and MR. Recognition of these features is invaluable in guiding appropriate surgical management. (orig.)

  12. Mass-like extramedullary hematopoiesis: imaging features

    Ginzel, Andrew W. [Synergy Radiology Associates, Houston, TX (United States); Kransdorf, Mark J.; Peterson, Jeffrey J.; Garner, Hillary W. [Mayo Clinic, Department of Radiology, Jacksonville, FL (United States); Murphey, Mark D. [American Institute for Radiologic Pathology, Silver Spring, MD (United States)

    2012-08-15

    To report the imaging appearances of mass-like extramedullary hematopoiesis (EMH), to identify those features that are sufficiently characteristic to allow a confident diagnosis, and to recognize the clinical conditions associated with EMH and the relative incidence of mass-like disease. We retrospectively identified 44 patients with EMH; 12 of which (27%) had focal mass-like lesions and formed the study group. The study group consisted of 6 male and 6 female subjects with a mean age of 58 years (range 13-80 years). All 12 patients underwent CT imaging and 3 of the 12 patients had undergone additional MR imaging. The imaging characteristics of the extramedullary hematopoiesis lesions in the study group were analyzed and recorded. The patient's clinical presentation, including any condition associated with extramedullary hematopoiesis, was also recorded. Ten of the 12 (83%) patients had one or more masses located along the axial skeleton. Of the 10 patients with axial masses, 9 (90%) had multiple masses and 7 (70%) demonstrated internal fat. Eight patients (80%) had paraspinal masses and 4 patients (40%) had presacral masses. Seven patients (70%) had splenomegaly. Eleven of the 12 patients had a clinical history available for review. A predisposing condition for extramedullary hematopoiesis was present in 10 patients and included various anemias (5 cases; 45%), myelofibrosis/myelodysplastic syndrome (4 cases; 36%), and marrow proliferative disorder (1 case; 9%). One patient had no known predisposing condition. Mass-like extramedullary hematopoiesis most commonly presents as multiple, fat-containing lesions localized to the axial skeleton. When these imaging features are identified, extramedullary hematopoiesis should be strongly considered, particularly when occurring in the setting of a predisposing medical condition. (orig.)

  13. Imaging features of cardiac myxoma

    Yang Youyou; Zheng Lili; Li Xiangmin; Zhou Xuhui; Kuang Jianyi; Zhang Wenzhao

    2007-01-01

    Objective: To study the imaging features of cardiac myxoma and their diagnostic values. Methods: Twenty-two patrents with cardiac myxoma were reviewed retrospectively for the clinical, pathologic, and radiologic findings. Posteroanterior and lateral chest radiographs, American Imatron C-150 XP Electron Beam CT examination, and Germany Siemens 1.5T Magnetom Vision MR scan were performed on every patient. Results: (1) Radiographs of 17 patients with left atrial myxoma showed evidence of mitral valve obstruction in 14(82.3%), radiographs of 5 patients with right atrial myxoma demonstrated right atrium enlargement in 3(60%) respectively. (2) CT scans of 22 myxomas demonstrated 18 (81.8%) lesions were hypoattenuated and 4 (19.1%) were isoattenuated relative to the myocardium. Calcification or ossification was seen in 3 patients. All myxomas apart from massive one were found attaching to the atrial septum. Movie mode could dis- play the movement of myxoma across the atrioventicular valves. (3) MRI studies of 22 myxomas showed 19 (86.3%) heterogeneous signal intensity and 3 (13.7%) homogeneous. They exhibited slight high or homogeneous signal intensity with both T 1 - and T 2 -weighted sequences, and low signal intensity with cine gradient recalled echo sequences. Point of attachment was visible in 21 (95.4%) cases. Conclusion: The typical radiograph sign of cardiac myxomas is mitral valve obstruction, CT and MR can demonstrate intracavitary lobular masses attacthing to artrial spetum. The latter two kinds of examinations not only provide accurate assessment of the size, location, and attachment point of these lesions, but also have important qualitative diagnostic advantage. (authors)

  14. MR imaging features of hemispherical spondylosclerosis

    Vicentini, Joao R.T.; Martinez-Salazar, Edgar L.; Chang, Connie Y.; Bredella, Miriam A.; Rosenthal, Daniel I.; Torriani, Martin [Massachusetts General Hospital and Harvard Medical School, Division of Musculoskeletal Imaging and Intervention, Department of Radiology, Boston, MA (United States)

    2017-10-15

    Hemispherical spondylosclerosis (HS) is a rare degenerative entity characterized by dome-shaped sclerosis of a single vertebral body that may pose a diagnostic dilemma. The goal of this study was to describe the MR imaging features of HS. We identified spine radiographs and CT examinations of subjects with HS who also had MR imaging for correlation. Two musculoskeletal radiologists independently assessed sclerosis characteristics, presence of endplate erosions, marrow signal intensity, and disk degeneration (Pfirrmann scale). We identified 11 subjects (six males, five females, mean 48 ± 10 years) with radiographic/CT findings of HS. The most commonly affected vertebral body was L4 (6/11; 55%). On MR imaging, variable signal intensity was noted, being most commonly low on T1 (8/11, 73%) and high on fat-suppressed T2-weighted (8/11, 73%) images. In two subjects, diffuse post-contrast enhancement was seen in the lesion. Moderate disk degeneration and endplate bone erosions adjacent to sclerosis were present in all subjects. Erosions of the opposite endplate were present in two subjects (2/11, 18%). CT data from nine subjects showed the mean attenuation value of HS was 472 ± 96 HU. HS appearance on MR imaging is variable and may not correlate with the degree of sclerosis seen on radiographs or CT. Disk degenerative changes and asymmetric endplate erosions are consistent markers of HS. (orig.)

  15. Identifying Image Manipulation Software from Image Features

    2015-03-26

    scales”. Educational and Psychological Measurement, 20(1):37, 1960. 7. Committee, Technical Standardization. Exchangeable image file format for digital...Digital Forensics. Springer, 2005. 23. Photography, Technical Committee. Photography and graphic technology - Ex- tended colour encodings for digital image

  16. Solving jigsaw puzzles using image features

    Nielsen, Ture R.; Drewsen, Peter; Hansen, Klaus

    2008-01-01

    In this article, we describe a method for automatic solving of the jigsaw puzzle problem based on using image features instead of the shape of the pieces. The image features are used for obtaining an accurate measure for edge similarity to be used in a new edge matching algorithm. The algorithm i...

  17. Image fusion using sparse overcomplete feature dictionaries

    Brumby, Steven P.; Bettencourt, Luis; Kenyon, Garrett T.; Chartrand, Rick; Wohlberg, Brendt

    2015-10-06

    Approaches for deciding what individuals in a population of visual system "neurons" are looking for using sparse overcomplete feature dictionaries are provided. A sparse overcomplete feature dictionary may be learned for an image dataset and a local sparse representation of the image dataset may be built using the learned feature dictionary. A local maximum pooling operation may be applied on the local sparse representation to produce a translation-tolerant representation of the image dataset. An object may then be classified and/or clustered within the translation-tolerant representation of the image dataset using a supervised classification algorithm and/or an unsupervised clustering algorithm.

  18. Infrared image enhancement with learned features

    Fan, Zunlin; Bi, Duyan; Ding, Wenshan

    2017-11-01

    Due to the variation of imaging environment and limitations of infrared imaging sensors, infrared images usually have some drawbacks: low contrast, few details and indistinct edges. Hence, to promote the applications of infrared imaging technology, it is essential to improve the qualities of infrared images. To enhance image details and edges adaptively, we propose an infrared image enhancement method under the proposed image enhancement scheme. On the one hand, on the assumption of high-quality image taking more evident structure singularities than low-quality images, we propose an image enhancement scheme that depends on the extractions of structure features. On the other hand, different from the current image enhancement algorithms based on deep learning networks that try to train and build the end-to-end mappings on improving image quality, we analyze the significance of first layer in Stacked Sparse Denoising Auto-encoder and propose a novel feature extraction for the proposed image enhancement scheme. Experiment results prove that the novel feature extraction is free from some artifacts on the edges such as blocking artifacts, ;gradient reversal;, and pseudo contours. Compared with other enhancement methods, the proposed method achieves the best performance in infrared image enhancement.

  19. Imaging features of colovesical fistulae on MRI.

    Tang, Y Z; Booth, T C; Swallow, D; Shahabuddin, K; Thomas, M; Hanbury, D; Chang, S; King, C

    2012-10-01

    MRI is routinely used in the investigation of colovesical fistulae at our institute. Several papers have alluded to its usefulness in achieving the diagnosis; however, there is a paucity of literature on its imaging findings. Our objective was to quantify the MRI characteristics of these fistulae. We selected all cases over a 4-year period with a final clinical diagnosis of colovesical fistula which had been investigated with MRI. The MRI scans were reviewed in a consensus fashion by two consultant uroradiologists. Their MRI features were quantified. There were 40 cases of colovesical fistulae. On MRI, the fistula morphology consistently fell into three patterns. The most common pattern (71%) demonstrated an intervening abscess between the bowel wall and bladder wall. The second pattern (15%) had a visible track between the affected bowel and bladder. The third pattern (13%) was a complete loss of fat plane between the affected bladder and bowel wall. MRI correctly determined the underlying aetiology in 63% of cases. MRI is a useful imaging modality in the diagnosis of colovesical fistulae. The fistulae appear to have three characteristic morphological patterns that may aid future diagnoses of colovesical fistulae. To the authors' knowledge, this is the first publication of the MRI findings in colovesical fistulae.

  20. Feature extraction for magnetic domain images of magneto-optical recording films using gradient feature segmentation

    Quanqing, Zhu.; Xinsai, Wang; Xuecheng, Zou; Haihua, Li; Xiaofei, Yang

    2002-01-01

    In this paper, we present a method to realize feature extraction on low contrast magnetic domain images of magneto-optical recording films. The method is based on the following three steps: first, Lee-filtering method is adopted to realize pre-filtering and noise reduction; this is followed by gradient feature segmentation, which separates the object area from the background area; finally the common linking method is adopted and the characteristic parameters of magnetic domain are calculated. We describe these steps with particular emphasis on the gradient feature segmentation. The results show that this method has advantages over other traditional ones for feature extraction of low contrast images

  1. Feature hashing for fast image retrieval

    Yan, Lingyu; Fu, Jiarun; Zhang, Hongxin; Yuan, Lu; Xu, Hui

    2018-03-01

    Currently, researches on content based image retrieval mainly focus on robust feature extraction. However, due to the exponential growth of online images, it is necessary to consider searching among large scale images, which is very timeconsuming and unscalable. Hence, we need to pay much attention to the efficiency of image retrieval. In this paper, we propose a feature hashing method for image retrieval which not only generates compact fingerprint for image representation, but also prevents huge semantic loss during the process of hashing. To generate the fingerprint, an objective function of semantic loss is constructed and minimized, which combine the influence of both the neighborhood structure of feature data and mapping error. Since the machine learning based hashing effectively preserves neighborhood structure of data, it yields visual words with strong discriminability. Furthermore, the generated binary codes leads image representation building to be of low-complexity, making it efficient and scalable to large scale databases. Experimental results show good performance of our approach.

  2. Histological image classification using biologically interpretable shape-based features

    Kothari, Sonal; Phan, John H; Young, Andrew N; Wang, May D

    2013-01-01

    Automatic cancer diagnostic systems based on histological image classification are important for improving therapeutic decisions. Previous studies propose textural and morphological features for such systems. These features capture patterns in histological images that are useful for both cancer grading and subtyping. However, because many of these features lack a clear biological interpretation, pathologists may be reluctant to adopt these features for clinical diagnosis. We examine the utility of biologically interpretable shape-based features for classification of histological renal tumor images. Using Fourier shape descriptors, we extract shape-based features that capture the distribution of stain-enhanced cellular and tissue structures in each image and evaluate these features using a multi-class prediction model. We compare the predictive performance of the shape-based diagnostic model to that of traditional models, i.e., using textural, morphological and topological features. The shape-based model, with an average accuracy of 77%, outperforms or complements traditional models. We identify the most informative shapes for each renal tumor subtype from the top-selected features. Results suggest that these shapes are not only accurate diagnostic features, but also correlate with known biological characteristics of renal tumors. Shape-based analysis of histological renal tumor images accurately classifies disease subtypes and reveals biologically insightful discriminatory features. This method for shape-based analysis can be extended to other histological datasets to aid pathologists in diagnostic and therapeutic decisions

  3. Tumor recognition in wireless capsule endoscopy images using textural features and SVM-based feature selection.

    Li, Baopu; Meng, Max Q-H

    2012-05-01

    Tumor in digestive tract is a common disease and wireless capsule endoscopy (WCE) is a relatively new technology to examine diseases for digestive tract especially for small intestine. This paper addresses the problem of automatic recognition of tumor for WCE images. Candidate color texture feature that integrates uniform local binary pattern and wavelet is proposed to characterize WCE images. The proposed features are invariant to illumination change and describe multiresolution characteristics of WCE images. Two feature selection approaches based on support vector machine, sequential forward floating selection and recursive feature elimination, are further employed to refine the proposed features for improving the detection accuracy. Extensive experiments validate that the proposed computer-aided diagnosis system achieves a promising tumor recognition accuracy of 92.4% in WCE images on our collected data.

  4. Featured Image: Simulating Planetary Gaps

    Kohler, Susanna

    2017-03-01

    The authors model of howthe above disk would look as we observe it in a scattered-light image. The morphology of the gap can be used to estimate the mass of the planet that caused it. [Dong Fung 2017]The above image from a computer simulation reveals the dust structure of a protoplanetary disk (with the star obscured in the center) as a newly formed planet orbits within it. A recent study by Ruobing Dong (Steward Observatory, University of Arizona) and Jeffrey Fung (University of California, Berkeley) examines how we can determine mass of such a planet based on our observations of the gap that the planet opens in the disk as it orbits. The authors models help us to better understand how our observations of gaps might change if the disk is inclined relative to our line of sight, and how we can still constrain the mass of the gap-opening planet and the viscosity of the disk from the scattered-light images we have recently begun to obtain of distant protoplanetary disks. For more information, check out the paper below!CitationRuobing Dong () and Jeffrey Fung () 2017 ApJ 835 146. doi:10.3847/1538-4357/835/2/146

  5. Quantitative imaging features: extension of the oncology medical image database

    Patel, M. N.; Looney, P. T.; Young, K. C.; Halling-Brown, M. D.

    2015-03-01

    Radiological imaging is fundamental within the healthcare industry and has become routinely adopted for diagnosis, disease monitoring and treatment planning. With the advent of digital imaging modalities and the rapid growth in both diagnostic and therapeutic imaging, the ability to be able to harness this large influx of data is of paramount importance. The Oncology Medical Image Database (OMI-DB) was created to provide a centralized, fully annotated dataset for research. The database contains both processed and unprocessed images, associated data, and annotations and where applicable expert determined ground truths describing features of interest. Medical imaging provides the ability to detect and localize many changes that are important to determine whether a disease is present or a therapy is effective by depicting alterations in anatomic, physiologic, biochemical or molecular processes. Quantitative imaging features are sensitive, specific, accurate and reproducible imaging measures of these changes. Here, we describe an extension to the OMI-DB whereby a range of imaging features and descriptors are pre-calculated using a high throughput approach. The ability to calculate multiple imaging features and data from the acquired images would be valuable and facilitate further research applications investigating detection, prognosis, and classification. The resultant data store contains more than 10 million quantitative features as well as features derived from CAD predictions. Theses data can be used to build predictive models to aid image classification, treatment response assessment as well as to identify prognostic imaging biomarkers.

  6. Robust Image Hashing Using Radon Transform and Invariant Features

    Y.L. Liu

    2016-09-01

    Full Text Available A robust image hashing method based on radon transform and invariant features is proposed for image authentication, image retrieval, and image detection. Specifically, an input image is firstly converted into a counterpart with a normalized size. Then the invariant centroid algorithm is applied to obtain the invariant feature point and the surrounding circular area, and the radon transform is employed to acquire the mapping coefficient matrix of the area. Finally, the hashing sequence is generated by combining the feature vectors and the invariant moments calculated from the coefficient matrix. Experimental results show that this method not only can resist against the normal image processing operations, but also some geometric distortions. Comparisons of receiver operating characteristic (ROC curve indicate that the proposed method outperforms some existing methods in classification between perceptual robustness and discrimination.

  7. Image Processing and Features Extraction of Fingerprint Images ...

    To demonstrate the importance of the image processing of fingerprint images prior to image enrolment or comparison, the set of fingerprint images in databases (a) and (b) of the FVC (Fingerprint Verification Competition) 2000 database were analyzed using a features extraction algorithm. This paper presents the results of ...

  8. MR imaging features of hydrocephalus

    Zinn, W.; George, A.E.; Leon, M.J. de; Pinto, R.S.; Litt, A.W.; Kricheff, I.I.

    1990-01-01

    This paper compares the midsagittal dimensions of the third and lateral ventricles on MR images in cases of known hydrocephalus and atrophy. Cranial MR studies of 55 age-matched patients, 21 with known hydrocephalus and 28 with atrophy were retrospectively reviewed. Measurements of the genu-to-splenium diameter (G-S) and anterior commissure to corpus callosum distance (AC-CC) were obtained. A volumetric index (VI) was calculated as (G-S) x (AC-CC), and a ratio was calculated as (AC-CC)/(G-S). The volumetric index (VI) was 22% larger in the hydrocephalus group (Student two-tail t test, P > .001,t = -4.23). Sixty-two percent of hydrocephalus patients had either ratios greater than 56% or VIs of a least 20 cm 2

  9. Saliency image of feature building for image quality assessment

    Ju, Xinuo; Sun, Jiyin; Wang, Peng

    2011-11-01

    The purpose and method of image quality assessment are quite different for automatic target recognition (ATR) and traditional application. Local invariant feature detectors, mainly including corner detectors, blob detectors and region detectors etc., are widely applied for ATR. A saliency model of feature was proposed to evaluate feasibility of ATR in this paper. The first step consisted of computing the first-order derivatives on horizontal orientation and vertical orientation, and computing DoG maps in different scales respectively. Next, saliency images of feature were built based auto-correlation matrix in different scale. Then, saliency images of feature of different scales amalgamated. Experiment were performed on a large test set, including infrared images and optical images, and the result showed that the salient regions computed by this model were consistent with real feature regions computed by mostly local invariant feature extraction algorithms.

  10. Imaging features of breast echinococcus granulosus

    Zeng Li; Liu Fanming; Gong Yue; Ge Jinmei; Li Xianjun; Shi Minxin; Guo Yongzhong

    2012-01-01

    Objective: To demonstrate the X-ray and CT features of breast hydatid disease. Methods: Of 11 patients with pathologically confirmed breast Echinococcus hydatid disease were collected and the X-ray and CT image data were analyzed. Results: Of 11 patients with hydatid cysts,single cyst was found in 9 patients which one cyst was ruptured due to trauma, multiple cyst in 2 patients. Mammography showed small or large shadow in different size, with low or high density and smooth margin. Calcification was found in 5 and 2 patients with egg shell-like calcification along the wall of cyst, 3 patients with spotted calcification within cyst. One case had cavity-like change (annular solar eclipse sign). Cystic lesion with a complete capsule was demonstrated on CT scan in 1 patient. Conclusion: Molybdenum target mammography can accurately display the imaging characteristics of hydatid cyst and improve the diagnostic ability of breast hydatid cyst in combination with clinical and epidemiological data. (authors)

  11. Feature coding for image representation and recognition

    Huang, Yongzhen

    2015-01-01

    This brief presents a comprehensive introduction to feature coding, which serves as a key module for the typical object recognition pipeline. The text offers a rich blend of theory and practice while reflects the recent developments on feature coding, covering the following five aspects: (1) Review the state-of-the-art, analyzing the motivations and mathematical representations of various feature coding methods; (2) Explore how various feature coding algorithms evolve along years; (3) Summarize the main characteristics of typical feature coding algorithms and categorize them accordingly; (4) D

  12. Characteristics of image converters and image intensifiers

    Gurvich, A.M.; Shamanov, A.A.; Rozenberg, A.M.; Fajnberg, V.S.; Kavtorova, V.P.; Salyuk, L.V.; Yakovleva, F.B.

    1978-01-01

    The characteristics of image converters and image intensifiers, which determine the range of the X-radiation dose rates used and the image quality, are considered. The equations for calculating the requirements to be imposed on the separate intensifier elements from known parameters of other elements with an allowance for the nonlinearity of the television system and the role of fluctuation in the space distribution of X-radiation quanta are given

  13. SAR Image Classification Based on Its Texture Features

    LI Pingxiang; FANG Shenghui

    2003-01-01

    SAR images not only have the characteristics of all-ay, all-eather, but also provide object information which is different from visible and infrared sensors. However, SAR images have some faults, such as more speckles and fewer bands. The authors conducted the experiments of texture statistics analysis on SAR image features in order to improve the accuracy of SAR image interpretation.It is found that the texture analysis is an effective method for improving the accuracy of the SAR image interpretation.

  14. Feature Detector and Descriptor for Medical Images

    Sargent, Dusty; Chen, Chao-I.; Tsai, Chang-Ming; Wang, Yuan-Fang; Koppel, Daniel

    2009-02-01

    The ability to detect and match features across multiple views of a scene is a crucial first step in many computer vision algorithms for dynamic scene analysis. State-of-the-art methods such as SIFT and SURF perform successfully when applied to typical images taken by a digital camera or camcorder. However, these methods often fail to generate an acceptable number of features when applied to medical images, because such images usually contain large homogeneous regions with little color and intensity variation. As a result, tasks like image registration and 3D structure recovery become difficult or impossible in the medical domain. This paper presents a scale, rotation and color/illumination invariant feature detector and descriptor for medical applications. The method incorporates elements of SIFT and SURF while optimizing their performance on medical data. Based on experiments with various types of medical images, we combined, adjusted, and built on methods and parameter settings employed in both algorithms. An approximate Hessian based detector is used to locate scale invariant keypoints and a dominant orientation is assigned to each keypoint using a gradient orientation histogram, providing rotation invariance. Finally, keypoints are described with an orientation-normalized distribution of gradient responses at the assigned scale, and the feature vector is normalized for contrast invariance. Experiments show that the algorithm detects and matches far more features than SIFT and SURF on medical images, with similar error levels.

  15. Field application of feature-enhanced imaging

    Mucciardi, A.N.

    1988-01-01

    One of the more challenging ultrasonic inspection problems is bimetallic weld inspection or, in general, dissimilar metal welds. These types of welds involve complicated geometries and various mixtures of materials. Attempts to address this problem with imaging alone have fallen short of desired goals. The probable reason for this is the lack of information supplied by imaging systems, which are limited to amplitude and time displays. Having RF information available for analysis greatly enhances the information obtainable from dissimilar metal welds and, coupled with the spatial map generated by an imaging system, can significantly improve the reliability of dissimilar metal weld inspections. Ultra Image and TestPro are, respectively, an imaging system and a feature-based signal analysis system. The purpose of this project is to integrate these two systems to produce a feature-enhanced imaging system. This means that a software link is established between Ultra Image and the PC-based TestPro system so that the user of the combined system can perform all the usual imaging functions and also have available a wide variety of RF signal analysis functions. The analysis functions include waveform feature-based pattern recognition as well as artificial intelligence/expert system techniques

  16. Image characteristics of adrenal ganglioneuroma

    Ohishi, Yukihiko; Machida, Toyohei; Tashiro, Kazuya

    1994-01-01

    The image characteristics of adrenal ganglioneuroma observed in various types of imaging were examined. The subjects of the study were 6 cases of adrenal ganglioneuroma which had been histologically confirmed: the ages of the subjects ranged from 25 to 54 (mean age 41), and the maximum diameter of the tumors were 4 to 7 cm. The diagnostic methods employed in their detection were ultrasonography (US) and computed tomography (CT) in all 6 cases, magnetic resonance imaging (MRI) in 5 cases, and arteriography in 3 cases. On US and CT images, all 6 tumors had clear and smooth boundaries, and were homogeneous. They were hypoechoic on US images and low density on CT images. Of the 5 cases for which contrast CT images had been obtained, one showed a slightly heterogeneous staining. On MRI, the tumors were of lower intensity in comparison to the liver in 4 of 5 cases on the T 1 -weighted images, and the internal structure was homogeneous in 3 cases and heterogeneous in one case. The remaining one case was of isointensity and homogeneous. On the T 2 -weighted images, all 5 cases were of high intensity and heterogeneous. The blood flow distribution in the 3 tumors which were examined by Gd-DTPA dynamic MRI was low and of isointensity to the liver: 2 were heterogeneous and one was homogeneous. T 1 -enhanced images were obtained in 4 cases: 2 were of high intensity and heterogeneous, one was of isointensity and homogeneous, and one was of heterogeneously isointensity. Arteriography indicated that all 3 cases were hypovascular and no vascularization or ruptures were evident. It appeared that the imaging characteristics of adrenal ganglioneuroma were as follows: (1) homogeneous on US and CT images; (2) hypoechoic on US images, low density on CT images and little enhancement on contrast CT images; (3) of low intensity homogeneous on T 1 -weighted images and of high intensity heterogeneous on T 2 -weighted images and little blood flow distribution on dynamic MRI. (author)

  17. Hemorrhage detection in MRI brain images using images features

    Moraru, Luminita; Moldovanu, Simona; Bibicu, Dorin; Stratulat (Visan), Mirela

    2013-11-01

    The abnormalities appear frequently on Magnetic Resonance Images (MRI) of brain in elderly patients presenting either stroke or cognitive impairment. Detection of brain hemorrhage lesions in MRI is an important but very time-consuming task. This research aims to develop a method to extract brain tissue features from T2-weighted MR images of the brain using a selection of the most valuable texture features in order to discriminate between normal and affected areas of the brain. Due to textural similarity between normal and affected areas in brain MR images these operation are very challenging. A trauma may cause microstructural changes, which are not necessarily perceptible by visual inspection, but they could be detected by using a texture analysis. The proposed analysis is developed in five steps: i) in the pre-processing step: the de-noising operation is performed using the Daubechies wavelets; ii) the original images were transformed in image features using the first order descriptors; iii) the regions of interest (ROIs) were cropped from images feature following up the axial symmetry properties with respect to the mid - sagittal plan; iv) the variation in the measurement of features was quantified using the two descriptors of the co-occurrence matrix, namely energy and homogeneity; v) finally, the meaningful of the image features is analyzed by using the t-test method. P-value has been applied to the pair of features in order to measure they efficacy.

  18. 14 CFR 35.7 - Features and characteristics.

    2010-01-01

    ... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Features and characteristics. 35.7 Section... AIRWORTHINESS STANDARDS: PROPELLERS General § 35.7 Features and characteristics. (a) The propeller may not have features or characteristics, revealed by any test or analysis or known to the applicant, that make it...

  19. MR Imaging Features of Obturator Internus Bursa of the Hip

    Hwang, Ji Young; Lee, Sun Wha; Kim, Jong Oh

    2008-01-01

    The authors report two cases with distension of the obturator internus bursa identified on MR images, and describe the location and characteristic features of obturator internus bursitis; the 'boomerang'-shaped fluid distension between the obturator internus tendon and the posterior grooved surface of the ischium

  20. MR Imaging Features of Obturator Internus Bursa of the Hip

    Hwang, Ji Young; Lee, Sun Wha; Kim, Jong Oh [School of Medicine, Ewha Womans University, Seoul (Korea, Republic of)

    2008-08-15

    The authors report two cases with distension of the obturator internus bursa identified on MR images, and describe the location and characteristic features of obturator internus bursitis; the 'boomerang'-shaped fluid distension between the obturator internus tendon and the posterior grooved surface of the ischium

  1. Discrimination Features of Chromatic Figures in Various Background Characteristics

    Y A Chudina

    2013-12-01

    Full Text Available Visual recognition features of images with different figure-ground segregation have been considered in the article. The research was carried out within the framework of Sokolov and Izmaylov’s spherical model and was based on the construction of color objects discrimination models depending on the changes of background characteristics. The research has revealed the specific influence of the background on figure discrimination. The derived models reflect the mechanisms of the all-in-one perception of the visual space.

  2. Imaging features of benign adrenal cysts

    Sanal, Hatice Tuba; Kocaoglu, Murat; Yildirim, Duzgun; Bulakbasi, Nail; Guvenc, Inanc; Tayfun, Cem; Ucoz, Taner

    2006-01-01

    Benign adrenal gland cysts (BACs) are rare lesions with a variable histological spectrum and may mimic not only each other but also malignant ones. We aimed to review imaging features of BACs which can be helpful in distinguishing each entity and determining the subsequent appropriate management

  3. Optimization of wavelet decomposition for image compression and feature preservation.

    Lo, Shih-Chung B; Li, Huai; Freedman, Matthew T

    2003-09-01

    A neural-network-based framework has been developed to search for an optimal wavelet kernel that can be used for a specific image processing task. In this paper, a linear convolution neural network was employed to seek a wavelet that minimizes errors and maximizes compression efficiency for an image or a defined image pattern such as microcalcifications in mammograms and bone in computed tomography (CT) head images. We have used this method to evaluate the performance of tap-4 wavelets on mammograms, CTs, magnetic resonance images, and Lena images. We found that the Daubechies wavelet or those wavelets with similar filtering characteristics can produce the highest compression efficiency with the smallest mean-square-error for many image patterns including general image textures as well as microcalcifications in digital mammograms. However, the Haar wavelet produces the best results on sharp edges and low-noise smooth areas. We also found that a special wavelet whose low-pass filter coefficients are 0.32252136, 0.85258927, 1.38458542, and -0.14548269) produces the best preservation outcomes in all tested microcalcification features including the peak signal-to-noise ratio, the contrast and the figure of merit in the wavelet lossy compression scheme. Having analyzed the spectrum of the wavelet filters, we can find the compression outcomes and feature preservation characteristics as a function of wavelets. This newly developed optimization approach can be generalized to other image analysis applications where a wavelet decomposition is employed.

  4. Remote Sensing Image Registration Using Multiple Image Features

    Kun Yang

    2017-06-01

    Full Text Available Remote sensing image registration plays an important role in military and civilian fields, such as natural disaster damage assessment, military damage assessment and ground targets identification, etc. However, due to the ground relief variations and imaging viewpoint changes, non-rigid geometric distortion occurs between remote sensing images with different viewpoint, which further increases the difficulty of remote sensing image registration. To address the problem, we propose a multi-viewpoint remote sensing image registration method which contains the following contributions. (i A multiple features based finite mixture model is constructed for dealing with different types of image features. (ii Three features are combined and substituted into the mixture model to form a feature complementation, i.e., the Euclidean distance and shape context are used to measure the similarity of geometric structure, and the SIFT (scale-invariant feature transform distance which is endowed with the intensity information is used to measure the scale space extrema. (iii To prevent the ill-posed problem, a geometric constraint term is introduced into the L2E-based energy function for better behaving the non-rigid transformation. We evaluated the performances of the proposed method by three series of remote sensing images obtained from the unmanned aerial vehicle (UAV and Google Earth, and compared with five state-of-the-art methods where our method shows the best alignments in most cases.

  5. RESEARCH ON FOREST FLAME RECOGNITION ALGORITHM BASED ON IMAGE FEATURE

    Z. Wang

    2017-09-01

    Full Text Available In recent years, fire recognition based on image features has become a hotspot in fire monitoring. However, due to the complexity of forest environment, the accuracy of forest fireworks recognition based on image features is low. Based on this, this paper proposes a feature extraction algorithm based on YCrCb color space and K-means clustering. Firstly, the paper prepares and analyzes the color characteristics of a large number of forest fire image samples. Using the K-means clustering algorithm, the forest flame model is obtained by comparing the two commonly used color spaces, and the suspected flame area is discriminated and extracted. The experimental results show that the extraction accuracy of flame area based on YCrCb color model is higher than that of HSI color model, which can be applied in different scene forest fire identification, and it is feasible in practice.

  6. Imaging characteristics of primary cranial Ewing sarcoma

    Li, Wai-Yung; Saunders, Dawn E.; Brock, Penelope

    2005-01-01

    Ewing sarcoma accounts for 10-15% of all childhood malignant bone tumours and is second in prevalence to osteosarcoma. The skull bones are an unusual site of origin of primary Ewing sarcoma in children. Previous reports concentrate on the neurosurgical aspects and relatively good outcome compared to other bone tumours of the calvarium. Reported cases mainly describe the imaging characteristics on CT. To describe the MRI and CT features of primary cranial Ewing sarcoma. The neuroimaging of three cases of primary cranial Ewing sarcoma are reviewed. Our three cases show an extra-axial mass that is high attenuation on CT and low signal on T2-weighted MRI. Haemorrhagic components, dural extension and contrast enhancement are also characteristic features. CT attenuation and magnetic resonance signal characteristics reflect sheets of densely packed cells seen in Ewing sarcoma. (orig.)

  7. Barrett's esophagus: clinical features, obesity, and imaging.

    Quigley, Eamonn M M

    2011-09-01

    The following includes commentaries on clinical features and imaging of Barrett\\'s esophagus (BE); the clinical factors that influence the development of BE; the influence of body fat distribution and central obesity; the role of adipocytokines and proinflammatory markers in carcinogenesis; the role of body mass index (BMI) in healing of Barrett\\'s epithelium; the role of surgery in prevention of carcinogenesis in BE; the importance of double-contrast esophagography and cross-sectional images of the esophagus; and the value of positron emission tomography\\/computed tomography.

  8. Featured Image: Diamonds in a Meteorite

    Kohler, Susanna

    2018-04-01

    This unique image which measures only 60 x 80 micrometers across reveals details in the Kapoeta meteorite, an 11-kg stone that fell in South Sudan in 1942. The sparkle in the image? A cluster of nanodiamonds discovered embedded in the stone in a recent study led by Yassir Abdu (University of Sharjah, United Arab Emirates). Abdu and collaborators showed that these nanodiamonds have similar spectral features to the interiors of dense interstellar clouds and they dont show any signs of shock features. This may suggest that the nanodiamonds were formed by condensation of nebular gases early in the history of the solar system. The diamonds were trapped in the surface material of the Kapoeta meteorites parent body, thought to be the asteroid Vesta. To read more about the authors study, check out the original article below.CitationYassir A. Abdu et al 2018 ApJL 856 L9. doi:10.3847/2041-8213/aab433

  9. Special feature on imaging systems and techniques

    Yang, Wuqiang; Giakos, George

    2013-07-01

    The IEEE International Conference on Imaging Systems and Techniques (IST'2012) was held in Manchester, UK, on 16-17 July 2012. The participants came from 26 countries or regions: Austria, Brazil, Canada, China, Denmark, France, Germany, Greece, India, Iran, Iraq, Italy, Japan, Korea, Latvia, Malaysia, Norway, Poland, Portugal, Sweden, Switzerland, Taiwan, Tunisia, UAE, UK and USA. The technical program of the conference consisted of a series of scientific and technical sessions, exploring physical principles, engineering and applications of new imaging systems and techniques, as reflected by the diversity of the submitted papers. Following a rigorous review process, a total of 123 papers were accepted, and they were organized into 30 oral presentation sessions and a poster session. In addition, six invited keynotes were arranged. The conference not only provided the participants with a unique opportunity to exchange ideas and disseminate research outcomes but also paved a way to establish global collaboration. Following the IST'2012, a total of 55 papers, which were technically extended substantially from their versions in the conference proceeding, were submitted as regular papers to this special feature of Measurement Science and Technology . Following a rigorous reviewing process, 25 papers have been finally accepted for publication in this special feature and they are organized into three categories: (1) industrial tomography, (2) imaging systems and techniques and (3) image processing. These papers not only present the latest developments in the field of imaging systems and techniques but also offer potential solutions to existing problems. We hope that this special feature provides a good reference for researchers who are active in the field and will serve as a catalyst to trigger further research. It has been our great pleasure to be the guest editors of this special feature. We would like to thank the authors for their contributions, without which it would

  10. Imaging features of skeletal changes in children with Gaucher disease

    Zhang Ningning; Duan Xiaomin; Duan Yanlong

    2011-01-01

    Objective: To discuss the imaging features of skeletal changes in children with Gaucher disease on X-ray and MRI images. Methods: One hundred and nine children with Gaucher disease were enrolled in this study. They all received routine X-ray for spine with anterior-posterior (A-P) and lateral view and bilateral femurs with A-P view. Among them, 18 patients received X-ray for pelvic with A-P view, 14 patients received X-ray for left wrist with A-P view, and 14 patients received MRI scan for femur. The MRI scan included T 1 -weighted imaging, T 2 -weighted imaging and fat-suppressed T 2 -weighted imaging with short tau inversion recovery (STIR) sequence. The imaging features of the X-ray and MRI images were analyzed retrospectively. Results: The most common feature is osteoporosis, which presented in 91 cases (83.5%). Besides this, decreased density of metaphysis occurred in 86 cases (78.9%), erlenmeyer flask deformity of metaphysis occurred in 89 patients (81.7%), thinner cortex occurred in 69 cases (63.3%), osteolytic destruction occurred in. 31 cases (28.4%), pathological fractures occurred in 26 cases (23.9%), osteosclerosis occurred in 12 cases (11.0%). cystic degeneration of bone occurred in 16 cases (14.7%), and dislocation of the hip occurred in 4 cases. All 14 patients received MRI presented abnormal signals. Among them, 4 patients presented low signal intensity both on T 1 -weighted and T 2 -weighted images in bone marrow, the other ten presented high signal intensity mixed in low signal intensity areas on T 2 - weighted and fat-suppressed T 2 -weighted images. Conclusions: The imaging features of skeletal changes in children with Gaucher disease are of some characteristics, which could provide useful information for the clinical treatment. (authors)

  11. Feature Evaluation for Building Facade Images - AN Empirical Study

    Yang, M. Y.; Förstner, W.; Chai, D.

    2012-08-01

    The classification of building facade images is a challenging problem that receives a great deal of attention in the photogrammetry community. Image classification is critically dependent on the features. In this paper, we perform an empirical feature evaluation task for building facade images. Feature sets we choose are basic features, color features, histogram features, Peucker features, texture features, and SIFT features. We present an approach for region-wise labeling using an efficient randomized decision forest classifier and local features. We conduct our experiments with building facade image classification on the eTRIMS dataset, where our focus is the object classes building, car, door, pavement, road, sky, vegetation, and window.

  12. Determination of the Image Complexity Feature in Pattern Recognition

    Veacheslav L. Perju

    2003-11-01

    Full Text Available The new image complexity informative feature is proposed. The experimental estimation of the image complexity is carried out. There are elaborated two optical-electronic processors for image complexity calculation. The determination of the necessary number of the image's digitization elements depending on the image complexity was carried out. The accuracy of the image complexity feature calculation was made.

  13. English Computer Discourse: Some Characteristic Features

    Tatjana Rusko

    2013-12-01

    Full Text Available The problem of virtual discourse is coming into focus of linguistic research. This interest results from the rapid spread of information technology, modern Internet culture incipience, a symbol of information revolution, new opportunities and threats that accompany computer civilization. The emergence of the communicative environment as a particular sphere of language actualization, necessitates new language means of communication or transformation and reframing the already existing ones. Obviously, it’s time to talk about the formation of a new discourse in the new communicative space – computer (electronic, virtual discourse, which subsequently may considerably affect the speech behavior of society. The present article makes an attempt to identify some linguistic and communicative features of virtual discourse. Computer discourse, being a sub-language of hybrid character, combines elements of oral and written discourse with its own specific features. It should be noted that in the context of information culture the problem of communication interaction is among the most topical issues in science and education. There is hardly any doubt that the study and advancement of virtual communication culture is one of higher education distinctive mission components.

  14. Imaging features of foot osteoid osteoma

    Shukla, Satyen; Clarke, Andrew W.; Saifuddin, Asif [Royal National Orthopaedic Hospital NHS Trust, Department of Radiology, Stanmore, Middlesex (United Kingdom)

    2010-07-15

    We performed a retrospective review of the imaging of nine patients with a diagnosis of foot osteoid osteoma (OO). Radiographs, computed tomography (CT) and magnetic resonance imaging (MRI) had been performed in all patients. Radiographic features evaluated were the identification of a nidus and cortical thickening. CT features noted were nidus location (affected bone - intramedullary, intracortical, subarticular) and nidus calcification. MRI features noted were the presence of an identifiable nidus, presence and grade of bone oedema and whether a joint effusion was identified. Of the nine patients, three were female and six male, with a mean age of 21 years (range 11-39 years). Classical symptoms of OO (night pain, relief with aspirin) were identified in five of eight (62.5%) cases (in one case, the medical records could not be retrieved). In five patients the lesion was located in the hindfoot (four calcaneus, one talus), while four were in the mid- or forefoot (two metatarsal and two phalangeal). Radiographs were normal in all patients with hindfoot OO. CT identified the nidus in all cases (89%) except one terminal phalanx lesion, while MRI demonstrated a nidus in six of nine cases (67%). The nidus was of predominantly intermediate signal intensity on T1-weighted (T1W) sequences, with intermediate to high signal intensity on T2-weighted (T2W) sequences. High-grade bone marrow oedema, limited to the affected bone and adjacent soft tissue oedema was identified in all cases. In a young patient with chronic hindfoot pain and a normal radiograph, MRI features suggestive of possible OO include extensive bone marrow oedema limited to one bone, with a possible nidus demonstrated in two-thirds of cases. The presence or absence of a nidus should be confirmed with high-resolution CT. (orig.)

  15. Feature extraction & image processing for computer vision

    Nixon, Mark

    2012-01-01

    This book is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in Matlab. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated. As one reviewer noted, ""The main strength of the proposed book is the exemplar code of the algorithms."" Fully updated with the latest developments in feature extraction, including expanded tutorials and new techniques, this new edition contains extensive new material on Haar wavelets, Viola-Jones, bilateral filt

  16. Cervical spine injury in the elderly: imaging features

    Ehara, S. [Dept. of Radiology, Iwate Medical University School of Medicine, Morioka (Japan); Shimamura, Tadashi [Dept. of Orthopedic Surgery, Iwate Medical University School of Medicine, Morioka (Japan)

    2001-01-01

    An increase in the elderly population has resulted in an increased incidence of cervical spine injury in this group. No specific type of cervical spine trauma is seen in the elderly, although dens fractures are reported to be common. Hyperextension injuries due to falling and the resultant central cord syndrome in the mid and lower cervical segments due to decreased elasticity as a result of spondylosis may be also characteristic. The imaging features of cervical spine injury are often modified by associated spondylosis deformans, DISH and other systemic disorders. The value of MR imaging in such cases is emphasized. (orig.)

  17. Research of image retrieval technology based on color feature

    Fu, Yanjun; Jiang, Guangyu; Chen, Fengying

    2009-10-01

    Recently, with the development of the communication and the computer technology and the improvement of the storage technology and the capability of the digital image equipment, more and more image resources are given to us than ever. And thus the solution of how to locate the proper image quickly and accurately is wanted.The early method is to set up a key word for searching in the database, but now the method has become very difficult when we search much more picture that we need. In order to overcome the limitation of the traditional searching method, content based image retrieval technology was aroused. Now, it is a hot research subject.Color image retrieval is the important part of it. Color is the most important feature for color image retrieval. Three key questions on how to make use of the color characteristic are discussed in the paper: the expression of color, the abstraction of color characteristic and the measurement of likeness based on color. On the basis, the extraction technology of the color histogram characteristic is especially discussed. Considering the advantages and disadvantages of the overall histogram and the partition histogram, a new method based the partition-overall histogram is proposed. The basic thought of it is to divide the image space according to a certain strategy, and then calculate color histogram of each block as the color feature of this block. Users choose the blocks that contain important space information, confirming the right value. The system calculates the distance between the corresponding blocks that users choosed. Other blocks merge into part overall histograms again, and the distance should be calculated. Then accumulate all the distance as the real distance between two pictures. The partition-overall histogram comprehensive utilizes advantages of two methods above, by choosing blocks makes the feature contain more spatial information which can improve performance; the distances between partition-overall histogram

  18. SAR Data Fusion Imaging Method Oriented to Target Feature Extraction

    Yang Wei

    2015-02-01

    Full Text Available To deal with the difficulty for target outlines extracting precisely due to neglect of target scattering characteristic variation during the processing of high-resolution space-borne SAR data, a novel fusion imaging method is proposed oriented to target feature extraction. Firstly, several important aspects that affect target feature extraction and SAR image quality are analyzed, including curved orbit, stop-and-go approximation, atmospheric delay, and high-order residual phase error. Furthermore, the corresponding compensation methods are addressed as well. Based on the analysis, the mathematical model of SAR echo combined with target space-time spectrum is established for explaining the space-time-frequency change rule of target scattering characteristic. Moreover, a fusion imaging strategy and method under high-resolution and ultra-large observation angle range conditions are put forward to improve SAR quality by fusion processing in range-doppler and image domain. Finally, simulations based on typical military targets are used to verify the effectiveness of the fusion imaging method.

  19. Features and characteristics of problem based learning

    Eser Ceker

    2016-12-01

    Full Text Available Throughout the years, there appears to be an increase in Problem Based Learning applications in education; and Problem Based Learning related research areas. The main aim of this research is to underline the fundamentals (basic elements of Problem Based Learning, investigate the dimensions of research approached to PBL oriented areas (with a look for the latest technology supported tools of Problem Based Learning. This research showed that the most researched characteristics of PBL are; teacher and student assessments on Problem Based Learning, Variety of disciplines in which Problem Based Learning strategies were tried and success evaluated, Using Problem Based Learning alone or with other strategies (Hybrid or Mix methods, Comparing Problem Based Learning with other strategies, and new trends and tendencies in Problem Based Learning related research. Our research may help us to identify the latest trends and tendencies referred to in the published studies related to “problem based learning” areas. In this research, Science Direct and Ulakbim were used as our main database resources. The sample of this study consists of 150 articles.

  20. Comparative imaging features of brucellar and tuberculous spondylitis

    Sharif, H.S.; Aldeyan, O.; Clark, D.C.; Madkour, M.M.

    1987-01-01

    Images obtained with various modalities in 17 patients with Brucella spondylitis and 12 patients with tuberculous spondylitis were analyzed in order to identify distinguishing features. All patients underwent radiography, 21 underwent bone scintigraphy, and all underwent high-resolution CT and/or MR imaging. Characteristic findings in Brucella spondylitis included a predilection for the lumbar spine, bone destruction limited to the end-plates and associated with sclerosis, and disk space collapse (16 of 19) with disk vacuum phenomenon in eight and localized soft-tissue edema. MR imaging showed diffuse increased signal in vertebrae, disks, and adjacent soft tissues on long repetition time/long echo time studies (four patients). Tuberculosis spondylitis was characterized by a midthoracic predilection, diffuse vertebral destruction with gibbus deformity, severe disk collapse, and extensive paraspinal abscesses. MR imaging findings (three patients) were similar to but more severe than findings in Brucella spondylitis

  1. Steganalysis based on reducing the differences of image statistical characteristics

    Wang, Ran; Niu, Shaozhang; Ping, Xijian; Zhang, Tao

    2018-04-01

    Compared with the process of embedding, the image contents make a more significant impact on the differences of image statistical characteristics. This makes the image steganalysis to be a classification problem with bigger withinclass scatter distances and smaller between-class scatter distances. As a result, the steganalysis features will be inseparate caused by the differences of image statistical characteristics. In this paper, a new steganalysis framework which can reduce the differences of image statistical characteristics caused by various content and processing methods is proposed. The given images are segmented to several sub-images according to the texture complexity. Steganalysis features are separately extracted from each subset with the same or close texture complexity to build a classifier. The final steganalysis result is figured out through a weighted fusing process. The theoretical analysis and experimental results can demonstrate the validity of the framework.

  2. Imaging features of intracranial solitary fibrous tumors

    Yu Shuilian; Man Yuping; Ma Longbai; Liu Ying; Wei Qiang; Zhu Youkai

    2012-01-01

    Objective: To summarize the imaging features of intracranial solitary fibrous tumors (ISFT). Methods: Ten patients with ISFT proven histopathologically were collected. Four cases had CT data and all cases had MR data. The imaging features and pathological results were retrospectively analyzed. Results: All cases were misdiagnosed as meningioma at pre-operation. All lesions arose from intracranial meninges including 5 lesions above the tentorium, 4 lesions beneath the tentorium and 1 lesion growing around the tentorium. The margins of all the masses were well defined, and 8 lesions presented multilobular shape. CT demonstrated hyerattenuated masses in all 4 lesions, smooth erosion of the basicranial skull in 1 lesion, and punctiform calcification of the capsule in 1 lesion. T 1 WI showed most lesions with isointense or slight hyperintense signals including homogeneous in 4 lesions and heterogeneous in 6 lesions. T 2 WI demonstrated isointense or slight hyperintense in 2 lesions, mixed hypointense and hyperintense signals in 4, cystic portion in 2, and two distinct portion of hyperintense and hypointense signal, so called 'yin-yang' pattern, in 2. Strong enhanced was found in all lesions, especially in 8 lesion with heterogeneous with the low T 2 signal. 'Dural tail' was found in 4 lesions. Conclusions: ISFI has some specific CT and MR features including heterogeneous signal intensity on T 2 WI, strong enhancement of areas with low T 2 signal intensity, slight or no 'dural tail', without skull thickening, and the typical 'yin-yang' pattern. (authors)

  3. Magnetic Resonance Imaging Features of Neuromyelitis Optica

    You, Sun Kyung; Song, Chang June; Park, Woon Ju; Lee, In Ho; Son, Eun Hee [Chungnam National University College of Medicine, Chungnam National University Hospital, Daejeon (Korea, Republic of)

    2013-03-15

    To report the magnetic resonance (MR) imaging features of the spinal cord and brain in patients of neuromyelitis optica (NMO). Between January 2001 and March 2010, the MR images (spinal cord, brain, and orbit) and the clinical and serologic findings of 11 NMO patients were retrospectively reviewed. The contrast-enhancement of the spinal cord was performed (20/23). The presence and pattern of the contrast-enhancement in the spinal cord were classified into 5 types. Acute myelitis was monophasic in 8 patients (8/11, 72.7%); and optic neuritis preceded acute myelitis in most patients. Longitudinally extensive cord lesion (average, 7.3 vertebral segments) was involved. The most common type was the diffuse and subtle enhancement of the spinal cord with a multifocal nodular, linear or segmental intense enhancement (45%). Most of the brain lesions (5/11, 10 lesions) were located in the brain stem, thalamus and callososeptal interphase. Anti-Ro autoantibody was positive in 2 patients, and they showed a high relapse rate of acute myelitis. Anti-NMO IgG was positive in 4 patients (4/7, 66.7%). The imaging findings of acute myelitis in NMO may helpful in making an early diagnosis of NMO which can result in a severe damage to the spinal cord, and to make a differential diagnosis of multiple sclerosis and inflammatory diseases of the spinal cord such as toxocariasis.

  4. Magnetic Resonance Imaging Features of Neuromyelitis Optica

    You, Sun Kyung; Song, Chang June; Park, Woon Ju; Lee, In Ho; Son, Eun Hee

    2013-01-01

    To report the magnetic resonance (MR) imaging features of the spinal cord and brain in patients of neuromyelitis optica (NMO). Between January 2001 and March 2010, the MR images (spinal cord, brain, and orbit) and the clinical and serologic findings of 11 NMO patients were retrospectively reviewed. The contrast-enhancement of the spinal cord was performed (20/23). The presence and pattern of the contrast-enhancement in the spinal cord were classified into 5 types. Acute myelitis was monophasic in 8 patients (8/11, 72.7%); and optic neuritis preceded acute myelitis in most patients. Longitudinally extensive cord lesion (average, 7.3 vertebral segments) was involved. The most common type was the diffuse and subtle enhancement of the spinal cord with a multifocal nodular, linear or segmental intense enhancement (45%). Most of the brain lesions (5/11, 10 lesions) were located in the brain stem, thalamus and callososeptal interphase. Anti-Ro autoantibody was positive in 2 patients, and they showed a high relapse rate of acute myelitis. Anti-NMO IgG was positive in 4 patients (4/7, 66.7%). The imaging findings of acute myelitis in NMO may helpful in making an early diagnosis of NMO which can result in a severe damage to the spinal cord, and to make a differential diagnosis of multiple sclerosis and inflammatory diseases of the spinal cord such as toxocariasis.

  5. Unsupervised feature learning for autonomous rock image classification

    Shu, Lei; McIsaac, Kenneth; Osinski, Gordon R.; Francis, Raymond

    2017-09-01

    Autonomous rock image classification can enhance the capability of robots for geological detection and enlarge the scientific returns, both in investigation on Earth and planetary surface exploration on Mars. Since rock textural images are usually inhomogeneous and manually hand-crafting features is not always reliable, we propose an unsupervised feature learning method to autonomously learn the feature representation for rock images. In our tests, rock image classification using the learned features shows that the learned features can outperform manually selected features. Self-taught learning is also proposed to learn the feature representation from a large database of unlabelled rock images of mixed class. The learned features can then be used repeatedly for classification of any subclass. This takes advantage of the large dataset of unlabelled rock images and learns a general feature representation for many kinds of rocks. We show experimental results supporting the feasibility of self-taught learning on rock images.

  6. Unusual imaging characteristics of complicated hydatid disease

    Turgut, Ahmet Tuncay [Department of Radiology, Ankara Training and Research Hospital, Ankara (Turkey)]. E-mail: ahmettuncayturgut@yahoo.com; Altin, Levent [Department of Radiology, Numune Training and Research Hospital, Ankara (Turkey); Topcu, Salih [Department of Thoracic Surgery, Faculty of Medicine, Kocaeli University, Izmit (Turkey); Kilicoglu, Buelent [Department of 4th General Surgery, Ankara Training and Research Hospital, Ankara (Turkey); Altinok, Tamer [Department of Thoracic Surgery, Meram Faculty of Medicine, Selcuk University, Konya (Turkey); Kaptanoglu, Erkan [Department of Neurosurgery, Numune Training and Research Hospital, Ankara (Turkey); Karademir, Alp [Department of Radiology, Numune Training and Research Hospital, Ankara (Turkey); Kosar, Ugur [Department of Radiology, Ankara Training and Research Hospital, Ankara (Turkey)

    2007-07-15

    Hydatid disease, a worldwide zoonosis, is caused by the larval stage of the Echinococcus tapeworm. Although the liver and the lungs are the most frequently involved organs in the body, hydatid cysts of other organs are unusual. Radiologically, they usually demonstrate typical imaging findings, but unusual imaging characteristics of complicated cyst of hydatid disease, associated with high morbidity and mortality, are rarely described in the literature. The purpose of this study is to review the general features of hydatidosis and to discuss atypical imaging characteristics of the complicated hydatid disease in the human, with an emphasis on structure and rupture of the cystic lesion as well as ultrasonography (USG), computed tomography (CT), and magnetic resonance imaging (MRI) features of the disease. In our study, the available literature and images of the cases with complicated hydatidosis involving liver, lung, brain, spine and orbit were reviewed retrospectively. In hydatid disease, there are many potential local and systemic complications due to secondary involvement in almost any anatomic location in humans. Radiologically, in addition to the presence of atypical findings such as perifocal edema, non-homogenous contrast enhancement, multiplicity or septations and calcification, various unusual manifestations due to rupture or infection of the cyst have been observed in our cases with complicated hydatid disease. To prevent subsequent acute catastrophic results and the development of recurrences in various organs, it should be kept in mind that complicated hydatid cysts can cause unusual USG, CT, and MRI findings, in addition to typical ones, in endemic areas. Therefore, familiarity with atypical radiological appearances of complicated hydatid disease may be valuable in making a correct diagnosis and treatment.

  7. Unusual imaging characteristics of complicated hydatid disease

    Turgut, Ahmet Tuncay; Altin, Levent; Topcu, Salih; Kilicoglu, Buelent; Altinok, Tamer; Kaptanoglu, Erkan; Karademir, Alp; Kosar, Ugur

    2007-01-01

    Hydatid disease, a worldwide zoonosis, is caused by the larval stage of the Echinococcus tapeworm. Although the liver and the lungs are the most frequently involved organs in the body, hydatid cysts of other organs are unusual. Radiologically, they usually demonstrate typical imaging findings, but unusual imaging characteristics of complicated cyst of hydatid disease, associated with high morbidity and mortality, are rarely described in the literature. The purpose of this study is to review the general features of hydatidosis and to discuss atypical imaging characteristics of the complicated hydatid disease in the human, with an emphasis on structure and rupture of the cystic lesion as well as ultrasonography (USG), computed tomography (CT), and magnetic resonance imaging (MRI) features of the disease. In our study, the available literature and images of the cases with complicated hydatidosis involving liver, lung, brain, spine and orbit were reviewed retrospectively. In hydatid disease, there are many potential local and systemic complications due to secondary involvement in almost any anatomic location in humans. Radiologically, in addition to the presence of atypical findings such as perifocal edema, non-homogenous contrast enhancement, multiplicity or septations and calcification, various unusual manifestations due to rupture or infection of the cyst have been observed in our cases with complicated hydatid disease. To prevent subsequent acute catastrophic results and the development of recurrences in various organs, it should be kept in mind that complicated hydatid cysts can cause unusual USG, CT, and MRI findings, in addition to typical ones, in endemic areas. Therefore, familiarity with atypical radiological appearances of complicated hydatid disease may be valuable in making a correct diagnosis and treatment

  8. Featured Image: Bright Dots in a Sunspot

    Kohler, Susanna

    2018-03-01

    This image of a sunspot, located in in NOAA AR 12227, was captured in December 2014 by the 0.5-meter Solar Optical Telescope on board the Hinode spacecraft. This image was processed by a team of scientists led by Rahul Yadav (Udaipur Solar Observatory, Physical Research Laboratory Dewali, India) in order to examine the properties of umbral dots: transient, bright features observed in the umbral region (the central, darkest part) of a sunspot. By exploring these dots, Yadav and collaborators learned how their properties relate to the large-scale properties of the sunspots in which they form for instance, how do the number, intensities, or filling factors of dots relate to the size of a sunspots umbra? To find out more about the authors results, check out the article below.Sunspot in NOAA AR 11921. Left: umbralpenumbral boundary. Center: the isolated umbra from the sunspot. Right: The umbra with locations of umbral dots indicated by yellow plus signs. [Adapted from Yadav et al. 2018]CitationRahul Yadav et al 2018 ApJ 855 8. doi:10.3847/1538-4357/aaaeba

  9. MR imaging features of spindle cell lipoma

    Kirwadi, Anand; Abdul-Halim, Rehan; Highland, Adrian; Kotnis, Nikhil [Sheffield Teaching Hospitals NHS Trust, Radiology Department, Sheffield (United Kingdom); Fernando, Malee [Sheffield Teaching Hospitals NHS Trust, Histopathology Department, Sheffield (United Kingdom)

    2014-02-15

    To assess the MR imaging features of spindle cell lipomas (SCL) and to compare these appearances directly with the histopathological findings. A retrospective review of our soft tissue tumor database was performed. This yielded 1,327 histologically proven lipomas, of which 25 were confirmed as being SCLs. Fourteen of the 25 patients had MR examinations available for review and only these patients were included in our study. Lesions were assessed at MR examination for the degree of internal fat signal content with grade 0 representing 0 % fat signal and grade 4 100 % fat signal. The degree of fat suppression and contrast-enhancement pattern were also recorded. The excision specimens were independently reviewed by a consultant histopathologist. The histology specimens were assessed for the amount of internal fat and non-adipose tissue and graded using the same scale applied for the imaging. Where core needle biopsy (CNB) was performed, the CNB specimens were also examined for positive features of SCL. In our study, 93 % (13/14) of our patients were male and the average age was 58 years. 65 % (9/14) of the lesions presented in the upper back, shoulder, or neck. All lesions were subcutaneous. 35 % (5/14) of the SCLs demonstrated grade 3 (>75 %) or grade 4 (100 %) fat signal on MR examination. 35 % (5/14) of the lesions had grade 2 (25-75 %) fat signal and 29 % (4/14) of the lesions demonstrated grade 0 (0 %) or grade 1 (<25 %) fat signal. 43 % (6/14) of lesions demonstrated homogenous fat suppression, 28 % (4/14) showed focal areas of high internal signal, and 28 % (4/14) had diffuse internal high signal on fluid-sensitive fat-saturated sequences. 86 % (6/7) of the cases demonstrated septal/nodular enhancement. The diagnosis was evident on the CNB specimen in 100 % (9/9) cases. The histopathology fat content grade was in agreement with the imaging grade in 86 % (12/14) cases. The internal signal pattern of SCL can range broadly, with low fat content lesions seen almost

  10. Heterotopic Pancreas: Histopathologic Features, Imaging Findings, and Complications.

    Rezvani, Maryam; Menias, Christine; Sandrasegaran, Kumaresan; Olpin, Jeffrey D; Elsayes, Khaled M; Shaaban, Akram M

    2017-01-01

    Heterotopic pancreas is a congenital anomaly in which pancreatic tissue is anatomically separate from the main gland. The most common locations of this displacement include the upper gastrointestinal tract-specifically, the stomach, duodenum, and proximal jejunum. Less common sites are the esophagus, ileum, Meckel diverticulum, biliary tree, mesentery, and spleen. Uncomplicated heterotopic pancreas is typically asymptomatic, with the lesion being discovered incidentally during an unrelated surgery, during an imaging examination, or at autopsy. The most common computed tomographic appearance of heterotopic pancreas is that of a small oval intramural mass with microlobulated margins and an endoluminal growth pattern. The attenuation and enhancement characteristics of these lesions parallel their histologic composition. Acinus-dominant lesions demonstrate avid homogeneous enhancement after intravenous contrast material administration, whereas duct-dominant lesions are hypovascular and heterogeneous. At magnetic resonance imaging, the heterotopic pancreas is isointense to the orthotopic pancreas, with characteristic T1 hyperintensity and early avid enhancement after intravenous gadolinium-based contrast material administration. Heterotopic pancreatic tissue has a rudimentary ductal system in which an orifice is sometimes visible at imaging as a central umbilication of the lesion. Complications of heterotopic pancreas include pancreatitis, pseudocyst formation, malignant degeneration, gastrointestinal bleeding, bowel obstruction, and intussusception. Certain complications may be erroneously diagnosed as malignancy. Paraduodenal pancreatitis is thought to be due to cystic degeneration of heterotopic pancreatic tissue in the medial wall of the duodenum. Recognizing the characteristic imaging features of heterotopic pancreas aids in differentiating it from cancer and thus in avoiding unnecessary surgery. © RSNA, 2017.

  11. Magnetic mirror fusion systems: Characteristics and distinctive features

    Post, R.F.

    1987-01-01

    A tutorial account is given of the main characteristics and distinctive features of conceptual magnetic fusion systems employing the magnetic mirror principle. These features are related to the potential advantages that mirror-based fusion systems may exhibit for the generation of economic fusion power

  12. Characteristic features of the exotic superconductors: A summary

    Brandow, B.

    1997-09-01

    The authors summarize the results of a comprehensive examination of the characteristic features of the exotic superconductors, the superconductors so-labelled by Uemura and co-workers. In both the electronic and the crystal-chemistry properties, they find anomalous features which appear to be universal for these materials, as well as other features which are clearly not universal but common enough to be considered typical for these materials. Some implications of these anomalies are discussed

  13. Color and neighbor edge directional difference feature for image retrieval

    Chaobing Huang; Shengsheng Yu; Jingli Zhou; Hongwei Lu

    2005-01-01

    @@ A novel image feature termed neighbor edge directional difference unit histogram is proposed, in which the neighbor edge directional difference unit is defined and computed for every pixel in the image, and is used to generate the neighbor edge directional difference unit histogram. This histogram and color histogram are used as feature indexes to retrieve color image. The feature is invariant to image scaling and translation and has more powerful descriptive for the natural color images. Experimental results show that the feature can achieve better retrieval performance than other color-spatial features.

  14. FEATURE EVALUATION FOR BUILDING FACADE IMAGES – AN EMPIRICAL STUDY

    M. Y. Yang

    2012-08-01

    Full Text Available The classification of building facade images is a challenging problem that receives a great deal of attention in the photogrammetry community. Image classification is critically dependent on the features. In this paper, we perform an empirical feature evaluation task for building facade images. Feature sets we choose are basic features, color features, histogram features, Peucker features, texture features, and SIFT features. We present an approach for region-wise labeling using an efficient randomized decision forest classifier and local features. We conduct our experiments with building facade image classification on the eTRIMS dataset, where our focus is the object classes building, car, door, pavement, road, sky, vegetation, and window.

  15. Focal hepatic lesions with peripheral eosinophilia: imaging features of various disease

    Seo, Joon Beom; Han, Joon Koo; Kim, Tae Kyoung; Choi, Byung Ihn; Han, Man Chung [Seoul National Univ. College of Medicine, Seoul (Korea, Republic of); Song, Chi Sung [Seoul City Boramae Hospital, Seoul (Korea, Republic of)

    1999-01-01

    Due to the recent advent of various imaging modalities such as ultrasonography, computed tomography and magnetic resonance imaging, as well as knowledge of the characteristic imaging features of hepatic lesions, radiologic examination plays a major role in the differential diagnosis of focal hepatic lesions. However, various 'nonspecific' or 'unusual' imaging features of focal hepatic lesions are occasionally encountered, and this makes correct diagnosis difficult. In such a situation, the presence of peripheral eosinophilia helps narrow the differential diagnoses. The aim of this pictorial essay is to describe the imaging features of various disease entities which cause focal hepatic lesions and peripheral eosinophilia.

  16. Image Quality Characteristics of Handheld Display Devices for Medical Imaging

    Yamazaki, Asumi; Liu, Peter; Cheng, Wei-Chung; Badano, Aldo

    2013-01-01

    Handheld devices such as mobile phones and tablet computers have become widespread with thousands of available software applications. Recently, handhelds are being proposed as part of medical imaging solutions, especially in emergency medicine, where immediate consultation is required. However, handheld devices differ significantly from medical workstation displays in terms of display characteristics. Moreover, the characteristics vary significantly among device types. We investigate the image quality characteristics of various handheld devices with respect to luminance response, spatial resolution, spatial noise, and reflectance. We show that the luminance characteristics of the handheld displays are different from those of workstation displays complying with grayscale standard target response suggesting that luminance calibration might be needed. Our results also demonstrate that the spatial characteristics of handhelds can surpass those of medical workstation displays particularly for recent generation devices. While a 5 mega-pixel monochrome workstation display has horizontal and vertical modulation transfer factors of 0.52 and 0.47 at the Nyquist frequency, the handheld displays released after 2011 can have values higher than 0.63 at the respective Nyquist frequencies. The noise power spectra for workstation displays are higher than 1.2×10−5 mm2 at 1 mm−1, while handheld displays have values lower than 3.7×10−6 mm2. Reflectance measurements on some of the handheld displays are consistent with measurements for workstation displays with, in some cases, low specular and diffuse reflectance coefficients. The variability of the characterization results among devices due to the different technological features indicates that image quality varies greatly among handheld display devices. PMID:24236113

  17. An Effective Combined Feature For Web Based Image Retrieval

    H.M.R.B Herath

    2015-08-01

    Full Text Available Abstract Technology advances as well as the emergence of large scale multimedia applications and the revolution of the World Wide Web has changed the world into a digital age. Anybody can use their mobile phone to take a photo at any time anywhere and upload that image to ever growing image databases. Development of effective techniques for visual and multimedia retrieval systems is one of the most challenging and important directions of the future research. This paper proposes an effective combined feature for web based image retrieval. Frequently used colour and texture features are explored in order to develop a combined feature for this purpose. Widely used three colour features Colour moments Colour coherence vector and Colour Correlogram and three texture features Grey Level Co-occurrence matrix Tamura features and Gabor filter were analyzed for their performance. Precision and Recall were used to evaluate the performance of each of these techniques. By comparing precision and recall values the methods that performed best were taken and combined to form a hybrid feature. The developed combined feature was evaluated by developing a web based CBIR system. A web crawler was used to first crawl through Web sites and images found in those sites are downloaded and the combined feature representation technique was used to extract image features. The test results indicated that this web system can be used to index web images with the combined feature representation schema and to find similar images. Random image retrievals using the web system shows that the combined feature can be used to retrieve images belonging to the general image domain. Accuracy of the retrieval can be noted high for natural images like outdoor scenes images of flowers etc. Also images which have a similar colour and texture distribution were retrieved as similar even though the images were belonging to deferent semantic categories. This can be ideal for an artist who wants

  18. Image feature detectors and descriptors foundations and applications

    Hassaballah, Mahmoud

    2016-01-01

    This book provides readers with a selection of high-quality chapters that cover both theoretical concepts and practical applications of image feature detectors and descriptors. It serves as reference for researchers and practitioners by featuring survey chapters and research contributions on image feature detectors and descriptors. Additionally, it emphasizes several keywords in both theoretical and practical aspects of image feature extraction. The keywords include acceleration of feature detection and extraction, hardware implantations, image segmentation, evolutionary algorithm, ordinal measures, as well as visual speech recognition. .

  19. CT imaging features of anaplastic thyroid carcinoma

    Shi Zhenshan; You Ruixiong; Cao Dairong; Li Yueming; Zhuang Qian

    2013-01-01

    Objective: To investigate the CT characteristics of anaplastic thyroid carcinoma and evaluate the diagnostic value of CT in this disease. Methods: The CT findings of 10 patients with pathologically proved anaplastic thyroid carcinoma were retrospectively reviewed. The patients included 7 females and 3 males. Their age ranged from 25.0 to 78 years with median of 61 years. Multi-slices plain and post contrast CT scans were performed in all patients. Results: Unilateral thyroid was involved in 6 patients. Unilateral thyroid and thyroid isthmus were both involved in 2 patients due to big size. Bilateral thyroid were involved in 2 patients. The maximum diameter of anaplastic thyroid carcinoma ranged from 2.9-12.8 cm with mean of (4.5 ± 1.4) cm. All lesions demonstrated unclear margins and envelope invasion. The densities of all lesions were heterogeneous and obvious necrosis areas were noted on precontrast images. Seven lesions showed varied calcifications, and coarse granular calcifications were found in 5 lesions among them. All lesions showed remarkable heterogenous enhancement on post-contrast CT. The CT value of solid portion of the tumor increased 40 HU after contrast media administration. The ratios of CT value which comparing of the tumor with contralateral sternocleidomastoid muscle were 0.69-0.82 (0.76 ± 0.18) and 1.25-1.41 (1.33 ± 0.28) on pre and post CT, respectively. Enlarged cervical lymph nodes were found in 6 cases (60.0%). It showed obvious homogeneous enhancement or irregular ring-like enhancement on post-contrast images and dot calcifications were seen in 1 case. Conclusions: Relative larger single thyroid masses with coarse granular calcifications, necrosis,envelope invasion, remarkable heterogeneous enhancing and enlarged lymph nodes on CT are suggestive of anaplastic thyroid carcinoma. (authors)

  20. Some Numerical Characteristics of Image Texture

    O. Samarina

    2012-05-01

    Full Text Available Texture classification is one of the basic images processing tasks. In this paper we present some numerical characteristics to the images analysis and processing. It can be used at the solving of images classification problems, their recognition, problems of remote sounding, biomedical images analysis, geological researches.

  1. The imaging features of neurologic complications of left atrial myxomas

    Liao, Wei-Hua; Ramkalawan, Divya; Liu, Jian-Ling; Shi, Wei; Zee, Chi-Shing; Yang, Xiao-Su; Li, Guo-Liang; Li, Jing; Wang, Xiao-Yi

    2015-01-01

    Background: Neurologic complications may be the first symptoms of atrial myxomas. Understanding the imaging features of neurologic complications of atrial myxomas can be helpful for the prompt diagnosis. Objective: To identify neuroimaging features for patients with neurologic complications attributed to atrial myxoma. Methods: We retrospectively reviewed the medical records of 103 patients with pathologically confirmed atrial myxoma at Xiangya Hospital from January 2009 to January 2014. The neuroimaging data for patients with neurologic complications were analyzed. Results: Eight patients with atrial myxomas (7.77%) presented with neurologic manifestations, which constituted the initial symptoms for seven patients (87.5%). Neuroimaging showed five cases of cerebral infarctions and three cases of aneurysms. The main patterns of the infarctions were multiplicity (100.0%) and involvement of the middle cerebral artery territory (80.0%). The aneurysms were fusiform in shape, multiple in number (100.0%) and located in the distal middle cerebral artery (100.0%). More specifically, high-density in the vicinity of the aneurysms was observed on CT for two patients (66.7%), and homogenous enhancement surrounding the aneurysms was detected in the enhanced imaging for two patients (66.7%). Conclusion: Neurologic complications secondary to atrial myxoma consist of cerebral infarctions and aneurysms, which show certain characteristic features in neuroimaging. Echocardiography should be performed in patients with multiple cerebral infarctions, and multiple aneurysms, especially when aneurysms are distal in location. More importantly, greater attention should be paid to the imaging changes surrounding the aneurysms when myxomatous aneurysms are suspected and these are going to be the relevant features in our article

  2. The imaging features of neurologic complications of left atrial myxomas

    Liao, Wei-Hua; Ramkalawan, Divya; Liu, Jian-Ling; Shi, Wei [Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, Hunan (China); Zee, Chi-Shing [Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033 (United States); Yang, Xiao-Su; Li, Guo-Liang; Li, Jing [Department of Neurology, Xiangya Hospital, Central South University, Changsha 410008, Hunan (China); Wang, Xiao-Yi, E-mail: cjr.wangxiaoyi@vip.163.com [Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, Hunan (China)

    2015-05-15

    Background: Neurologic complications may be the first symptoms of atrial myxomas. Understanding the imaging features of neurologic complications of atrial myxomas can be helpful for the prompt diagnosis. Objective: To identify neuroimaging features for patients with neurologic complications attributed to atrial myxoma. Methods: We retrospectively reviewed the medical records of 103 patients with pathologically confirmed atrial myxoma at Xiangya Hospital from January 2009 to January 2014. The neuroimaging data for patients with neurologic complications were analyzed. Results: Eight patients with atrial myxomas (7.77%) presented with neurologic manifestations, which constituted the initial symptoms for seven patients (87.5%). Neuroimaging showed five cases of cerebral infarctions and three cases of aneurysms. The main patterns of the infarctions were multiplicity (100.0%) and involvement of the middle cerebral artery territory (80.0%). The aneurysms were fusiform in shape, multiple in number (100.0%) and located in the distal middle cerebral artery (100.0%). More specifically, high-density in the vicinity of the aneurysms was observed on CT for two patients (66.7%), and homogenous enhancement surrounding the aneurysms was detected in the enhanced imaging for two patients (66.7%). Conclusion: Neurologic complications secondary to atrial myxoma consist of cerebral infarctions and aneurysms, which show certain characteristic features in neuroimaging. Echocardiography should be performed in patients with multiple cerebral infarctions, and multiple aneurysms, especially when aneurysms are distal in location. More importantly, greater attention should be paid to the imaging changes surrounding the aneurysms when myxomatous aneurysms are suspected and these are going to be the relevant features in our article.

  3. Classification of Carotid Plaque Echogenicity by Combining Texture Features and Morphologic Characteristics.

    Huang, Xiaowei; Zhang, Yanling; Qian, Ming; Meng, Long; Xiao, Yang; Niu, Lili; Zheng, Rongqin; Zheng, Hairong

    2016-10-01

    Anechoic carotid plaques on sonography have been used to predict future cardiovascular or cerebrovascular events. The purpose of this study was to investigate whether carotid plaque echogenicity could be assessed objectively by combining texture features extracted by MaZda software (Institute of Electronics, Technical University of Lodz, Lodz, Poland) and morphologic characteristics, which may provide a promising method for early prediction of acute cardiovascular disease. A total of 268 plaque images were collected from 136 volunteers and classified into 85 hyperechoic, 83 intermediate, and 100 anechoic plaques. About 300 texture features were extracted from histogram, absolute gradient, run-length matrix, gray-level co-occurrence matrix, autoregressive model, and wavelet transform algorithms by MaZda. The morphologic characteristics, including degree of stenosis, maximum plaque intima-media thickness, and maximum plaque length, were measured by B-mode sonography. Statistically significant features were selected by analysis of covariance. The most discriminative features were obtained from statistically significant features by linear discriminant analysis. The K-nearest neighbor classifier was used to classify plaque echogenicity based on statistically significant and most discriminative features. A total of 30 statistically significant features were selected among the plaques, and 2 most discriminative features were obtained from the statistically significant features. The classification accuracy rates for 3 types of plaques based on statistically significant and most discriminative features were 72.03% (κ= 0.571; P MaZda and morphologic characteristics.

  4. Featured Image: Revealing Hidden Objects with Color

    Kohler, Susanna

    2018-02-01

    Stunning color astronomical images can often be the motivation for astronomers to continue slogging through countless data files, calculations, and simulations as we seek to understand the mysteries of the universe. But sometimes the stunning images can, themselves, be the source of scientific discovery. This is the case with the below image of Lynds Dark Nebula 673, located in the Aquila constellation, that was captured with the Mayall 4-meter telescope at Kitt Peak National Observatory by a team of scientists led by Travis Rector (University of Alaska Anchorage). After creating the image with a novel color-composite imaging method that reveals faint H emission (visible in red in both images here), Rector and collaborators identified the presence of a dozen new Herbig-Haro objects small cloud patches that are caused when material is energetically flung out from newly born stars. The image adapted above shows three of the new objects, HH 118789, aligned with two previously known objects, HH 32 and 332 suggesting they are driven by the same source. For more beautiful images and insight into the authors discoveries, check out the article linked below!Full view of Lynds Dark Nebula 673. Click for the larger view this beautiful composite image deserves! [T.A. Rector (University of Alaska Anchorage) and H. Schweiker (WIYN and NOAO/AURA/NSF)]CitationT. A. Rector et al 2018 ApJ 852 13. doi:10.3847/1538-4357/aa9ce1

  5. Wavelength calibration of imaging spectrometer using atmospheric absorption features

    Zhou, Jiankang; Chen, Yuheng; Chen, Xinhua; Ji, Yiqun; Shen, Weimin

    2012-11-01

    Imaging spectrometer is a promising remote sensing instrument widely used in many filed, such as hazard forecasting, environmental monitoring and so on. The reliability of the spectral data is the determination to the scientific communities. The wavelength position at the focal plane of the imaging spectrometer will change as the pressure and temperature vary, or the mechanical vibration. It is difficult for the onboard calibration instrument itself to keep the spectrum reference accuracy and it also occupies weight and the volume of the remote sensing platform. Because the spectral images suffer from the atmospheric effects, the carbon oxide, water vapor, oxygen and solar Fraunhofer line, the onboard wavelength calibration can be processed by the spectral images themselves. In this paper, wavelength calibration is based on the modeled and measured atmospheric absorption spectra. The modeled spectra constructed by the atmospheric radiative transfer code. The spectral angle is used to determine the best spectral similarity between the modeled spectra and measured spectra and estimates the wavelength position. The smile shape can be obtained when the matching process across all columns of the data. The present method is successful applied on the Hyperion data. The value of the wavelength shift is obtained by shape matching of oxygen absorption feature and the characteristics are comparable to that of the prelaunch measurements.

  6. Comparisons of feature extraction algorithm based on unmanned aerial vehicle image

    Xi Wenfei

    2017-07-01

    Full Text Available Feature point extraction technology has become a research hotspot in the photogrammetry and computer vision. The commonly used point feature extraction operators are SIFT operator, Forstner operator, Harris operator and Moravec operator, etc. With the high spatial resolution characteristics, UAV image is different from the traditional aviation image. Based on these characteristics of the unmanned aerial vehicle (UAV, this paper uses several operators referred above to extract feature points from the building images, grassland images, shrubbery images, and vegetable greenhouses images. Through the practical case analysis, the performance, advantages, disadvantages and adaptability of each algorithm are compared and analyzed by considering their speed and accuracy. Finally, the suggestions of how to adapt different algorithms in diverse environment are proposed.

  7. Texture Feature Analysis for Different Resolution Level of Kidney Ultrasound Images

    Kairuddin, Wan Nur Hafsha Wan; Mahmud, Wan Mahani Hafizah Wan

    2017-08-01

    Image feature extraction is a technique to identify the characteristic of the image. The objective of this work is to discover the texture features that best describe a tissue characteristic of a healthy kidney from ultrasound (US) image. Three ultrasound machines that have different specifications are used in order to get a different quality (different resolution) of the image. Initially, the acquired images are pre-processed to de-noise the speckle to ensure the image preserve the pixels in a region of interest (ROI) for further extraction. Gaussian Low- pass Filter is chosen as the filtering method in this work. 150 of enhanced images then are segmented by creating a foreground and background of image where the mask is created to eliminate some unwanted intensity values. Statistical based texture features method is used namely Intensity Histogram (IH), Gray-Level Co-Occurance Matrix (GLCM) and Gray-level run-length matrix (GLRLM).This method is depends on the spatial distribution of intensity values or gray levels in the kidney region. By using One-Way ANOVA in SPSS, the result indicated that three features (Contrast, Difference Variance and Inverse Difference Moment Normalized) from GLCM are not statistically significant; this concludes that these three features describe a healthy kidney characteristics regardless of the ultrasound image quality.

  8. Superpixel-Based Feature for Aerial Image Scene Recognition

    Hongguang Li

    2018-01-01

    Full Text Available Image scene recognition is a core technology for many aerial remote sensing applications. Different landforms are inputted as different scenes in aerial imaging, and all landform information is regarded as valuable for aerial image scene recognition. However, the conventional features of the Bag-of-Words model are designed using local points or other related information and thus are unable to fully describe landform areas. This limitation cannot be ignored when the aim is to ensure accurate aerial scene recognition. A novel superpixel-based feature is proposed in this study to characterize aerial image scenes. Then, based on the proposed feature, a scene recognition method of the Bag-of-Words model for aerial imaging is designed. The proposed superpixel-based feature that utilizes landform information establishes top-task superpixel extraction of landforms to bottom-task expression of feature vectors. This characterization technique comprises the following steps: simple linear iterative clustering based superpixel segmentation, adaptive filter bank construction, Lie group-based feature quantification, and visual saliency model-based feature weighting. Experiments of image scene recognition are carried out using real image data captured by an unmanned aerial vehicle (UAV. The recognition accuracy of the proposed superpixel-based feature is 95.1%, which is higher than those of scene recognition algorithms based on other local features.

  9. Measurements of image characteristics of DSA installations

    Busch, H.P.; Strauss, L.G.; Freimarck, R.D.

    1984-01-01

    Measurements for quantifying the image characteristics were carried out on three DSA installations (DVI 1 - Philips, Angiotron - Siemens and DF 3000 - General Eletric). Contrast resolution was measured with a vessel phantom (General Electric) and spatial resolution with a lead grid. A further parameter was the dose entering the image intensifier. The Angiotron was used with an intensifier with 53 cm. diameter and the DF 3000 with temporal subtraction of the video images and the subtraction of dual energy images (hybrid technique). These measurements can be carried out quickly and easily and are a step towards standardisation of measurements of image characteristics of DSA installations. (orig.) [de

  10. Iris recognition based on key image feature extraction.

    Ren, X; Tian, Q; Zhang, J; Wu, S; Zeng, Y

    2008-01-01

    In iris recognition, feature extraction can be influenced by factors such as illumination and contrast, and thus the features extracted may be unreliable, which can cause a high rate of false results in iris pattern recognition. In order to obtain stable features, an algorithm was proposed in this paper to extract key features of a pattern from multiple images. The proposed algorithm built an iris feature template by extracting key features and performed iris identity enrolment. Simulation results showed that the selected key features have high recognition accuracy on the CASIA Iris Set, where both contrast and illumination variance exist.

  11. Imaging features of ovarian metastases from colonic adenocarcinoma in adolescents

    Kauffman, W.M.; Jenkins, J.J. III; Helton, K.; Rao, B.N.; Winer-Muram, H.T.; Pratt, C.B.

    1995-01-01

    This paper describes the imaging features of ovarian metastases from adenocarcinoma of the colon in adolescent females. We reviewed retrospectively abdominal and pelvic computed tomographic and pelvic ultrasound examinations, histologic slices, and clinical charts of six adolescent females with ovarian metastases secondary to adenocarcinoma of the colon. One patient had ovarian metastasis at presentation and was presumed to have a primary ovarian tumor. The ovarian metastases were either solid (n = 3), complex with both solid and cystic components (n = 2), or multilocular cysts (n = 1). The ovarian lesions were large, ranging from 6 cm to 18 cm in diameter. Colorectal carcinoma in adolescent females is frequently associated with ovarian metastases. One imaging characteristic differs in adult and adolescent ovarian metastases, although they do have features in common: in adolescents, a smaller proportion of colorectal ovarian metastases are multicystic (17%) compared with the adult series (45%). These lesions are frequently large and may be complex, multicystic, or solid. Although it is a rare disease, the differential dignosis of adnexal masses in adolescent females should include ovarian metastases from adenocarcinoma of the colon. (orig.)

  12. Clinical feature and imaging findings of juvenile ankylosing spondylitis

    Zeng Hui; Liang Hongchang; Wang Weigang; Liu Hui; Huang Meiping; Zheng Junhui

    2003-01-01

    Objective: To analyze the clinical features and imaging findings of juvenile ankylosing spondylitis (JAS) in order to improve the diagnosis and the prognosis of JAS. Methods: Twelve cases were analyzed retrospectively and 14 cases, who were followed-up averagely for 2.3 years, were analyzed prospectively. Initially 10 were diagnosed as Still's disease and four were diagnosed as rheumatoid arthritis. Photography was performed in all cases, CT scan was done in 18 cases, and MRI in 8 cases. Lower extremity big joint disorders were observed in all cases and the small joints were reserved. The abnormalities of the sacroiliac joint were revealed in the early stage in 12 cases. The results were analyzed statistically. Results: The age of preliminary diagnosis was 9.3 years in average. There were statistical correlation between the age of the first episode and severity of the disease. And there were statistical correlation between the course of the illness and severity of the disease. The large joints of the lower extremities were most commonly involved. Conclusion: There were characteristic clinical features and imaging findings in the JAS. Early diagnosis and treatment improve the prognosis

  13. Multimodality imaging features of hereditary multiple exostoses

    Kok, H K; Fitzgerald, L; Campbell, N; Lyburn, I D; Munk, P L; Buckley, O; Torreggiani, W C

    2013-01-01

    Hereditary multiple exostoses (HME) or diaphyseal aclasis is an inherited disorder characterised by the formation of multiple osteochondromas, which are cartilage-capped osseous outgrowths, and the development of associated osseous deformities. Individuals with HME may be asymptomatic or develop clinical symptoms, which prompt imaging studies. Different modalities ranging from plain radiographs to cross-sectional and nuclear medicine imaging studies can be helpful in the diagnosis and detecti...

  14. Feature-based Alignment of Volumetric Multi-modal Images

    Toews, Matthew; Zöllei, Lilla; Wells, William M.

    2014-01-01

    This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

  15. Motor features in posterior cortical atrophy and their imaging correlates.

    Ryan, Natalie S; Shakespeare, Timothy J; Lehmann, Manja; Keihaninejad, Shiva; Nicholas, Jennifer M; Leung, Kelvin K; Fox, Nick C; Crutch, Sebastian J

    2014-12-01

    Posterior cortical atrophy (PCA) is a neurodegenerative syndrome characterized by impaired higher visual processing skills; however, motor features more commonly associated with corticobasal syndrome may also occur. We investigated the frequency and clinical characteristics of motor features in 44 PCA patients and, with 30 controls, conducted voxel-based morphometry, cortical thickness, and subcortical volumetric analyses of their magnetic resonance imaging. Prominent limb rigidity was used to define a PCA-motor subgroup. A total of 30% (13) had PCA-motor; all demonstrating asymmetrical left upper limb rigidity. Limb apraxia was more frequent and asymmetrical in PCA-motor, as was myoclonus. Tremor and alien limb phenomena only occurred in this subgroup. The subgroups did not differ in neuropsychological test performance or apolipoprotein E4 allele frequency. Greater asymmetry of atrophy occurred in PCA-motor, particularly involving right frontoparietal and peri-rolandic cortices, putamen, and thalamus. The 9 patients (including 4 PCA-motor) with pathology or cerebrospinal fluid all showed evidence of Alzheimer's disease. Our data suggest that PCA patients with motor features have greater atrophy of contralateral sensorimotor areas but are still likely to have underlying Alzheimer's disease. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  16. Motor features in posterior cortical atrophy and their imaging correlates☆

    Ryan, Natalie S.; Shakespeare, Timothy J.; Lehmann, Manja; Keihaninejad, Shiva; Nicholas, Jennifer M.; Leung, Kelvin K.; Fox, Nick C.; Crutch, Sebastian J.

    2014-01-01

    Posterior cortical atrophy (PCA) is a neurodegenerative syndrome characterized by impaired higher visual processing skills; however, motor features more commonly associated with corticobasal syndrome may also occur. We investigated the frequency and clinical characteristics of motor features in 44 PCA patients and, with 30 controls, conducted voxel-based morphometry, cortical thickness, and subcortical volumetric analyses of their magnetic resonance imaging. Prominent limb rigidity was used to define a PCA-motor subgroup. A total of 30% (13) had PCA-motor; all demonstrating asymmetrical left upper limb rigidity. Limb apraxia was more frequent and asymmetrical in PCA-motor, as was myoclonus. Tremor and alien limb phenomena only occurred in this subgroup. The subgroups did not differ in neuropsychological test performance or apolipoprotein E4 allele frequency. Greater asymmetry of atrophy occurred in PCA-motor, particularly involving right frontoparietal and peri-rolandic cortices, putamen, and thalamus. The 9 patients (including 4 PCA-motor) with pathology or cerebrospinal fluid all showed evidence of Alzheimer's disease. Our data suggest that PCA patients with motor features have greater atrophy of contralateral sensorimotor areas but are still likely to have underlying Alzheimer's disease. PMID:25086839

  17. Prototype Theory Based Feature Representation for PolSAR Images

    Huang Xiaojing; Yang Xiangli; Huang Pingping; Yang Wen

    2016-01-01

    This study presents a new feature representation approach for Polarimetric Synthetic Aperture Radar (PolSAR) image based on prototype theory. First, multiple prototype sets are generated using prototype theory. Then, regularized logistic regression is used to predict similarities between a test sample and each prototype set. Finally, the PolSAR image feature representation is obtained by ensemble projection. Experimental results of an unsupervised classification of PolSAR images show that our...

  18. Unexpected diagnosis of superficial neurofibroma in a lesion with imaging features of a vascular malformation

    O' Keefe, Patrick; Reid, Janet; Morrison, Stuart [Cleveland Clinic Foundation, Department of Radiology, Cleveland, OH (United States); Vidimos, Allison [Cleveland Clinic Foundation, Department of Dermatology, Cleveland, OH (United States); DiFiore, John [Cleveland Clinic Foundation, Department of Pediatric Surgery, Cleveland, OH (United States)

    2005-12-01

    Plexiform neurofibroma is a pathognomonic, often disabling feature of neurofibromatosis type I. Although the target-like appearance of deep plexiform neurofibroma on T2-weighted MRI has been well-described, a second superficial form of plexiform neurofibroma has differing imaging features. We report a 15-year-old boy who presented with multiple cutaneous lesions exhibiting clinical and imaging characteristics of a venolymphatic malformation. These lesions were histologically proved to represent superficial plexiform neurofibromas. We wish to emphasize the unique MR findings of superficial plexiform neurofibromas; these findings are different from the imaging characteristics of the deep form and can be confused with a low-flow vascular malformation. (orig.)

  19. Prenatal MR imaging features of isolated cerebellar haemorrhagic lesions

    Martino, Francesca; Malova, Mariya; Ramenghi, Luca A.; Cesaretti, Claudia; Parazzini, Cecilia; Doneda, Chiara; Righini, Andrea; Rossi, Andrea

    2016-01-01

    Prenatal features of isolated cerebellar haemorrhagic lesions have not been sufficiently characterised. We aimed to better define their MR imaging characteristics, documenting the location, extension, evolution stage and anatomic sequelae, and to better understand cerebellar haemorrhage pathophysiology. We screened our foetal MR imaging database (3200 cases) for reports of haemorrhagic lesions affecting only the cerebellum (without any supratentorial bleeding or other clastic lesions), defined as one of the following: T2-weighted hypointense or mixed hypo-/hyperintense signal; rim of T2-weighted hypointense signal covering the surface of volume-reduced parenchyma; T1-weighted hyperintense signal; increased DWI signal. Seventeen cases corresponded to the selection criteria. All lesions occurred before the 26th week of gestation, with prevalent origin from the peripheral-caudal portion of the hemispheres and equal frequency of unilateral/bilateral involvement. The caudal vermis appeared affected in 2/3 of cases, not in all cases confirmed postnatally. Lesions evolved towards malformed cerebellar foliation. The aetiology and pathophysiology were unknown, although in a subset of cases intra- and extracranial venous engorgement seemed to play a key role. Onset from the peripheral and caudal portion of the hemispheres seems characteristic of prenatal cerebellar haemorrhagic lesions. Elective involvement of the peripheral germinal matrix is hypothesised. (orig.)

  20. Multilevel binomial logistic prediction model for malignant pulmonary nodules based on texture features of CT image

    Wang Huan; Guo Xiuhua; Jia Zhongwei; Li Hongkai; Liang Zhigang; Li Kuncheng; He Qian

    2010-01-01

    Purpose: To introduce multilevel binomial logistic prediction model-based computer-aided diagnostic (CAD) method of small solitary pulmonary nodules (SPNs) diagnosis by combining patient and image characteristics by textural features of CT image. Materials and methods: Describe fourteen gray level co-occurrence matrix textural features obtained from 2171 benign and malignant small solitary pulmonary nodules, which belongs to 185 patients. Multilevel binomial logistic model is applied to gain these initial insights. Results: Five texture features, including Inertia, Entropy, Correlation, Difference-mean, Sum-Entropy, and age of patients own aggregating character on patient-level, which are statistically different (P < 0.05) between benign and malignant small solitary pulmonary nodules. Conclusion: Some gray level co-occurrence matrix textural features are efficiently descriptive features of CT image of small solitary pulmonary nodules, which can profit diagnosis of earlier period lung cancer if combined patient-level characteristics to some extent.

  1. Diffusion tensor image registration using hybrid connectivity and tensor features.

    Wang, Qian; Yap, Pew-Thian; Wu, Guorong; Shen, Dinggang

    2014-07-01

    Most existing diffusion tensor imaging (DTI) registration methods estimate structural correspondences based on voxelwise matching of tensors. The rich connectivity information that is given by DTI, however, is often neglected. In this article, we propose to integrate complementary information given by connectivity features and tensor features for improved registration accuracy. To utilize connectivity information, we place multiple anchors representing different brain anatomies in the image space, and define the connectivity features for each voxel as the geodesic distances from all anchors to the voxel under consideration. The geodesic distance, which is computed in relation to the tensor field, encapsulates information of brain connectivity. We also extract tensor features for every voxel to reflect the local statistics of tensors in its neighborhood. We then combine both connectivity features and tensor features for registration of tensor images. From the images, landmarks are selected automatically and their correspondences are determined based on their connectivity and tensor feature vectors. The deformation field that deforms one tensor image to the other is iteratively estimated and optimized according to the landmarks and their associated correspondences. Experimental results show that, by using connectivity features and tensor features simultaneously, registration accuracy is increased substantially compared with the cases using either type of features alone. Copyright © 2013 Wiley Periodicals, Inc.

  2. Adapting Local Features for Face Detection in Thermal Image

    Chao Ma

    2017-11-01

    Full Text Available A thermal camera captures the temperature distribution of a scene as a thermal image. In thermal images, facial appearances of different people under different lighting conditions are similar. This is because facial temperature distribution is generally constant and not affected by lighting condition. This similarity in face appearances is advantageous for face detection. To detect faces in thermal images, cascade classifiers with Haar-like features are generally used. However, there are few studies exploring the local features for face detection in thermal images. In this paper, we introduce two approaches relying on local features for face detection in thermal images. First, we create new feature types by extending Multi-Block LBP. We consider a margin around the reference and the generally constant distribution of facial temperature. In this way, we make the features more robust to image noise and more effective for face detection in thermal images. Second, we propose an AdaBoost-based training method to get cascade classifiers with multiple types of local features. These feature types have different advantages. In this way we enhance the description power of local features. We did a hold-out validation experiment and a field experiment. In the hold-out validation experiment, we captured a dataset from 20 participants, comprising 14 males and 6 females. For each participant, we captured 420 images with 10 variations in camera distance, 21 poses, and 2 appearances (participant with/without glasses. We compared the performance of cascade classifiers trained by different sets of the features. The experiment results showed that the proposed approaches effectively improve the performance of face detection in thermal images. In the field experiment, we compared the face detection performance in realistic scenes using thermal and RGB images, and gave discussion based on the results.

  3. Feature Importance for Human Epithelial (HEp-2 Cell Image Classification

    Vibha Gupta

    2018-02-01

    Full Text Available Indirect Immuno-Fluorescence (IIF microscopy imaging of human epithelial (HEp-2 cells is a popular method for diagnosing autoimmune diseases. Considering large data volumes, computer-aided diagnosis (CAD systems, based on image-based classification, can help in terms of time, effort, and reliability of diagnosis. Such approaches are based on extracting some representative features from the images. This work explores the selection of the most distinctive features for HEp-2 cell images using various feature selection (FS methods. Considering that there is no single universally optimal feature selection technique, we also propose hybridization of one class of FS methods (filter methods. Furthermore, the notion of variable importance for ranking features, provided by another type of approaches (embedded methods such as Random forest, Random uniform forest is exploited to select a good subset of features from a large set, such that addition of new features does not increase classification accuracy. In this work, we have also, with great consideration, designed class-specific features to capture morphological visual traits of the cell patterns. We perform various experiments and discussions to demonstrate the effectiveness of FS methods along with proposed and a standard feature set. We achieve state-of-the-art performance even with small number of features, obtained after the feature selection.

  4. Clinical and imaging features of neonatal chlamydial pneumonia

    Cao Yongli; Peng Yun; Sun Guoqiang

    2012-01-01

    Objective: To study the clinical and imaging features of chlamydial pneumonia in newborns. Methods: Medical records,chest X-Ray and CT findings of 17 neonates with chlamydia pneumonia were reviewed. The age was ranged from 9.0 to 28.0 days with mean of (16.8 ± 5.8) days. There were 11 males and 6 females. Sixteen were full term infants and one was born post term. All babies were examined with chest X-ray film, and 13 patients also underwent chest CT scan. Serologic test using immunofluorescence method for Chlamydia IgG and IgM antibodies were performed in all patients. Results: All newborns presented with cough but without fever. Positive results of the serologic tests were demonstrated. Chest films showed bilateral hyperventilation in 10 patients, diffuse reticular nodules in 10 patients including nodules mimicking military tuberculosis in 7 patients, and accompanying consolidation in 9 patients. CT features included interstitial reticular nodules in 13 patients with size, density, and distribution varied. Subpleural nodules (11 patients) and fusion of nodules (10 patients) predominated. Bilateral hyperinflation was found in 10 patients, which combined with infiltration in 12 patients, thickening of bronchovascular bundles in 10 patients, and ground glass sign in 5 patients. No pleural effusion and lymphadenopathy was detected in any patient. Conclusions: Bilateral hyperinflation and diffuse interstitial reticular nodules were the most common imaging features of neonatal chlamydial pneumonia. The main clinical characteristic of neonatal chlamydial pneumonia is respiratory symptoms without fever, which is helpful to its diagnosis. (authors)

  5. Learning Hierarchical Feature Extractors for Image Recognition

    2012-09-01

    feature space . . . . . . . . . . . . . . . 85 5.3.1 Preserving neighborhood relationships during coding . . . . . . 86 5.3.2 Letting only neighbors vote ...Letting only neighbors vote during pooling Pooling involves extracting an ensemble statistic from a potentially large group of in- puts. However...element. For slicing the 4D tensor S we adopt the MATLAB notation for simplicity of notation. function ConvCoD(x,D, α) Set: S = DT ∗ D Initialize: z = 0; β

  6. Featured Image: Identifying a Glowing Shell

    Kohler, Susanna

    2018-05-01

    New nebulae are being discovered and classified every day and this false-color image reveals one of the more recent objects of interest. This nebula, IPHASX J210204.7+471015, was recently imaged by the Andalucia Faint Object Spectrograph and Camera mounted on the 2.5-m Nordic Optical Telescope in La Palma, Spain. J210204 was initially identified as a possible planetary nebula a remnant left behind at the end of a red giants lifetime. Based on the above imaging, however, a team of authors led by Martn Guerrero (Institute of Astrophysics of Andalusia, Spain) is arguing that this shell of glowing gas was instead expelled around a classical nova. In a classical nova eruption, a white dwarf and its binary companion come very close together, and mass transfers to form a thin atmosphere of hydrogen around the white dwarf. When this hydrogen suddenly ignites in runaway fusion, this outer atmosphere can be expelled, forming a short-lived nova remnant which is what Guerrero and collaborators think were seeing with J210204. If so, this nebula can reveal information about the novathat caused it. To find out more about what the authors learned from this nebula, check out the paper below.CitationMartn A. Guerrero et al 2018 ApJ 857 80. doi:10.3847/1538-4357/aab669

  7. Imaging characteristics of hemophagocytic lymphohistiocytosis

    Fitzgerald, Nancy E.; MacClain, Kenneth L.

    2003-01-01

    Hemophagocytic lymphohistiocytosis (HLH) is a nonmalignant disorder of immune regulation, with overproduction of cytokines and diminished immune surveillance. Symptoms are nonspecific and may affect multiple organs, including the central nervous system. Neuroimaging findings have been described in case reports and small series; body imaging findings have not been described extensively. To summarize findings of the most frequently performed imaging studies of the brain, chest and abdomen in patients with HLH. Retrospective review of chest radiographs and CT, abdominal ultrasound and CT, brain CT and MRI, skeletal surveys, and autopsy data. Twenty-five patients were diagnosed and treated for HLH at our institution over an 11-year period; 15 patients (60%) died. Common chest radiograph findings included alveolar-interstitial opacities with pleural effusions, often with rapid evolution and resolution. Hepatosplenomegaly, gallbladder wall thickening, hyperechoic kidneys and ascites were common abdominal findings, which resolved after therapy in some cases. Brain-imaging studies revealed nonspecific periventricular white-matter abnormalities, brain-volume loss and enlargement of extra-axial fluid spaces. Three infant cases, one with intracranial hemorrhage, one with multiple pathologic rib fractures and one with diaphyseal periosteal reaction involving multiple long bones on skeletal survey, raised suspicion of child abuse at presentation. Abuse was not substantiated in any case. Clinicians and radiologists should be aware of the radiographic manifestations of HLH, which are nonspecific and overlap with infectious, inflammatory and neoplastic disorders. Findings in the chest (similar to acute respiratory distress syndrome) and abdomen may progress rapidly and then regress with institution of appropriate anti-HLH therapy. CNS findings may be progressive. In some infants, initial imaging findings may mimic nonaccidental trauma. (orig.)

  8. Imaging characteristics of hemophagocytic lymphohistiocytosis

    Fitzgerald, Nancy E. [E. B. Singleton Department of Diagnostic Imaging, Texas Children' s Hospital, 6621 Fannin Street, MC 2-2521, TX 77030, Houston (United States); MacClain, Kenneth L. [Texas Children' s Cancer Center, 6701 Fannin, Suite 1510, TX 77030, Houston (United States)

    2003-06-01

    Hemophagocytic lymphohistiocytosis (HLH) is a nonmalignant disorder of immune regulation, with overproduction of cytokines and diminished immune surveillance. Symptoms are nonspecific and may affect multiple organs, including the central nervous system. Neuroimaging findings have been described in case reports and small series; body imaging findings have not been described extensively. To summarize findings of the most frequently performed imaging studies of the brain, chest and abdomen in patients with HLH. Retrospective review of chest radiographs and CT, abdominal ultrasound and CT, brain CT and MRI, skeletal surveys, and autopsy data. Twenty-five patients were diagnosed and treated for HLH at our institution over an 11-year period; 15 patients (60%) died. Common chest radiograph findings included alveolar-interstitial opacities with pleural effusions, often with rapid evolution and resolution. Hepatosplenomegaly, gallbladder wall thickening, hyperechoic kidneys and ascites were common abdominal findings, which resolved after therapy in some cases. Brain-imaging studies revealed nonspecific periventricular white-matter abnormalities, brain-volume loss and enlargement of extra-axial fluid spaces. Three infant cases, one with intracranial hemorrhage, one with multiple pathologic rib fractures and one with diaphyseal periosteal reaction involving multiple long bones on skeletal survey, raised suspicion of child abuse at presentation. Abuse was not substantiated in any case. Clinicians and radiologists should be aware of the radiographic manifestations of HLH, which are nonspecific and overlap with infectious, inflammatory and neoplastic disorders. Findings in the chest (similar to acute respiratory distress syndrome) and abdomen may progress rapidly and then regress with institution of appropriate anti-HLH therapy. CNS findings may be progressive. In some infants, initial imaging findings may mimic nonaccidental trauma. (orig.)

  9. A visual perceptual descriptor with depth feature for image retrieval

    Wang, Tianyang; Qin, Zhengrui

    2017-07-01

    This paper proposes a visual perceptual descriptor (VPD) and a new approach to extract perceptual depth feature for 2D image retrieval. VPD mimics human visual system, which can easily distinguish regions that have different textures, whereas for regions which have similar textures, color features are needed for further differentiation. We apply VPD on the gradient direction map of an image, capture texture-similar regions to generate a VPD map. We then impose the VPD map on a quantized color map and extract color features only from the overlapped regions. To reflect the nature of perceptual distance in single 2D image, we propose and extract the perceptual depth feature by computing the nuclear norm of the sparse depth map of an image. Extracted color features and the perceptual depth feature are both incorporated to a feature vector, we utilize this vector to represent an image and measure similarity. We observe that the proposed VPD + depth method achieves a promising result, and extensive experiments prove that it outperforms other typical methods on 2D image retrieval.

  10. Axial nonimaging characteristics of imaging lenses: discussion.

    Siew, Ronian

    2016-05-01

    At observation planes away from the image plane, an imaging lens is a nonimaging optic. We examine the variation of axial irradiance with distance in image space and highlight the following little-known observation for discussion: On a per-unit-area basis, the position of the highest concentration in image space is generally not at the focal plane. This characteristic is contrary to common experience, and it offers an additional degree of freedom for the design of detection systems. Additionally, it would also apply to lenses with negative refractive index. The position of peak concentration and its irradiance is dependent upon the location and irradiance of the image. As such, this discussion also includes a close examination of expressions for image irradiance and explains how they are related to irradiance calculations beyond the image plane. This study is restricted to rotationally symmetric refractive imaging systems with incoherent extended Lambertian sources.

  11. MR Imaging Features of Fibrocystic Change of the Breast

    Chen, Jeon-Hor; Liu, Hui; Baek, Hyeon-Man; Nalcioglu, Orhan; Su, Min-Ying

    2008-01-01

    Purpose Studies specifically reporting MR imaging of fibrocystic change (FCC) of the breast are very few and its MR imaging features are not clearly known. The purpose of this study was to analyze the MR imaging features of FCC of the breast. Materials and Methods Thirty one patients of pathologically proved FCC of the breast were retrospectively reviewed. The MRI study was performed using a 1.5 T MR scanner with standard bilateral breast coil. The imaging protocol consisted of pre-contrast T1W imaging and dynamic contrast-enhanced axial T1W imaging. The MRI features were interpreted based on the morphologic and enhancement kinetic descriptors defined on ACR BIRADS-MRI lexicon. Results FCC of the breast had a wide spectrum of morphologic and kinetic features on MRI. Two types of FCC were found, including a more diffuse type of non-mass lesion (12/31, 39%) showing benign enhancement kinetic pattern with medium wash-in in early phase (9/10, 90%) and a focal mass type lesion (11/31, 35%) with enhancement kinetic usually showing rapid up-slope mimicking a breast cancer (8/11, 73%). Conclusion MRI is able to elaborate the diverse imaging features of fibrocystic change of the breast. Our result showed that FCC presenting as focal mass type lesion were usually over-diagnosed as malignancy. Understanding MR imaging of FCC is important to determine which cohort of patients should be followed up alone or receive aggressive management. PMID:18436406

  12. Effect of magnetic resonance imaging characteristics on uterine fibroid treatment

    Duc NM

    2018-04-01

    Full Text Available Nguyen Minh Duc, Huynh Quang HuyDepartment of Radiology, Pham Ngoc Thach University of Medicine, Ho Chi Minh City, VietnamAbstract: Uterine fibroids are the most common gynecological benign tumors adversely affecting the quality of life of women of a reproductive age. Magnetic resonance imaging (MRI is efficient at localizing the site of lesions and characterizing uterine fibroids before treatment. Understanding the different characteristics of uterine fibroids on MRI is essential, because it not only enables prompt diagnosis, but also guides the development of suitable therapeutic methods. This pictorial review demonstrates the effect of MRI features on uterine fibroid treatment. Keywords: uterine fibroids, characteristics, magnetic resonance imaging, treatments

  13. Features Selection for Skin Micro-Image Symptomatic Recognition

    HUYue-li; CAOJia-lin; ZHAOQian; FENGXu

    2004-01-01

    Automatic recognition of skin micro-image symptom is important in skin diagnosis and treatment. Feature selection is to improve the classification performance of skin micro-image symptom.This paper proposes a hybrid approach based on the support vector machine (SVM) technique and genetic algorithm (GA) to select an optimum feature subset from the feature group extracted from the skin micro-images. An adaptive GA is introduced for maintaining the convergence rate. With the proposed method, the average cross validation accuracy is increased from 88.25% using all features to 96.92% using only selected features provided by a classifier for classification of 5 classes of skin symptoms. The experimental results are satisfactory.

  14. Features Selection for Skin Micro-Image Symptomatic Recognition

    HU Yue-li; CAO Jia-lin; ZHAO Qian; FENG Xu

    2004-01-01

    Automatic recognition of skin micro-image symptom is important in skin diagnosis and treatment. Feature selection is to improve the classification performance of skin micro-image symptom.This paper proposes a hybrid approach based on the support vector machine (SVM) technique and genetic algorithm (GA) to select an optimum feature subset from the feature group extracted from the skin micro-images. An adaptive GA is introduced for maintaining the convergence rate. With the proposed method, the average cross validation accuracy is increased from 88.25% using all features to 96.92 % using only selected features provided by a classifier for classification of 5 classes of skin symptoms. The experimental results are satisfactory.

  15. FEATURE MATCHING OF HISTORICAL IMAGES BASED ON GEOMETRY OF QUADRILATERALS

    F. Maiwald

    2018-05-01

    Full Text Available This contribution shows an approach to match historical images from the photo library of the Saxon State and University Library Dresden (SLUB in the context of a historical three-dimensional city model of Dresden. In comparison to recent images, historical photography provides diverse factors which make an automatical image analysis (feature detection, feature matching and relative orientation of images difficult. Due to e.g. film grain, dust particles or the digitalization process, historical images are often covered by noise interfering with the image signal needed for a robust feature matching. The presented approach uses quadrilaterals in image space as these are commonly available in man-made structures and façade images (windows, stones, claddings. It is explained how to generally detect quadrilaterals in images. Consequently, the properties of the quadrilaterals as well as the relationship to neighbouring quadrilaterals are used for the description and matching of feature points. The results show that most of the matches are robust and correct but still small in numbers.

  16. Hand and wrist arthritis of Behcet disease: Imaging features

    Sugawara, Shunsuke; Ehara, Shigeru; Hitachi, Shin; Sugimoto, Hideharu

    2010-01-01

    Background: Reports on arthritis in Behcet disease are relatively scarce, and imaging features vary. Purpose: To document the various imaging features of articular disorders of the hand and wrist in Behcet disease. Material and Methods: Four patients, four women aged 26 to 65 years, fulfilling the diagnostic criteria of Behcet disease, with imaging findings of hand and wrist arthritis, were seen in two institutions. Radiography and magnetic resonance (MR) imaging were studied to elucidate the pattern and distribution. Results: Both non-erosive arthritis and erosive arthritis of different features were noted: one with non-erosive synovitis of the wrist, one with wrist synovitis with minimal erosion, and two with erosive arthritis of the distal interphalangeal joint. Conclusion: Imaging manifestations of arthritis of Behcet disease vary, and may be similar to other seronegative arthritides

  17. Image Mosaic Method Based on SIFT Features of Line Segment

    Jun Zhu

    2014-01-01

    Full Text Available This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling.

  18. Breast image feature learning with adaptive deconvolutional networks

    Jamieson, Andrew R.; Drukker, Karen; Giger, Maryellen L.

    2012-03-01

    Feature extraction is a critical component of medical image analysis. Many computer-aided diagnosis approaches employ hand-designed, heuristic lesion extracted features. An alternative approach is to learn features directly from images. In this preliminary study, we explored the use of Adaptive Deconvolutional Networks (ADN) for learning high-level features in diagnostic breast mass lesion images with potential application to computer-aided diagnosis (CADx) and content-based image retrieval (CBIR). ADNs (Zeiler, et. al., 2011), are recently-proposed unsupervised, generative hierarchical models that decompose images via convolution sparse coding and max pooling. We trained the ADNs to learn multiple layers of representation for two breast image data sets on two different modalities (739 full field digital mammography (FFDM) and 2393 ultrasound images). Feature map calculations were accelerated by use of GPUs. Following Zeiler et. al., we applied the Spatial Pyramid Matching (SPM) kernel (Lazebnik, et. al., 2006) on the inferred feature maps and combined this with a linear support vector machine (SVM) classifier for the task of binary classification between cancer and non-cancer breast mass lesions. Non-linear, local structure preserving dimension reduction, Elastic Embedding (Carreira-Perpiñán, 2010), was then used to visualize the SPM kernel output in 2D and qualitatively inspect image relationships learned. Performance was found to be competitive with current CADx schemes that use human-designed features, e.g., achieving a 0.632+ bootstrap AUC (by case) of 0.83 [0.78, 0.89] for an ultrasound image set (1125 cases).

  19. The analysis of image feature robustness using cometcloud

    Xin Qi

    2012-01-01

    Full Text Available The robustness of image features is a very important consideration in quantitative image analysis. The objective of this paper is to investigate the robustness of a range of image texture features using hematoxylin stained breast tissue microarray slides which are assessed while simulating different imaging challenges including out of focus, changes in magnification and variations in illumination, noise, compression, distortion, and rotation. We employed five texture analysis methods and tested them while introducing all of the challenges listed above. The texture features that were evaluated include co-occurrence matrix, center-symmetric auto-correlation, texture feature coding method, local binary pattern, and texton. Due to the independence of each transformation and texture descriptor, a network structured combination was proposed and deployed on the Rutgers private cloud. The experiments utilized 20 randomly selected tissue microarray cores. All the combinations of the image transformations and deformations are calculated, and the whole feature extraction procedure was completed in 70 minutes using a cloud equipped with 20 nodes. Center-symmetric auto-correlation outperforms all the other four texture descriptors but also requires the longest computational time. It is roughly 10 times slower than local binary pattern and texton. From a speed perspective, both the local binary pattern and texton features provided excellent performance for classification and content-based image retrieval.

  20. Feature representation of RGB-D images using joint spatial-depth feature pooling

    Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping

    2016-01-01

    Recent development in depth imaging technology makes acquisition of depth information easier. With the additional depth cue, RGB-D cameras can provide effective support for many RGB-D perception tasks beyond traditional RGB information. However, current feature representation based on RGB-D image...

  1. Design features and operating characteristics of the MC-50 cyclotron

    Bak, Hae Ill; Bak, Joo Shik

    1989-01-01

    The MC-50 cyclotron at Korean Cancer Center Hospital is now operational for neutron therapy and medical radioisotope production. Design features, mechanical structures and operating characteristics of the MC-50 are described in this paper. Optimum operating condition for this cyclotron has been determined by the repetitive running, and the performances of the internal beam have been investigated through the measurements of intensity and spatial distribution of the internal beam as a function of the radius of the cyclotron. Routinely, the 40 μA of 50 MeV protons have been obtained at first Faraday cup with a extraction efficiency of 61%. (Author)

  2. Pilomatricomas in children: imaging characteristics with pathologic correlation

    Lim, Hyun Wook; Im, Soo Ah; Lim, Gye-Yeon; Park, Hyun Jin; Lee, Heejeong; Sung, Mi Sook; Kang, Bong Joo; Kim, Jee Young

    2007-01-01

    Although pilomatricoma commonly occurs in children, there is still a poor understanding of the imaging characteristics of pilomatricoma and lack of agreement regarding its imaging findings and histopathologic features. To characterize the radiologic appearance of pilomatricomas on US, CT, and MR and to correlate the imaging findings with histopathologic features. The imaging findings of 47 pilomatricomas on US (n = 17), CT (n = 31), and MR (n = 5) were retrospectively evaluated. Pathologic specimens of all cases were reviewed and compared with imaging findings. All lesions were well-circumscribed, subcutaneous nodules with partial attachment to the overlying skin. On US, the lesions were mostly hyperechoic with posterior acoustic shadowing and hypoechoic rim. On CT, they appeared as enhancing soft-tissue masses with varying amounts of calcification. MR findings were internal reticulations and patchy areas on T2-weighted images and contrast-enhanced T1-weighted images, corresponding to edematous stroma on pathology. Peritumoral inflammatory changes and connective capsule on pathology were well correlated with imaging findings. Pilomatricoma should be considered when US or CT shows a well-defined hyperechoic or calcific nodule in subcutaneous fat attached to the skin in children. MR images may be helpful in diagnosis. Pathologic findings are well correlated with imaging findings. (orig.)

  3. Convolutional neural network features based change detection in satellite images

    Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong

    2016-07-01

    With the popular use of high resolution remote sensing (HRRS) satellite images, a huge research efforts have been placed on change detection (CD) problem. An effective feature selection method can significantly boost the final result. While hand-designed features have proven difficulties to design features that effectively capture high and mid-level representations, the recent developments in machine learning (Deep Learning) omit this problem by learning hierarchical representation in an unsupervised manner directly from data without human intervention. In this letter, we propose approaching the change detection problem from a feature learning perspective. A novel deep Convolutional Neural Networks (CNN) features based HR satellite images change detection method is proposed. The main guideline is to produce a change detection map directly from two images using a pretrained CNN. This method can omit the limited performance of hand-crafted features. Firstly, CNN features are extracted through different convolutional layers. Then, a concatenation step is evaluated after an normalization step, resulting in a unique higher dimensional feature map. Finally, a change map was computed using pixel-wise Euclidean distance. Our method has been validated on real bitemporal HRRS satellite images according to qualitative and quantitative analyses. The results obtained confirm the interest of the proposed method.

  4. Image feature extraction based on the camouflage effectiveness evaluation

    Yuan, Xin; Lv, Xuliang; Li, Ling; Wang, Xinzhu; Zhang, Zhi

    2018-04-01

    The key step of camouflage effectiveness evaluation is how to combine the human visual physiological features, psychological features to select effectively evaluation indexes. Based on the predecessors' camo comprehensive evaluation method, this paper chooses the suitable indexes combining with the image quality awareness, and optimizes those indexes combining with human subjective perception. Thus, it perfects the theory of index extraction.

  5. Featured Image: Orbiting Stars Share an Envelope

    Kohler, Susanna

    2016-03-01

    This beautiful series of snapshots from a simulation (click for a better look!) shows what happens when two stars in a binary system become enclosed in the same stellar envelope. In this binary system, one of the stars has exhausted its hydrogen fuel and become a red giant, complete with an expanding stellar envelope composed of hydrogen and helium. Eventually, the envelope expands so much that the companion star falls into it, where it releases gravitational potential energy into the common envelope. A team led by Sebastian Ohlmann (Heidelberg Institute for Theoretical Studies and University of Wrzburg) recently performed hydrodynamic simulations of this process. Ohlmann and collaborators discovered that the energy release eventually triggers large-scale flow instabilities, which leads to turbulence within the envelope. This process has important consequences for how these systems next evolve (for instance, determining whether or not a supernova occurs!). You can check out the authors video of their simulated stellar inspiral below, or see their paper for more images and results from their study.CitationSebastian T. Ohlmann et al 2016 ApJ 816 L9. doi:10.3847/2041-8205/816/1/L9

  6. Featured Image: Making Dust in the Lab

    Kohler, Susanna

    2017-12-01

    This remarkable photograph (which spans only 10 m across; click for a full view) reveals what happens when you form dust grains in a laboratory under conditions similar to those of interstellar space. The cosmic life cycle of dust grains is not well understood we know that in the interstellar medium (ISM), dust is destroyed at a higher rate than it is produced by stellar sources. Since the amount of dust in the ISM stays constant, however, there must be additional sources of dust production besides stars. A team of scientists led by Daniele Fulvio (Pontifical Catholic University of Rio de Janeiro and the Max Planck Institute for Astronomy at the Friedrich Schiller University Jena) have now studied formation mechanisms of dust grains in the lab by mimicking low-temperature ISM conditions and exploring how, under these conditions, carbonaceous materials condense from gas phase to form dust grains. To read more about their results and see additional images, check out the paper below.CitationDaniele Fulvio et al 2017 ApJS 233 14. doi:10.3847/1538-4365/aa9224

  7. CT and MR imaging features of hydrocephalus

    Shier, C.K.; George, A.E.; de Leon, M.J.; Stylopoulos, L.A.; Pinto, R.S.

    1989-01-01

    Sylvian fissure and sulcal enlargement is generally perceived as indicative of cortical atrophy and has been used by surgeons in cases of suspected hydrocephalus as a criterion for exclusion from ventricular shunting procedure. The authors have observed sylvian fissure collapse following ventricular shunting in several patients with communicating hydrocephalus (CH). The purpose of this study was to determine the incidence of this finding in patients with CH. The pre- and postshunt CT and MR images of 30 patients with communicating hydrocephalus were reviewed. As anticipated, after shunting a diminution in caliber of the lateral ventricle bodies, temporal horns, and third ventricle occurred in a majority of cases. However, sulcal width paradoxically decreased in 13% of cases after shunt, and sylvian fissure size decreased in seven patients after shunt (23%). In summary, large sylvian fissures and focally dilated sulci do not rule out the presence of hydrocephalus and may in fact act as cerebrospinal fluid reservoirs in cases of obstruction higher along the cerebral convexities

  8. Smart Images Search based on Visual Features Fusion

    Saad, M.H.

    2013-01-01

    Image search engines attempt to give fast and accurate access to the wide range of the huge amount images available on the Internet. There have been a number of efforts to build search engines based on the image content to enhance search results. Content-Based Image Retrieval (CBIR) systems have achieved a great interest since multimedia files, such as images and videos, have dramatically entered our lives throughout the last decade. CBIR allows automatically extracting target images according to objective visual contents of the image itself, for example its shapes, colors and textures to provide more accurate ranking of the results. The recent approaches of CBIR differ in terms of which image features are extracted to be used as image descriptors for matching process. This thesis proposes improvements of the efficiency and accuracy of CBIR systems by integrating different types of image features. This framework addresses efficient retrieval of images in large image collections. A comparative study between recent CBIR techniques is provided. According to this study; image features need to be integrated to provide more accurate description of image content and better image retrieval accuracy. In this context, this thesis presents new image retrieval approaches that provide more accurate retrieval accuracy than previous approaches. The first proposed image retrieval system uses color, texture and shape descriptors to form the global features vector. This approach integrates the yc b c r color histogram as a color descriptor, the modified Fourier descriptor as a shape descriptor and modified Edge Histogram as a texture descriptor in order to enhance the retrieval results. The second proposed approach integrates the global features vector, which is used in the first approach, with the SURF salient point technique as local feature. The nearest neighbor matching algorithm with a proposed similarity measure is applied to determine the final image rank. The second approach

  9. Disorders of the pediatric pancreas: imaging features

    Nijs, Els; Callahan, Michael J.; Taylor, George A.

    2005-01-01

    The purpose of this manuscript is to provide an overview of the normal development of the pancreas as well as pancreatic pathology in children. Diagnostic imaging plays a major role in the evaluation of the pancreas in infants and children. Familiarity with the range of normal appearance and the diseases that commonly affect this gland is important for the accurate and timely diagnosis of pancreatic disorders in the pediatric population. Normal embryology is discussed, as are the most common congenital anomalies that occur as a result of aberrant development during embryology. These include pancreas divisum, annular pancreas, agenesis of the dorsal pancreatic anlagen and ectopic pancreatic tissue. Syndromes that can manifest pancreatic pathology include: Beckwith Wiedemann syndrome, von Hippel-Lindau disease and autosomal dominant polycystic kidney disease. Children and adults with cystic fibrosis and Shwachman-Diamond syndrome frequently present with pancreatic insufficiency. Trauma is the most common cause of pancreatitis in children. In younger children, unexplained pancreatic injury must always alert the radiologist to potential child abuse. Pancreatic pseudocysts are a complication of trauma, but can also be seen in the setting of acute or chronic pancreatitis from other causes. Primary pancreatic neoplasms are rare in children and are divided into exocrine tumors such as pancreatoblastoma and adenocarcinoma and into endocrine or islet cell tumors. Islet cell tumors are classified as functioning (insulinoma, gastrinoma, VIPoma and glucagonoma) and nonfunctioning tumors. Solid-cystic papillary tumor is probably the most common pancreatic tumor in Asian children. Although quite rare, secondary tumors of the pancreas can be associated with certain primary malignancies. (orig.)

  10. Disorders of the pediatric pancreas: imaging features

    Nijs, Els [University Hospital Gasthuisberg, Department of Radiology, Leuven (Belgium); Callahan, Michael J.; Taylor, George A. [Boston Children' s Hospital, Department of Radiology, Boston, MA (United States)

    2005-04-01

    The purpose of this manuscript is to provide an overview of the normal development of the pancreas as well as pancreatic pathology in children. Diagnostic imaging plays a major role in the evaluation of the pancreas in infants and children. Familiarity with the range of normal appearance and the diseases that commonly affect this gland is important for the accurate and timely diagnosis of pancreatic disorders in the pediatric population. Normal embryology is discussed, as are the most common congenital anomalies that occur as a result of aberrant development during embryology. These include pancreas divisum, annular pancreas, agenesis of the dorsal pancreatic anlagen and ectopic pancreatic tissue. Syndromes that can manifest pancreatic pathology include: Beckwith Wiedemann syndrome, von Hippel-Lindau disease and autosomal dominant polycystic kidney disease. Children and adults with cystic fibrosis and Shwachman-Diamond syndrome frequently present with pancreatic insufficiency. Trauma is the most common cause of pancreatitis in children. In younger children, unexplained pancreatic injury must always alert the radiologist to potential child abuse. Pancreatic pseudocysts are a complication of trauma, but can also be seen in the setting of acute or chronic pancreatitis from other causes. Primary pancreatic neoplasms are rare in children and are divided into exocrine tumors such as pancreatoblastoma and adenocarcinoma and into endocrine or islet cell tumors. Islet cell tumors are classified as functioning (insulinoma, gastrinoma, VIPoma and glucagonoma) and nonfunctioning tumors. Solid-cystic papillary tumor is probably the most common pancreatic tumor in Asian children. Although quite rare, secondary tumors of the pancreas can be associated with certain primary malignancies. (orig.)

  11. Invariant Feature Matching for Image Registration Application Based on New Dissimilarity of Spatial Features

    Mousavi Kahaki, Seyed Mostafa; Nordin, Md Jan; Ashtari, Amir H.; J. Zahra, Sophia

    2016-01-01

    An invariant feature matching method is proposed as a spatially invariant feature matching approach. Deformation effects, such as affine and homography, change the local information within the image and can result in ambiguous local information pertaining to image points. New method based on dissimilarity values, which measures the dissimilarity of the features through the path based on Eigenvector properties, is proposed. Evidence shows that existing matching techniques using similarity metrics—such as normalized cross-correlation, squared sum of intensity differences and correlation coefficient—are insufficient for achieving adequate results under different image deformations. Thus, new descriptor’s similarity metrics based on normalized Eigenvector correlation and signal directional differences, which are robust under local variation of the image information, are proposed to establish an efficient feature matching technique. The method proposed in this study measures the dissimilarity in the signal frequency along the path between two features. Moreover, these dissimilarity values are accumulated in a 2D dissimilarity space, allowing accurate corresponding features to be extracted based on the cumulative space using a voting strategy. This method can be used in image registration applications, as it overcomes the limitations of the existing approaches. The output results demonstrate that the proposed technique outperforms the other methods when evaluated using a standard dataset, in terms of precision-recall and corner correspondence. PMID:26985996

  12. Invariant Feature Matching for Image Registration Application Based on New Dissimilarity of Spatial Features.

    Seyed Mostafa Mousavi Kahaki

    Full Text Available An invariant feature matching method is proposed as a spatially invariant feature matching approach. Deformation effects, such as affine and homography, change the local information within the image and can result in ambiguous local information pertaining to image points. New method based on dissimilarity values, which measures the dissimilarity of the features through the path based on Eigenvector properties, is proposed. Evidence shows that existing matching techniques using similarity metrics--such as normalized cross-correlation, squared sum of intensity differences and correlation coefficient--are insufficient for achieving adequate results under different image deformations. Thus, new descriptor's similarity metrics based on normalized Eigenvector correlation and signal directional differences, which are robust under local variation of the image information, are proposed to establish an efficient feature matching technique. The method proposed in this study measures the dissimilarity in the signal frequency along the path between two features. Moreover, these dissimilarity values are accumulated in a 2D dissimilarity space, allowing accurate corresponding features to be extracted based on the cumulative space using a voting strategy. This method can be used in image registration applications, as it overcomes the limitations of the existing approaches. The output results demonstrate that the proposed technique outperforms the other methods when evaluated using a standard dataset, in terms of precision-recall and corner correspondence.

  13. Perinatal clinical and imaging features of CLOVES syndrome

    Fernandez-Pineda, Israel [Virgen del Rocio Children' s Hospital, Department of Pediatric Surgery, Seville (Spain); Fajardo, Manuel [Virgen del Rocio Children' s Hospital, Department of Pediatric Radiology, Seville (Spain); Chaudry, Gulraiz; Alomari, Ahmad I. [Children' s Hospital Boston and Harvard Medical School, Division of Vascular and Interventional Radiology, Boston, MA (United States)

    2010-08-15

    We report a neonate with antenatal imaging features suggestive of CLOVES syndrome. Postnatal clinical and imaging findings confirmed the diagnosis, with the constellation of truncal overgrowth, cutaneous capillary malformation, lymphatic and musculoskeletal anomalies. The clinical, radiological and histopathological findings noted in this particular phenotype help differentiate it from other overgrowth syndromes with complex vascular anomalies. (orig.)

  14. Robust Tomato Recognition for Robotic Harvesting Using Feature Images Fusion

    Yuanshen Zhao

    2016-01-01

    Full Text Available Automatic recognition of mature fruits in a complex agricultural environment is still a challenge for an autonomous harvesting robot due to various disturbances existing in the background of the image. The bottleneck to robust fruit recognition is reducing influence from two main disturbances: illumination and overlapping. In order to recognize the tomato in the tree canopy using a low-cost camera, a robust tomato recognition algorithm based on multiple feature images and image fusion was studied in this paper. Firstly, two novel feature images, the  a*-component image and the I-component image, were extracted from the L*a*b* color space and luminance, in-phase, quadrature-phase (YIQ color space, respectively. Secondly, wavelet transformation was adopted to fuse the two feature images at the pixel level, which combined the feature information of the two source images. Thirdly, in order to segment the target tomato from the background, an adaptive threshold algorithm was used to get the optimal threshold. The final segmentation result was processed by morphology operation to reduce a small amount of noise. In the detection tests, 93% target tomatoes were recognized out of 200 overall samples. It indicates that the proposed tomato recognition method is available for robotic tomato harvesting in the uncontrolled environment with low cost.

  15. Robust Tomato Recognition for Robotic Harvesting Using Feature Images Fusion.

    Zhao, Yuanshen; Gong, Liang; Huang, Yixiang; Liu, Chengliang

    2016-01-29

    Automatic recognition of mature fruits in a complex agricultural environment is still a challenge for an autonomous harvesting robot due to various disturbances existing in the background of the image. The bottleneck to robust fruit recognition is reducing influence from two main disturbances: illumination and overlapping. In order to recognize the tomato in the tree canopy using a low-cost camera, a robust tomato recognition algorithm based on multiple feature images and image fusion was studied in this paper. Firstly, two novel feature images, the  a*-component image and the I-component image, were extracted from the L*a*b* color space and luminance, in-phase, quadrature-phase (YIQ) color space, respectively. Secondly, wavelet transformation was adopted to fuse the two feature images at the pixel level, which combined the feature information of the two source images. Thirdly, in order to segment the target tomato from the background, an adaptive threshold algorithm was used to get the optimal threshold. The final segmentation result was processed by morphology operation to reduce a small amount of noise. In the detection tests, 93% target tomatoes were recognized out of 200 overall samples. It indicates that the proposed tomato recognition method is available for robotic tomato harvesting in the uncontrolled environment with low cost.

  16. A comparison of image features for registering LWIR and visual images

    Cronje, J

    2012-11-01

    Full Text Available This paper presents a comparison of several established and recent image feature-descriptors to register long wave infra-red images in the 8–14 m band to visual band images. The feature descriptors were chosen to include robust algorithms, SURF...

  17. Imaging features of nontumorous conditions involving the trachea and main-stem bronchi

    Jeon, Kyung Nyeo; Kang, Duk Sik; Bae, Kyung Soo

    2002-01-01

    A number of nontumorous diseases may affect the trachea and main-stem bronchi, and their nonspecific symptoms may include coughing, dyspnea, wheezing and stridor. The clinical course is often long-term and a misdiagnosis of bronchial asthma is common. The imaging findings of these nontumorous conditions are, however, relatively characteristic, and diagnosis either without or in conjunction with clinical information is often possible. For specific diagnosis, recognition of their imaging features is therefore of prime importance. In this pictorial essay, we illustrate the imaging features of various nontumorous conditions involving the trachea and main-stem bronchi

  18. INTEGRATION OF IMAGE-DERIVED AND POS-DERIVED FEATURES FOR IMAGE BLUR DETECTION

    T.-A. Teo

    2016-06-01

    Full Text Available The image quality plays an important role for Unmanned Aerial Vehicle (UAV’s applications. The small fixed wings UAV is suffering from the image blur due to the crosswind and the turbulence. Position and Orientation System (POS, which provides the position and orientation information, is installed onto an UAV to enable acquisition of UAV trajectory. It can be used to calculate the positional and angular velocities when the camera shutter is open. This study proposes a POS-assisted method to detect the blur image. The major steps include feature extraction, blur image detection and verification. In feature extraction, this study extracts different features from images and POS. The image-derived features include mean and standard deviation of image gradient. For POS-derived features, we modify the traditional degree-of-linear-blur (blinear method to degree-of-motion-blur (bmotion based on the collinear condition equations and POS parameters. Besides, POS parameters such as positional and angular velocities are also adopted as POS-derived features. In blur detection, this study uses Support Vector Machines (SVM classifier and extracted features (i.e. image information, POS data, blinear and bmotion to separate blur and sharp UAV images. The experiment utilizes SenseFly eBee UAV system. The number of image is 129. In blur image detection, we use the proposed degree-of-motion-blur and other image features to classify the blur image and sharp images. The classification result shows that the overall accuracy using image features is only 56%. The integration of image-derived and POS-derived features have improved the overall accuracy from 56% to 76% in blur detection. Besides, this study indicates that the performance of the proposed degree-of-motion-blur is better than the traditional degree-of-linear-blur.

  19. A new and fast image feature selection method for developing an optimal mammographic mass detection scheme.

    Tan, Maxine; Pu, Jiantao; Zheng, Bin

    2014-08-01

    Selecting optimal features from a large image feature pool remains a major challenge in developing computer-aided detection (CAD) schemes of medical images. The objective of this study is to investigate a new approach to significantly improve efficacy of image feature selection and classifier optimization in developing a CAD scheme of mammographic masses. An image dataset including 1600 regions of interest (ROIs) in which 800 are positive (depicting malignant masses) and 800 are negative (depicting CAD-generated false positive regions) was used in this study. After segmentation of each suspicious lesion by a multilayer topographic region growth algorithm, 271 features were computed in different feature categories including shape, texture, contrast, isodensity, spiculation, local topological features, as well as the features related to the presence and location of fat and calcifications. Besides computing features from the original images, the authors also computed new texture features from the dilated lesion segments. In order to select optimal features from this initial feature pool and build a highly performing classifier, the authors examined and compared four feature selection methods to optimize an artificial neural network (ANN) based classifier, namely: (1) Phased Searching with NEAT in a Time-Scaled Framework, (2) A sequential floating forward selection (SFFS) method, (3) A genetic algorithm (GA), and (4) A sequential forward selection (SFS) method. Performances of the four approaches were assessed using a tenfold cross validation method. Among these four methods, SFFS has highest efficacy, which takes 3%-5% of computational time as compared to GA approach, and yields the highest performance level with the area under a receiver operating characteristic curve (AUC) = 0.864 ± 0.034. The results also demonstrated that except using GA, including the new texture features computed from the dilated mass segments improved the AUC results of the ANNs optimized

  20. Feature-Based Retinal Image Registration Using D-Saddle Feature

    Roziana Ramli

    2017-01-01

    Full Text Available Retinal image registration is important to assist diagnosis and monitor retinal diseases, such as diabetic retinopathy and glaucoma. However, registering retinal images for various registration applications requires the detection and distribution of feature points on the low-quality region that consists of vessels of varying contrast and sizes. A recent feature detector known as Saddle detects feature points on vessels that are poorly distributed and densely positioned on strong contrast vessels. Therefore, we propose a multiresolution difference of Gaussian pyramid with Saddle detector (D-Saddle to detect feature points on the low-quality region that consists of vessels with varying contrast and sizes. D-Saddle is tested on Fundus Image Registration (FIRE Dataset that consists of 134 retinal image pairs. Experimental results show that D-Saddle successfully registered 43% of retinal image pairs with average registration accuracy of 2.329 pixels while a lower success rate is observed in other four state-of-the-art retinal image registration methods GDB-ICP (28%, Harris-PIIFD (4%, H-M (16%, and Saddle (16%. Furthermore, the registration accuracy of D-Saddle has the weakest correlation (Spearman with the intensity uniformity metric among all methods. Finally, the paired t-test shows that D-Saddle significantly improved the overall registration accuracy of the original Saddle.

  1. Online Feature Selection for Classifying Emphysema in HRCT Images

    M. Prasad

    2008-06-01

    Full Text Available Feature subset selection, applied as a pre- processing step to machine learning, is valuable in dimensionality reduction, eliminating irrelevant data and improving classifier performance. In the classic formulation of the feature selection problem, it is assumed that all the features are available at the beginning. However, in many real world problems, there are scenarios where not all features are present initially and must be integrated as they become available. In such scenarios, online feature selection provides an efficient way to sort through a large space of features. It is in this context that we introduce online feature selection for the classification of emphysema, a smoking related disease that appears as low attenuation regions in High Resolution Computer Tomography (HRCT images. The technique was successfully evaluated on 61 HRCT scans and compared with different online feature selection approaches, including hill climbing, best first search, grafting, and correlation-based feature selection. The results were also compared against ldensity maskr, a standard approach used for emphysema detection in medical image analysis.

  2. Image Recommendation Algorithm Using Feature-Based Collaborative Filtering

    Kim, Deok-Hwan

    As the multimedia contents market continues its rapid expansion, the amount of image contents used in mobile phone services, digital libraries, and catalog service is increasing remarkably. In spite of this rapid growth, users experience high levels of frustration when searching for the desired image. Even though new images are profitable to the service providers, traditional collaborative filtering methods cannot recommend them. To solve this problem, in this paper, we propose feature-based collaborative filtering (FBCF) method to reflect the user's most recent preference by representing his purchase sequence in the visual feature space. The proposed approach represents the images that have been purchased in the past as the feature clusters in the multi-dimensional feature space and then selects neighbors by using an inter-cluster distance function between their feature clusters. Various experiments using real image data demonstrate that the proposed approach provides a higher quality recommendation and better performance than do typical collaborative filtering and content-based filtering techniques.

  3. Abdominal vascular syndromes: characteristic imaging findings

    Cardarelli-Leite, Leandro; Velloni, Fernanda Garozzo; Salvadori, Priscila Silveira; Lemos, Marcelo Delboni; D'Ippolito, Giuseppe

    2016-01-01

    Abdominal vascular syndromes are rare diseases. Although such syndromes vary widely in terms of symptoms and etiologies, certain imaging findings are characteristic. Depending on their etiology, they can be categorized as congenital - including blue rubber bleb nevus syndrome, Klippel-Trenaunay syndrome, and hereditary hemorrhagic telangiectasia (Rendu-Osler-Weber syndrome) - compressive - including 'nutcracker' syndrome, median arcuate ligament syndrome, Cockett syndrome (also known as May-Thurner syndrome), and superior mesenteric artery syndrome. In this article, we aimed to illustrate imaging findings that are characteristic of these syndromes, through studies conducted at our institution, as well as to perform a brief review of the literature on this topic. (author)

  4. Abdominal vascular syndromes: characteristic imaging findings

    Cardarelli-Leite, Leandro; Velloni, Fernanda Garozzo; Salvadori, Priscila Silveira; Lemos, Marcelo Delboni; D' Ippolito, Giuseppe, E-mail: leandrocleite@gmail.com [Universidade Federal de Sao Paulo (EPM/UNIFESP), Sao Paulo, SP (Brazil). Escola Paulista de Mediciana. Departmento de Diagnostico por Imagem

    2016-07-15

    Abdominal vascular syndromes are rare diseases. Although such syndromes vary widely in terms of symptoms and etiologies, certain imaging findings are characteristic. Depending on their etiology, they can be categorized as congenital - including blue rubber bleb nevus syndrome, Klippel-Trenaunay syndrome, and hereditary hemorrhagic telangiectasia (Rendu-Osler-Weber syndrome) - compressive - including 'nutcracker' syndrome, median arcuate ligament syndrome, Cockett syndrome (also known as May-Thurner syndrome), and superior mesenteric artery syndrome. In this article, we aimed to illustrate imaging findings that are characteristic of these syndromes, through studies conducted at our institution, as well as to perform a brief review of the literature on this topic. (author)

  5. Multimodal Image Alignment via Linear Mapping between Feature Modalities.

    Jiang, Yanyun; Zheng, Yuanjie; Hou, Sujuan; Chang, Yuchou; Gee, James

    2017-01-01

    We propose a novel landmark matching based method for aligning multimodal images, which is accomplished uniquely by resolving a linear mapping between different feature modalities. This linear mapping results in a new measurement on similarity of images captured from different modalities. In addition, our method simultaneously solves this linear mapping and the landmark correspondences by minimizing a convex quadratic function. Our method can estimate complex image relationship between different modalities and nonlinear nonrigid spatial transformations even in the presence of heavy noise, as shown in our experiments carried out by using a variety of image modalities.

  6. Malignant fibrous histiocytoma of bone: conventional X-ray and MR imaging features

    Link, T.M.; Haeussler, M.D.; Poppek, S.; Woertler, K.; Rummeny, E.J.; Blasius, S.; Lindner, N.

    1998-01-01

    Objective. To evaluate the conventional X-ray and MR imaging features of malignant fibrous histiocytoma (MFH) of bone. Design. MRI examinations and conventional radiographs were reviewed in 39 patients with biopsy-proven MFH. Imaging characteristics were analyzed and the differential diagnoses assessed in a masked fashion by two experienced radiologists. Results. Typical X-ray features included aggressive, destructive tumor growth centrally located in the metaphysis of long bones. Periosteal reactions and expansive growth were rarely seen. On MR images extraosseous tumor spread was frequently noted. On T2-weighted images and contrast-enhanced T1-weighted images most of the tumors displayed an inhomogeneous, nodular signal pattern with peripheral Gd-DTPA enhancement. Conclusions. Although several MR imaging criteria were typical for MFH none of them was specific. X-ray diagnosis of MFH may also prove difficult, with the main differential diagnosis being metastasis in the older and osteosarcoma in the younger population. (orig.)

  7. Simultenious binary hash and features learning for image retrieval

    Frantc, V. A.; Makov, S. V.; Voronin, V. V.; Marchuk, V. I.; Semenishchev, E. A.; Egiazarian, K. O.; Agaian, S.

    2016-05-01

    Content-based image retrieval systems have plenty of applications in modern world. The most important one is the image search by query image or by semantic description. Approaches to this problem are employed in personal photo-collection management systems, web-scale image search engines, medical systems, etc. Automatic analysis of large unlabeled image datasets is virtually impossible without satisfactory image-retrieval technique. It's the main reason why this kind of automatic image processing has attracted so much attention during recent years. Despite rather huge progress in the field, semantically meaningful image retrieval still remains a challenging task. The main issue here is the demand to provide reliable results in short amount of time. This paper addresses the problem by novel technique for simultaneous learning of global image features and binary hash codes. Our approach provide mapping of pixel-based image representation to hash-value space simultaneously trying to save as much of semantic image content as possible. We use deep learning methodology to generate image description with properties of similarity preservation and statistical independence. The main advantage of our approach in contrast to existing is ability to fine-tune retrieval procedure for very specific application which allow us to provide better results in comparison to general techniques. Presented in the paper framework for data- dependent image hashing is based on use two different kinds of neural networks: convolutional neural networks for image description and autoencoder for feature to hash space mapping. Experimental results confirmed that our approach has shown promising results in compare to other state-of-the-art methods.

  8. Vehicle Unsteady Dynamics Characteristics Based on Tire and Road Features

    Bin Ma

    2013-01-01

    Full Text Available During automotive related accidents, tire and road play an important role in vehicle unsteady dynamics as they have a significant impact on the sliding friction. The calculation of the rubber viscoelastic energy loss modulus and the true contact area model is improved based on the true contact area and the rubber viscoelastic theory. A 10 DOF full vehicle dynamic model in consideration of the kinetic sliding friction coefficient which has good accuracy and reality is developed. The stability test is carried out to evaluate the effectiveness of the model, and the simulation test is done in MATLAB to analyze the impact of tire feature and road self-affine characteristics on the sport utility vehicle (SUV unsteady dynamics under different weights. The findings show that it is a great significance to analyze the SUV dynamics equipped with different tire on different roads, which may provide useful insights into solving the explicit-implicit features of tire prints in systematically and designing active safety systems.

  9. Improved image retrieval based on fuzzy colour feature vector

    Ben-Ahmeida, Ahlam M.; Ben Sasi, Ahmed Y.

    2013-03-01

    One of Image indexing techniques is the Content-Based Image Retrieval which is an efficient way for retrieving images from the image database automatically based on their visual contents such as colour, texture, and shape. In this paper will be discuss how using content-based image retrieval (CBIR) method by colour feature extraction and similarity checking. By dividing the query image and all images in the database into pieces and extract the features of each part separately and comparing the corresponding portions in order to increase the accuracy in the retrieval. The proposed approach is based on the use of fuzzy sets, to overcome the problem of curse of dimensionality. The contribution of colour of each pixel is associated to all the bins in the histogram using fuzzy-set membership functions. As a result, the Fuzzy Colour Histogram (FCH), outperformed the Conventional Colour Histogram (CCH) in image retrieving, due to its speedy results, where were images represented as signatures that took less size of memory, depending on the number of divisions. The results also showed that FCH is less sensitive and more robust to brightness changes than the CCH with better retrieval recall values.

  10. HDR IMAGING FOR FEATURE DETECTION ON DETAILED ARCHITECTURAL SCENES

    G. Kontogianni

    2015-02-01

    Full Text Available 3D reconstruction relies on accurate detection, extraction, description and matching of image features. This is even truer for complex architectural scenes that pose needs for 3D models of high quality, without any loss of detail in geometry or color. Illumination conditions influence the radiometric quality of images, as standard sensors cannot depict properly a wide range of intensities in the same scene. Indeed, overexposed or underexposed pixels cause irreplaceable information loss and degrade digital representation. Images taken under extreme lighting environments may be thus prohibitive for feature detection/extraction and consequently for matching and 3D reconstruction. High Dynamic Range (HDR images could be helpful for these operators because they broaden the limits of illumination range that Standard or Low Dynamic Range (SDR/LDR images can capture and increase in this way the amount of details contained in the image. Experimental results of this study prove this assumption as they examine state of the art feature detectors applied both on standard dynamic range and HDR images.

  11. An image-processing methodology for extracting bloodstain pattern features.

    Arthur, Ravishka M; Humburg, Philomena J; Hoogenboom, Jerry; Baiker, Martin; Taylor, Michael C; de Bruin, Karla G

    2017-08-01

    There is a growing trend in forensic science to develop methods to make forensic pattern comparison tasks more objective. This has generally involved the application of suitable image-processing methods to provide numerical data for identification or comparison. This paper outlines a unique image-processing methodology that can be utilised by analysts to generate reliable pattern data that will assist them in forming objective conclusions about a pattern. A range of features were defined and extracted from a laboratory-generated impact spatter pattern. These features were based in part on bloodstain properties commonly used in the analysis of spatter bloodstain patterns. The values of these features were consistent with properties reported qualitatively for such patterns. The image-processing method developed shows considerable promise as a way to establish measurable discriminating pattern criteria that are lacking in current bloodstain pattern taxonomies. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Hierarchical Feature Extraction With Local Neural Response for Image Recognition.

    Li, Hong; Wei, Yantao; Li, Luoqing; Chen, C L P

    2013-04-01

    In this paper, a hierarchical feature extraction method is proposed for image recognition. The key idea of the proposed method is to extract an effective feature, called local neural response (LNR), of the input image with nontrivial discrimination and invariance properties by alternating between local coding and maximum pooling operation. The local coding, which is carried out on the locally linear manifold, can extract the salient feature of image patches and leads to a sparse measure matrix on which maximum pooling is carried out. The maximum pooling operation builds the translation invariance into the model. We also show that other invariant properties, such as rotation and scaling, can be induced by the proposed model. In addition, a template selection algorithm is presented to reduce computational complexity and to improve the discrimination ability of the LNR. Experimental results show that our method is robust to local distortion and clutter compared with state-of-the-art algorithms.

  13. Imaging of Groin Pain: Magnetic Resonance and Ultrasound Imaging Features.

    Lee, Susan C; Endo, Yoshimi; Potter, Hollis G

    Evaluation of groin pain in athletes may be challenging as pain is typically poorly localized and the pubic symphyseal region comprises closely approximated tendons and muscles. As such, magnetic resonance imaging (MRI) and ultrasound (US) may help determine the etiology of groin pain. A PubMed search was performed using the following search terms: ultrasound, magnetic resonance imaging, sports hernia, athletic pubalgia, and groin pain. Date restrictions were not placed on the literature search. Clinical review. Level 4. MRI is sensitive in diagnosing pathology in groin pain. Not only can MRI be used to image rectus abdominis/adductor longus aponeurosis and pubic bone pathology, but it can also evaluate other pathology within the hip and pelvis. MRI is especially helpful when groin pain is poorly localized. Real-time capability makes ultrasound useful in evaluating the pubic symphyseal region, as it can be used for evaluation and treatment. MRI and US are valuable in diagnosing pathology in athletes with groin pain, with the added utility of treatment using US-guided intervention. Strength-of Recommendation Taxonomy: C.

  14. Extraction of Lesion-Partitioned Features and Retrieval of Contrast-Enhanced Liver Images

    Mei Yu

    2012-01-01

    Full Text Available The most critical step in grayscale medical image retrieval systems is feature extraction. Understanding the interrelatedness between the characteristics of lesion images and corresponding imaging features is crucial for image training, as well as for features extraction. A feature-extraction algorithm is developed based on different imaging properties of lesions and on the discrepancy in density between the lesions and their surrounding normal liver tissues in triple-phase contrast-enhanced computed tomographic (CT scans. The algorithm includes mainly two processes: (1 distance transformation, which is used to divide the lesion into distinct regions and represents the spatial structure distribution and (2 representation using bag of visual words (BoW based on regions. The evaluation of this system based on the proposed feature extraction algorithm shows excellent retrieval results for three types of liver lesions visible on triple-phase scans CT images. The results of the proposed feature extraction algorithm show that although single-phase scans achieve the average precision of 81.9%, 80.8%, and 70.2%, dual- and triple-phase scans achieve 86.3% and 88.0%.

  15. Skull base chordoid meningioma: Imaging features and pathology

    Soo, Mark Y.S.; Gomes, Lavier; Ng, Thomas; Cruz, Malville Da; Dexter, Mark

    2004-01-01

    The clinical, imaging and pathological features of a skull base chordoid meningioma (CM) are described. The huge tumour resulted in obstructive hydrocephalus and partial erosion of the clivus such that a chordoma was suspected. The lesion's MRI findings were similar to those of a meningioma. Light microscopic, immunohistochemistry and ultrastructural features were diagnostic of CM. Chordoid meningioma is a rare subtype of meningioma and has a great tendency to recur should surgical resection be incomplete Copyright (2004) Blackwell Publishing Asia Pty Ltd

  16. Image segmentation-based robust feature extraction for color image watermarking

    Li, Mianjie; Deng, Zeyu; Yuan, Xiaochen

    2018-04-01

    This paper proposes a local digital image watermarking method based on Robust Feature Extraction. The segmentation is achieved by Simple Linear Iterative Clustering (SLIC) based on which an Image Segmentation-based Robust Feature Extraction (ISRFE) method is proposed for feature extraction. Our method can adaptively extract feature regions from the blocks segmented by SLIC. This novel method can extract the most robust feature region in every segmented image. Each feature region is decomposed into low-frequency domain and high-frequency domain by Discrete Cosine Transform (DCT). Watermark images are then embedded into the coefficients in the low-frequency domain. The Distortion-Compensated Dither Modulation (DC-DM) algorithm is chosen as the quantization method for embedding. The experimental results indicate that the method has good performance under various attacks. Furthermore, the proposed method can obtain a trade-off between high robustness and good image quality.

  17. Magnetic resonance imaging features of fibrocystic change of the breast.

    Chen, Jeon-Hor; Liu, Hui; Baek, Hyeon-Man; Nalcioglu, Orhan; Su, Min-Ying

    2008-11-01

    Studies specifically reporting MRI of fibrocystic change (FCC) of the breast are very few and its MRI features are not clearly known. The purpose of this study was to analyze the MRI features of FCC of the breast. Thirty-one patients with pathologically proven FCC of the breast were retrospectively reviewed. The MRI study was performed using a 1.5-T MR scanner with standard bilateral breast coil. The imaging protocol consisted of pre-contrast T1-weighed imaging and dynamic contrast-enhanced axial T1-weighed imaging. The MRI features were interpreted based on the morphologic and enhancement kinetic descriptors defined on ACR BIRADS-MRI lexicon. FCC of the breast had a wide spectrum of morphologic and kinetic features on MRI. Two types of FCC were found, including a more diffuse type of nonmass lesion (12/31, 39%) showing benign enhancement kinetic pattern with medium wash-in in early phase (9/10, 90%) and a focal mass-type lesion (11/31, 35%) with enhancement kinetic usually showing rapid up-slope mimicking a breast cancer (8/11, 73%). MRI is able to elaborate the diverse imaging features of FCC of the breast. Our result showed that FCC presenting as a focal mass-type lesion was usually overdiagnosed as malignancy. Understanding MRI of FCC is important to determine which cohort of patients should be followed up alone or receive aggressive management.

  18. Imaging features of maxillary osteoblastoma and its malignant transformation

    Ueno, Hiroshi; Ariji, Ei-ichiro; Tanaka, Takemasa; Kanda, Shigenobu; Mori, Shin-ichiro; Goto, Masaaki; Mizuno, Akio; Okabe, Haruo; Nakamura, Takashi

    1994-01-01

    We report two cases of osteoblastoma, one of them an unusual case in a 32-year-old woman in whom a maxillary tumor was confidently diagnosed as an osteoblastoma at the time of primary excision and subsequently transformed into an osteosarcoma 7 years after the onset of clinical symptoms. The other patient developed osteosarcoma arising in the maxilla, which was diagnosed 3 years after the primary excision and is very suggestive of malignant transformation in osteoblastoma. We present the radiological features, including computed tomographic and magnetic resonance imaging studies, of this unusual event of transformed tumor and compare imaging features of benign and dedifferentiated counterparts of this rare tumor complex. (orig.)

  19. Vaginal Masses: Magnetic Resonance Imaging Features with Pathologic Correlation

    Elsayes, K.M.; Narra, V.R.; Dillman, J.R.; Velcheti, V.; Hameed, O.; Tongdee, R.; Menias, C.O.

    2007-01-01

    The detection of vaginal lesions has increased with the expanding use of cross-sectional imaging. Magnetic resonance imaging (MRI) - with its high-contrast resolution and multiplanar capabilities - is often useful for characterizing vaginal masses. Vaginal masses can be classified as congenital, inflammatory, cystic (benign), and neoplastic (benign or malignant) in etiology. Recognition of the typical MR imaging features of such lesions is important because it often determines the treatment approach and may obviate surgery. Finally, vaginal MR imaging can be used to evaluate post-treatment changes related to previous surgery and radiation therapy. In this article, we will review pertinent vaginal anatomy, vaginal and pelvic MRI technique, and the MRI features of a variety of vaginal lesions with pathological correlation

  20. Imaging features of mycobacterium in patients with acquired immunodeficiency syndrome

    Yang Jun; Sun Yue; Wei Liangui; Xu Yunliang; Li Xingwang

    2013-01-01

    Objective: To analyze the imaging features of mycobacterium in AIDS patients. Methods: Twenty-three cases of mycobacterium tuberculosis and 13 patients of non-tuberculous mycobacteria were proved etiologically and included in this study. All patients underwent X-ray and CT examinations, imaging data were analyzed and compared. Results: The imaging findings of mycobacterium tuberculosis in AIDS patients included consolidation (n = 11), pleural effusion (n = 11), mediastinal lymphadenopathy (n = 11). Pulmonary lesions were always diffuse distribution, and 14 patients of extrapulmonary tuberculosis were found. Pulmonary lesions in non-tuberculous mycobacteria tend to be circumscribed. Conclusions: Non-tuberculous mycobacterial infection in AIDS patients is more common and usually combined with other infections. Imaging features are atypical. (authors)

  1. Hyperspectral image classifier based on beach spectral feature

    Liang, Zhang; Lianru, Gao; Bing, Zhang

    2014-01-01

    The seashore, especially coral bank, is sensitive to human activities and environmental changes. A multispectral image, with coarse spectral resolution, is inadaptable for identify subtle spectral distinctions between various beaches. To the contrary, hyperspectral image with narrow and consecutive channels increases our capability to retrieve minor spectral features which is suit for identification and classification of surface materials on the shore. Herein, this paper used airborne hyperspectral data, in addition to ground spectral data to study the beaches in Qingdao. The image data first went through image pretreatment to deal with the disturbance of noise, radiation inconsistence and distortion. In succession, the reflection spectrum, the derivative spectrum and the spectral absorption features of the beach surface were inspected in search of diagnostic features. Hence, spectra indices specific for the unique environment of seashore were developed. According to expert decisions based on image spectrums, the beaches are ultimately classified into sand beach, rock beach, vegetation beach, mud beach, bare land and water. In situ surveying reflection spectrum from GER1500 field spectrometer validated the classification production. In conclusion, the classification approach under expert decision based on feature spectrum is proved to be feasible for beaches

  2. [Diagnostic imaging of high-grade astrocytoma: heterogeneity of clinical manifestation, image characteristics, and histopathological findings].

    Okajima, Kaoru; Ohta, Yoshio

    2012-10-01

    Recent developments in diagnostic radiology, which have enabled accurate differential diagnoses of brain tumors, have been well described in the last three decades. MR and PET imaging can also provide information to predict histological grades and prognoses that might influence treatment strategies. However, high-grade astrocytomas consist of many different subtypes that are associated with different imaging and histological characteristics. Hemorrhage and necrosis results in a variety of imaging features, and infiltrative tumor growth entrapping normal neurons may cause different clinical manifestations. We reviewed patients with high-grade astrocytomas that showed various imaging characteristics, with special emphasis on initial symptoms and histological features. Clinicopathological characteristics of astrocytomas were also compared with other malignant tumors. Neurological deficits were not notable in patients with grade 3-4 astrocytomas when they showed infiltrative tumor growth, while brain metastases with compact cellular proliferation caused more neurological symptoms. Infiltrative tumors did not show any enhancing masses on MR imaging, but these tumors may show intratumor heterogeneity. Seizures were reported to be more frequent in low-grade glioma and in secondary glioblastoma. Tumor heterogeneity was also reported in molecular genetic profile, and investigators identified some subsets of astrocytomas. They investigated IHD1/2 mutation, EGFR amplification, TP53 mutation, Ki-67 index, etc. In summary, high-grade astrocytomas are not homogenous groups of tumors, and this is associated with the heterogeneity of clinical manifestation, image characteristics, and histopathological findings. Molecular studies may explain the tumor heterogeneity in the near future.

  3. Modality prediction of biomedical literature images using multimodal feature representation

    Pelka, Obioma

    2016-08-01

    Full Text Available This paper presents the modelling approaches performed to automatically predict the modality of images found in biomedical literature. Various state-of-the-art visual features such as Bag-of-Keypoints computed with dense SIFT descriptors, texture features and Joint Composite Descriptors were used for visual image representation. Text representation was obtained by vector quantisation on a Bag-of-Words dictionary generated using attribute importance derived from a χ-test. Computing the principal components separately on each feature, dimension reduction as well as computational load reduction was achieved. Various multiple feature fusions were adopted to supplement visual image information with corresponding text information. The improvement obtained when using multimodal features vs. visual or text features was detected, analysed and evaluated. Random Forest models with 100 to 500 deep trees grown by resampling, a multi class linear kernel SVM with C=0.05 and a late fusion of the two classifiers were used for modality prediction. A Random Forest classifier achieved a higher accuracy and computed Bag-of-Keypoints with dense SIFT descriptors proved to be a better approach than with Lowe SIFT.

  4. Image cytometric nuclear texture features in inoperable head and neck cancer: a pilot study

    Strojan-Flezar, Margareta; Lavrencak, Jaka; Zganec, Mario; Strojan, Primoz

    2011-01-01

    Image cytometry can measure numerous nuclear features which could be considered a surrogate end-point marker of molecular genetic changes in a nucleus. The aim of the study was to analyze image cytometric nuclear features in paired samples of primary tumor and neck metastasis in patients with inoperable carcinoma of the head and neck. Image cytometric analysis of cell suspensions prepared from primary tumor tissue and fine needle aspiration biopsy cell samples of neck metastases from 21 patients treated with concomitant radiochemotherapy was performed. Nuclear features were correlated with clinical characteristics and response to therapy. Manifestation of distant metastases and new primaries was associated (p<0.05) with several chromatin characteristics from primary tumor cells, whereas the origin of index cancer and disease response in the neck was related to those in the cells from metastases. Many nuclear features of primary tumors and metastases correlated with the TNM stage. A specific pattern of correlation between well-established prognostic indicators and nuclear features of samples from primary tumors and those from neck metastases was observed. Image cytometric nuclear features represent a promising candidate marker for recognition of biologically different tumor subgroups

  5. Intracranial Infections: Clinical and Imaging Characteristics

    Foerster, B.R.; Thurnher, M.M.; Malani, P.N.; Petrou, M.; Carets-Zumelzu, F.; Sundgren, P.C. [Dept. of Radiology, and Divisions of Infectious Diseases and G eriatric Medicine, Dept. of Internal Medicine, Univ. of Michigan Medical Center, Ann Arbor, MI (United States)

    2007-10-15

    The radiologist plays a crucial role in identifying and narrowing the differential diagnosis of intracranial infections. A thorough understanding of the intracranial compartment anatomy and characteristic imaging findings of specific pathogens, as well incorporation of the clinical information, is essential to establish correct diagnosis. Specific types of infections have certain propensities for different anatomical regions within the brain. In addition, the imaging findings must be placed in the context of the clinical setting, particularly in immunocompromised and human immunodeficiency virus (HIV)-positive patients. This paper describes and depicts infections within the different compartments of the brain. Pathology-proven infectious cases are presented in both immunocompetent and immunocompromised patients, with a discussion of the characteristic findings of each pathogen. Magnetic resonance spectroscopy (MRS) characteristics for several infections are also discussed.

  6. The fuzzy Hough Transform-feature extraction in medical images

    Philip, K.P.; Dove, E.L.; Stanford, W.; Chandran, K.B.; McPherson, D.D.; Gotteiner, N.L.

    1994-01-01

    Identification of anatomical features is a necessary step for medical image analysis. Automatic methods for feature identification using conventional pattern recognition techniques typically classify an object as a member of a predefined class of objects, but do not attempt to recover the exact or approximate shape of that object. For this reason, such techniques are usually not sufficient to identify the borders of organs when individual geometry varies in local detail, even though the general geometrical shape is similar. The authors present an algorithm that detects features in an image based on approximate geometrical models. The algorithm is based on the traditional and generalized Hough Transforms but includes notions from fuzzy set theory. The authors use the new algorithm to roughly estimate the actual locations of boundaries of an internal organ, and from this estimate, to determine a region of interest around the organ. Based on this rough estimate of the border location, and the derived region of interest, the authors find the final estimate of the true borders with other image processing techniques. The authors present results that demonstrate that the algorithm was successfully used to estimate the approximate location of the chest wall in humans, and of the left ventricular contours of a dog heart obtained from cine-computed tomographic images. The authors use this fuzzy Hough Transform algorithm as part of a larger procedures to automatically identify the myocardial contours of the heart. This algorithm may also allow for more rapid image processing and clinical decision making in other medical imaging applications

  7. Deformable Image Registration with Inclusion of Autodetected Homologous Tissue Features

    Qingsong Zhu

    2012-01-01

    Full Text Available A novel deformable registration algorithm is proposed in the application of radiation therapy. The algorithm starts with autodetection of a number of points with distinct tissue features. The feature points are then matched by using the scale invariance features transform (SIFT method. The associated feature point pairs are served as landmarks for the subsequent thin plate spline (TPS interpolation. Several registration experiments using both digital phantom and clinical data demonstrate the accuracy and efficiency of the method. For the 3D phantom case, markers with error less than 2 mm are over 85% of total test markers, and it takes only 2-3 minutes for 3D feature points association. The proposed method provides a clinically practical solution and should be valuable for various image-guided radiation therapy (IGRT applications.

  8. Investigation of efficient features for image recognition by neural networks.

    Goltsev, Alexander; Gritsenko, Vladimir

    2012-04-01

    In the paper, effective and simple features for image recognition (named LiRA-features) are investigated in the task of handwritten digit recognition. Two neural network classifiers are considered-a modified 3-layer perceptron LiRA and a modular assembly neural network. A method of feature selection is proposed that analyses connection weights formed in the preliminary learning process of a neural network classifier. In the experiments using the MNIST database of handwritten digits, the feature selection procedure allows reduction of feature number (from 60 000 to 7000) preserving comparable recognition capability while accelerating computations. Experimental comparison between the LiRA perceptron and the modular assembly neural network is accomplished, which shows that recognition capability of the modular assembly neural network is somewhat better. Copyright © 2011 Elsevier Ltd. All rights reserved.

  9. A comparative study of image low level feature extraction algorithms

    M.M. El-gayar

    2013-07-01

    Full Text Available Feature extraction and matching is at the base of many computer vision problems, such as object recognition or structure from motion. Current methods for assessing the performance of popular image matching algorithms are presented and rely on costly descriptors for detection and matching. Specifically, the method assesses the type of images under which each of the algorithms reviewed herein perform to its maximum or highest efficiency. The efficiency is measured in terms of the number of matches founds by the algorithm and the number of type I and type II errors encountered when the algorithm is tested against a specific pair of images. Current comparative studies asses the performance of the algorithms based on the results obtained in different criteria such as speed, sensitivity, occlusion, and others. This study addresses the limitations of the existing comparative tools and delivers a generalized criterion to determine beforehand the level of efficiency expected from a matching algorithm given the type of images evaluated. The algorithms and the respective images used within this work are divided into two groups: feature-based and texture-based. And from this broad classification only three of the most widely used algorithms are assessed: color histogram, FAST (Features from Accelerated Segment Test, SIFT (Scale Invariant Feature Transform, PCA-SIFT (Principal Component Analysis-SIFT, F-SIFT (fast-SIFT and SURF (speeded up robust features. The performance of the Fast-SIFT (F-SIFT feature detection methods are compared for scale changes, rotation, blur, illumination changes and affine transformations. All the experiments use repeatability measurement and the number of correct matches for the evaluation measurements. SIFT presents its stability in most situations although its slow. F-SIFT is the fastest one with good performance as the same as SURF, SIFT, PCA-SIFT show its advantages in rotation and illumination changes.

  10. Magnetic resonance imaging features of extremity sarcomas of uncertain differentiation

    Stacy, G.S.; Nair, L.

    2007-01-01

    The purpose of this review is to illustrate the pertinent clinical and imaging features of extremity sarcomas of uncertain differentiation, including synovial sarcoma, epithelioid sarcoma, clear-cell sarcoma, and alveolar soft part sarcoma. These tumours should be considered in the differential diagnosis when a soft-tissue mass is encountered in the extremity of an adolescent or young adult

  11. Tracking image features with PCA-SURF descriptors

    Pancham, A

    2015-05-01

    Full Text Available IAPR International Conference on Machine Vision Applications, May 18-22, 2015, Tokyo, JAPAN Tracking Image Features with PCA-SURF Descriptors Ardhisha Pancham CSIR, UKZN South Africa apancham@csir.co.za Daniel Withey CSIR South Africa...

  12. Headache Characteristics and Clinical Features of Elderly Migraine Patients.

    de Rijk, Pablo; Resseguier, Noémie; Donnet, Anne

    2018-04-01

    To investigate the headache characteristics and clinical features of elderly migraine patients at a tertiary headache center. We retrospectively reviewed 239 records of migraine patients, over the age of 64 at the first visit, who had migraine as defined by the International Classification of Headache Disorders 3rd edition (beta version) from 2006 to 2015 based on the Marseille registry at Timone Hospital. 13.8% (33/239) patients had migraine with aura only, 13.0% (31/239) had both diagnoses. Of the patients who presented with migraine with aura, 13.4% (32/239) presented with aura without headache. Unilateral pain location was reported by 58.6% (140/239) of patients and the throbbing type of pain was present in 50.2% (120/239) of our study group. Photo- and phonophobia were observed in 77.4% (185/239) and 79.5% (190/239) of patients. Seventy-nine out of 239 (30.1%) patients were found to have probable medication overuse. Within this group, 31.65% (25/79) overused triptan and 70.9% (56/79) overused combination analgesics. We found higher frequencies of migraine for patients whose age at onset of migraine was younger than 18 years, and low frequency migraine was reported more frequently in the later onset group (P = .0357). We assess the headache characteristics of elderly migraine patients who were seen at our tertiary headache center and report the high frequency of probable medication overuse headache in this study group. Finally, we suggest that age of onset is an important factor in the clinical profile of these patients. © 2017 American Headache Society.

  13. Imaging features of multicentric Castleman's disease in HIV infection

    Hillier, J.C.; Shaw, P.; Miller, R.F.; Cartledge, J.D.; Nelson, M.; Bower, M.; Francis, N.; Padley, S.P.

    2004-01-01

    AIM: To describe the computed tomography (CT) features of human immunodeficiency virus (HIV)-associated Castleman's disease. MATERIALS AND METHODS: Nine HIV-positive patients with biopsy-proven Castleman's disease were studied. Clinical and demographic data, CD4 count, histological diagnosis and human herpes type 8 (HHV8) serology or immunostaining results were recorded. CT images were reviewed independently by two radiologists. RESULTS: CT findings included splenomegaly (n=7) and peripheral lymph node enlargement (axillary n=8, inguinal n=4). All nodes displayed mild to avid enhancement after intravenous administration of contrast material. Hepatomegaly was evident in seven patients. Other features included abdominal (n=6) and mediastinal (n=5) lymph node enlargement and pulmonary abnormalities (n=4). Patterns of parenchymal abnormality included bronchovascular nodularity (n=2), consolidation (n=1) and pleural effusion (n=2). On histological examination eight patients (spleen n=3, lymph node n=9, lung n=1 bone marrow n=1) had the plasma cell variant and one had mixed hyaline-vascular/plasma cell variant. The majority had either positive immunostaining for HHV8 or positive serology (n=8). CONCLUSION: Common imaging features of multicentric Castleman's disease in HIV infection are hepatosplenomegaly and peripheral lymph node enlargement. Although these imaging features may suggest the diagnosis in the appropriate clinical context, they lack specificity and so biopsy is needed for diagnosis. In distinction from multicentric Castleman's disease in other populations the plasma cell variant is most commonly encountered, splenomegaly is a universal feature and there is a strong association with Kaposi's sarcoma

  14. An effective image classification method with the fusion of invariant feature and a new color descriptor

    Mansourian, Leila; Taufik Abdullah, Muhamad; Nurliyana Abdullah, Lili; Azman, Azreen; Mustaffa, Mas Rina

    2017-02-01

    Pyramid Histogram of Words (PHOW), combined Bag of Visual Words (BoVW) with the spatial pyramid matching (SPM) in order to add location information to extracted features. However, different PHOW extracted from various color spaces, and they did not extract color information individually, that means they discard color information, which is an important characteristic of any image that is motivated by human vision. This article, concatenated PHOW Multi-Scale Dense Scale Invariant Feature Transform (MSDSIFT) histogram and a proposed Color histogram to improve the performance of existing image classification algorithms. Performance evaluation on several datasets proves that the new approach outperforms other existing, state-of-the-art methods.

  15. Adaptive Colour Feature Identification in Image for Object Tracking

    Feng Su

    2012-01-01

    Full Text Available Identification and tracking of a moving object using computer vision techniques is important in robotic surveillance. In this paper, an adaptive colour filtering method is introduced for identifying and tracking a moving object appearing in image sequences. This filter is capable of automatically identifying the most salient colour feature of the moving object in the image and using this for a robot to track the object. The method enables the selected colour feature to adapt to surrounding condition when it is changed. A method of determining the region of interest of the moving target is also developed for the adaptive colour filter to extract colour information. Experimental results show that by using a camera mounted on a robot, the proposed methods can perform robustly in tracking a randomly moving object using adaptively selected colour features in a crowded environment.

  16. Feature extraction from mammographic images using fast marching methods

    Bottigli, U.; Golosio, B.

    2002-01-01

    Features extraction from medical images represents a fundamental step for shape recognition and diagnostic support. The present work faces the problem of the detection of large features, such as massive lesions and organ contours, from mammographic images. The regions of interest are often characterized by an average grayness intensity that is different from the surrounding. In most cases, however, the desired features cannot be extracted by simple gray level thresholding, because of image noise and non-uniform density of the surrounding tissue. In this work, edge detection is achieved through the fast marching method (Level Set Methods and Fast Marching Methods, Cambridge University Press, Cambridge, 1999), which is based on the theory of interface evolution. Starting from a seed point in the shape of interest, a front is generated which evolves according to an appropriate speed function. Such function is expressed in terms of geometric properties of the evolving interface and of image properties, and should become zero when the front reaches the desired boundary. Some examples of application of such method to mammographic images from the CALMA database (Nucl. Instr. and Meth. A 460 (2001) 107) are presented here and discussed

  17. THE EFFECT OF IMAGE ENHANCEMENT METHODS DURING FEATURE DETECTION AND MATCHING OF THERMAL IMAGES

    O. Akcay

    2017-05-01

    Full Text Available A successful image matching is essential to provide an automatic photogrammetric process accurately. Feature detection, extraction and matching algorithms have performed on the high resolution images perfectly. However, images of cameras, which are equipped with low-resolution thermal sensors are problematic with the current algorithms. In this paper, some digital image processing techniques were applied to the low-resolution images taken with Optris PI 450 382 x 288 pixel optical resolution lightweight thermal camera to increase extraction and matching performance. Image enhancement methods that adjust low quality digital thermal images, were used to produce more suitable images for detection and extraction. Three main digital image process techniques: histogram equalization, high pass and low pass filters were considered to increase the signal-to-noise ratio, sharpen image, remove noise, respectively. Later on, the pre-processed images were evaluated using current image detection and feature extraction methods Maximally Stable Extremal Regions (MSER and Speeded Up Robust Features (SURF algorithms. Obtained results showed that some enhancement methods increased number of extracted features and decreased blunder errors during image matching. Consequently, the effects of different pre-process techniques were compared in the paper.

  18. Feature Tracking for High Speed AFM Imaging of Biopolymers.

    Hartman, Brett; Andersson, Sean B

    2018-03-31

    The scanning speed of atomic force microscopes continues to advance with some current commercial microscopes achieving on the order of one frame per second and at least one reaching 10 frames per second. Despite the success of these instruments, even higher frame rates are needed with scan ranges larger than are currently achievable. Moreover, there is a significant installed base of slower instruments that would benefit from algorithmic approaches to increasing their frame rate without requiring significant hardware modifications. In this paper, we present an experimental demonstration of high speed scanning on an existing, non-high speed instrument, through the use of a feedback-based, feature-tracking algorithm that reduces imaging time by focusing on features of interest to reduce the total imaging area. Experiments on both circular and square gratings, as well as silicon steps and DNA strands show a reduction in imaging time by a factor of 3-12 over raster scanning, depending on the parameters chosen.

  19. Robust and efficient method for matching features in omnidirectional images

    Zhu, Qinyi; Zhang, Zhijiang; Zeng, Dan

    2018-04-01

    Binary descriptors have been widely used in many real-time applications due to their efficiency. These descriptors are commonly designed for perspective images but perform poorly on omnidirectional images, which are severely distorted. To address this issue, this paper proposes tangent plane BRIEF (TPBRIEF) and adapted log polar grid-based motion statistics (ALPGMS). TPBRIEF projects keypoints to a unit sphere and applies the fixed test set in BRIEF descriptor on the tangent plane of the unit sphere. The fixed test set is then backprojected onto the original distorted images to construct the distortion invariant descriptor. TPBRIEF directly enables keypoint detecting and feature describing on original distorted images, whereas other approaches correct the distortion through image resampling, which introduces artifacts and adds time cost. With ALPGMS, omnidirectional images are divided into circular arches named adapted log polar grids. Whether a match is true or false is then determined by simply thresholding the match numbers in a grid pair where the two matched points located. Experiments show that TPBRIEF greatly improves the feature matching accuracy and ALPGMS robustly removes wrong matches. Our proposed method outperforms the state-of-the-art methods.

  20. Magnetic resonance imaging characteristics of fibrocystic change of the breast.

    van den Bosch, Maurice A A J; Daniel, Bruce L; Mariano, Michelle N; Nowels, Kent N; Birdwell, Robyn L; Fong, Kathy J; Desmond, Pam S; Plevritis, Sylvia; Stables, Lara A; Zakhour, Marowan; Herfkens, Robert J; Ikeda, Debra M

    2005-07-01

    The objective of this study was to identify magnetic resonance imaging (MRI) characteristics of fibrocystic change (FCC) of the breast. Fourteen patients with a histopathologic diagnosis of solitary FCC of the breast underwent x-ray mammography and MRI of the breast. Three experienced breast imaging radiologists retrospectively reviewed the MRI findings and categorized the lesions on morphologic and kinetic criteria according to the ACR BI-RADS-MRI Lexicon. The most striking morphologic feature of fibrocystic change was nonmass-like regional enhancement found in 6 of 14 (43%) FCC lesions. Based on morphologic criteria alone, 12 of 14 (86%) lesions were correctly classified as benign. According to analysis of the time-intensity curves, 10 of 14 (71%) FCC lesions were correctly classified as benign. Although FCC has a wide spectrum of morphologic and kinetic features on MRI, it most often presents as a mass or a nonmass-like regional enhancing lesion with benign enhancement kinetics.

  1. Computer-aided breast MR image feature analysis for prediction of tumor response to chemotherapy

    Aghaei, Faranak; Tan, Maxine; Liu, Hong; Zheng, Bin; Hollingsworth, Alan B.; Qian, Wei

    2015-01-01

    Purpose: To identify a new clinical marker based on quantitative kinetic image features analysis and assess its feasibility to predict tumor response to neoadjuvant chemotherapy. Methods: The authors assembled a dataset involving breast MR images acquired from 68 cancer patients before undergoing neoadjuvant chemotherapy. Among them, 25 patients had complete response (CR) and 43 had partial and nonresponse (NR) to chemotherapy based on the response evaluation criteria in solid tumors. The authors developed a computer-aided detection scheme to segment breast areas and tumors depicted on the breast MR images and computed a total of 39 kinetic image features from both tumor and background parenchymal enhancement regions. The authors then applied and tested two approaches to classify between CR and NR cases. The first one analyzed each individual feature and applied a simple feature fusion method that combines classification results from multiple features. The second approach tested an attribute selected classifier that integrates an artificial neural network (ANN) with a wrapper subset evaluator, which was optimized using a leave-one-case-out validation method. Results: In the pool of 39 features, 10 yielded relatively higher classification performance with the areas under receiver operating characteristic curves (AUCs) ranging from 0.61 to 0.78 to classify between CR and NR cases. Using a feature fusion method, the maximum AUC = 0.85 ± 0.05. Using the ANN-based classifier, AUC value significantly increased to 0.96 ± 0.03 (p < 0.01). Conclusions: This study demonstrated that quantitative analysis of kinetic image features computed from breast MR images acquired prechemotherapy has potential to generate a useful clinical marker in predicting tumor response to chemotherapy

  2. Computer-aided breast MR image feature analysis for prediction of tumor response to chemotherapy

    Aghaei, Faranak; Tan, Maxine; Liu, Hong; Zheng, Bin, E-mail: Bin.Zheng-1@ou.edu [School of Electrical and Computer Engineering, University of Oklahoma, Norman, Oklahoma 73019 (United States); Hollingsworth, Alan B. [Mercy Women’s Center, Mercy Health Center, Oklahoma City, Oklahoma 73120 (United States); Qian, Wei [Department of Electrical and Computer Engineering, University of Texas, El Paso, Texas 79968 (United States)

    2015-11-15

    Purpose: To identify a new clinical marker based on quantitative kinetic image features analysis and assess its feasibility to predict tumor response to neoadjuvant chemotherapy. Methods: The authors assembled a dataset involving breast MR images acquired from 68 cancer patients before undergoing neoadjuvant chemotherapy. Among them, 25 patients had complete response (CR) and 43 had partial and nonresponse (NR) to chemotherapy based on the response evaluation criteria in solid tumors. The authors developed a computer-aided detection scheme to segment breast areas and tumors depicted on the breast MR images and computed a total of 39 kinetic image features from both tumor and background parenchymal enhancement regions. The authors then applied and tested two approaches to classify between CR and NR cases. The first one analyzed each individual feature and applied a simple feature fusion method that combines classification results from multiple features. The second approach tested an attribute selected classifier that integrates an artificial neural network (ANN) with a wrapper subset evaluator, which was optimized using a leave-one-case-out validation method. Results: In the pool of 39 features, 10 yielded relatively higher classification performance with the areas under receiver operating characteristic curves (AUCs) ranging from 0.61 to 0.78 to classify between CR and NR cases. Using a feature fusion method, the maximum AUC = 0.85 ± 0.05. Using the ANN-based classifier, AUC value significantly increased to 0.96 ± 0.03 (p < 0.01). Conclusions: This study demonstrated that quantitative analysis of kinetic image features computed from breast MR images acquired prechemotherapy has potential to generate a useful clinical marker in predicting tumor response to chemotherapy.

  3. Estimating perception of scene layout properties from global image features.

    Ross, Michael G; Oliva, Aude

    2010-01-08

    The relationship between image features and scene structure is central to the study of human visual perception and computer vision, but many of the specifics of real-world layout perception remain unknown. We do not know which image features are relevant to perceiving layout properties, or whether those features provide the same information for every type of image. Furthermore, we do not know the spatial resolutions required for perceiving different properties. This paper describes an experiment and a computational model that provides new insights on these issues. Humans perceive the global spatial layout properties such as dominant depth, openness, and perspective, from a single image. This work describes an algorithm that reliably predicts human layout judgments. This model's predictions are general, not specific to the observers it trained on. Analysis reveals that the optimal spatial resolutions for determining layout vary with the content of the space and the property being estimated. Openness is best estimated at high resolution, depth is best estimated at medium resolution, and perspective is best estimated at low resolution. Given the reliability and simplicity of estimating the global layout of real-world environments, this model could help resolve perceptual ambiguities encountered by more detailed scene reconstruction schemas.

  4. Central nervous system lymphoma: magnetic resonance imaging features at presentation

    Ricardo Schwingel

    2012-02-01

    Full Text Available OBJECTIVE: This paper aimed at studying presentations of the central nervous system (CNS lymphoma using structural images obtained by magnetic resonance imaging (MRI. METHODS: The MRI features at presentation of 15 patients diagnosed with CNS lymphoma in a university hospital, between January 1999 and March 2011, were analyzed by frequency and cross tabulation. RESULTS: All patients had supratentorial lesions; and four had infra- and supratentorial lesions. The signal intensity on T1 and T2 weighted images was predominantly hypo- or isointense. In the T2 weighted images, single lesions were associated with a hypointense signal component. Six patients presented necrosis, all of them showed perilesional abnormal white matter, nine had meningeal involvement, and five had subependymal spread. Subependymal spread and meningeal involvement tended to occur in younger patients. CONCLUSION: Presentations of lymphoma are very pleomorphic, but some of them should point to this diagnostic possibility.

  5. Clinical Features and Patterns of Imaging in Cerebral Venous Sinus ...

    Background: Cerebral venous sinus thrombosis (CVST) is an uncommon neurological deficit. It shows a wide range of clinical manifestations that may mimic many other neurological disorders and lead to misdiagnosis. Imaging plays a key role in the diagnosis. Objective: To evaluate the clinical characteristics and patterns ...

  6. Shear-wave elastographic features of breast cancers: comparison with mechanical elasticity and histopathologic characteristics.

    Lee, Su Hyun; Moon, Woo Kyung; Cho, Nariya; Chang, Jung Min; Moon, Hyeong-Gon; Han, Wonshik; Noh, Dong-Young; Lee, Jung Chan; Kim, Hee Chan; Lee, Kyoung-Bun; Park, In-Ae

    2014-03-01

    The objective of this study was to compare the quantitative and qualitative shear-wave elastographic (SWE) features of breast cancers with mechanical elasticity and histopathologic characteristics. This prospective study was conducted with institutional review board approval, and written informed consent was obtained. Shear-wave elastography was performed for 30 invasive breast cancers in 30 women before surgery. The mechanical elasticity of a fresh breast tissue section, correlated with the ultrasound image, was measured using an indentation system. Quantitative (maximum, mean, minimum, and standard deviation of elasticity in kilopascals) and qualitative (color heterogeneity and presence of signal void areas in the mass) SWE features were compared with mechanical elasticity and histopathologic characteristics using the Pearson correlation coefficient and the Wilcoxon signed rank test. Maximum SWE values showed a moderate correlation with maximum mechanical elasticity (r = 0.530, P = 0.003). There were no significant differences between SWE values and mechanical elasticity in histologic grade I or II cancers (P = 0.268). However, SWE values were significantly higher than mechanical elasticity in histologic grade III cancers (P masses were present in 43% of breast cancers (13 of 30) and were correlated with dense collagen depositions (n = 11) or intratumoral necrosis (n = 2). Quantitative and qualitative SWE features reflect both the mechanical elasticity and histopathologic characteristics of breast cancers.

  7. Feature Extraction and Classification on Esophageal X-Ray Images of Xinjiang Kazak Nationality

    Fang Yang

    2017-01-01

    Full Text Available Esophageal cancer is one of the fastest rising types of cancers in China. The Kazak nationality is the highest-risk group in Xinjiang. In this work, an effective computer-aided diagnostic system is developed to assist physicians in interpreting digital X-ray image features and improving the quality of diagnosis. The modules of the proposed system include image preprocessing, feature extraction, feature selection, image classification, and performance evaluation. 300 original esophageal X-ray images were resized to a region of interest and then enhanced by the median filter and histogram equalization method. 37 features from textural, frequency, and complexity domains were extracted. Both sequential forward selection and principal component analysis methods were employed to select the discriminative features for classification. Then, support vector machine and K-nearest neighbors were applied to classify the esophageal cancer images with respect to their specific types. The classification performance was evaluated in terms of the area under the receiver operating characteristic curve, accuracy, precision, and recall, respectively. Experimental results show that the classification performance of the proposed system outperforms the conventional visual inspection approaches in terms of diagnostic quality and processing time. Therefore, the proposed computer-aided diagnostic system is promising for the diagnostics of esophageal cancer.

  8. Learning with distribution of optimized features for recognizing common CT imaging signs of lung diseases

    Ma, Ling; Liu, Xiabi; Fei, Baowei

    2017-01-01

    Common CT imaging signs of lung diseases (CISLs) are defined as the imaging signs that frequently appear in lung CT images from patients. CISLs play important roles in the diagnosis of lung diseases. This paper proposes a novel learning method, namely learning with distribution of optimized feature (DOF), to effectively recognize the characteristics of CISLs. We improve the classification performance by learning the optimized features under different distributions. Specifically, we adopt the minimum spanning tree algorithm to capture the relationship between features and discriminant ability of features for selecting the most important features. To overcome the problem of various distributions in one CISL, we propose a hierarchical learning method. First, we use an unsupervised learning method to cluster samples into groups based on their distribution. Second, in each group, we use a supervised learning method to train a model based on their categories of CISLs. Finally, we obtain multiple classification decisions from multiple trained models and use majority voting to achieve the final decision. The proposed approach has been implemented on a set of 511 samples captured from human lung CT images and achieves a classification accuracy of 91.96%. The proposed DOF method is effective and can provide a useful tool for computer-aided diagnosis of lung diseases on CT images.

  9. FRACTAL IMAGE FEATURE VECTORS WITH APPLICATIONS IN FRACTOGRAPHY

    Hynek Lauschmann

    2011-05-01

    Full Text Available The morphology of fatigue fracture surface (caused by constant cycle loading is strictly related to crack growth rate. This relation may be expressed, among other methods, by means of fractal analysis. Fractal dimension as a single numerical value is not sufficient. Two types of fractal feature vectors are discussed: multifractal and multiparametric. For analysis of images, the box-counting method for 3D is applied with respect to the non-homogeneity of dimensions (two in space, one in brightness. Examples of application are shown: images of several fracture surfaces are analyzed and related to crack growth rate.

  10. Primary Neuroendocrine Tumor of the Breast: Imaging Features

    Chang, Eun Deok; Kim, Min Kyun; Kim, Jeong Soo; Whang, In Yong

    2013-01-01

    Focal neuroendocrine differentiation can be found in diverse histological types of breast tumors. However, the term, neuroendocrine breast tumor, indicates the diffuse expression of neuroendocrine markers in more than 50% of the tumor cell population. The imaging features of neuroendocrine breast tumor have not been accurately described due to extreme rarity of this tumor type. We present a case of a pathologically confirmed, primary neuroendocrine breast tumor in a 42-year-old woman, with imaging findings difficult to be differentiated from that of invasive ductal carcinoma

  11. Color Texture Image Retrieval Based on Local Extrema Features and Riemannian Distance

    Minh-Tan Pham

    2017-10-01

    Full Text Available A novel efficient method for content-based image retrieval (CBIR is developed in this paper using both texture and color features. Our motivation is to represent and characterize an input image by a set of local descriptors extracted from characteristic points (i.e., keypoints within the image. Then, dissimilarity measure between images is calculated based on the geometric distance between the topological feature spaces (i.e., manifolds formed by the sets of local descriptors generated from each image of the database. In this work, we propose to extract and use the local extrema pixels as our feature points. Then, the so-called local extrema-based descriptor (LED is generated for each keypoint by integrating all color, spatial as well as gradient information captured by its nearest local extrema. Hence, each image is encoded by an LED feature point cloud and Riemannian distances between these point clouds enable us to tackle CBIR. Experiments performed on several color texture databases including Vistex, STex, color Brodazt, USPtex and Outex TC-00013 using the proposed approach provide very efficient and competitive results compared to the state-of-the-art methods.

  12. Effect of zooming on texture features of ultrasonic images

    Kyriacou Efthyvoulos

    2006-01-01

    Full Text Available Abstract Background Unstable carotid plaques on subjective, visual, assessment using B-mode ultrasound scanning appear as echolucent and heterogeneous. Although previous studies on computer assisted plaque characterisation have standardised B-mode images for brightness, improving the objective assessment of echolucency, little progress has been made towards standardisation of texture analysis methods, which assess plaque heterogeneity. The aim of the present study was to investigate the influence of image zooming during ultrasound scanning on textural features and to test whether or not resolution standardisation decreases the variability introduced. Methods Eighteen still B-mode images of carotid plaques were zoomed during carotid scanning (zoom factor 1.3 and both images were transferred to a PC and normalised. Using bilinear and bicubic interpolation, the original images were interpolated in a process of simulating off-line zoom using the same interpolation factor. With the aid of the colour-coded image, carotid plaques of the original, zoomed and two resampled images for each case were outlined and histogram, first order and second order statistics were subsequently calculated. Results Most second order statistics (21/25, 84% were significantly (p Conclusion Texture analysis of ultrasonic plaques should be performed under standardised resolution settings; otherwise a resolution normalisation algorithm should be applied.

  13. MR imaging features of peritoneal adenomatoid mesothelioma: a case report

    Lins, Cynthia Maria Coelho; Elias Junior, Jorge; Muglia, Valdair Francisco; Monteiro, Carlos Ribeiro; Feres, Omar

    2009-01-01

    Adenomatoid mesothelioma of the peritoneum (AMP) is a rare benign tumor originating from mesothelial cells.1 Most frequently, AMP occurs between 26 and 55 years of age, at a mean age of 41 years. In contrast to diffuse malignant mesothelioma, which has been linked to asbestos exposure, the etiology of AMP has not been established. Only a minority of patients have symptoms related to the tumor. AMP may present local recurrence, but it has no potential for malignant transformation. Although there are many case reports of abdominal mesotheliomas, to date, there have been no reports of MR imaging features of AMP. In this article, we present the MR imaging features of a case of AMP with histopathological correlation. (author)

  14. MR imaging features of peritoneal adenomatoid mesothelioma: a case report

    Lins, Cynthia Maria Coelho; Elias Junior, Jorge; Muglia, Valdair Francisco; Monteiro, Carlos Ribeiro [University of Sao Paulo (USP), Ribeirao Preto, SP (Brazil). School of Medicine. Dept. of Internal Medicine], e-mail: jejunior@fmrp.usp.br; Cunha, Adilson Ferreira [School of Medicine of Sao Jose do Rio Preto (FAMERP), SP (Brazil). Dept. of Gynecology and Obstetrics; Valeri, Fabio V. [Victorio Valeri Institute of Medical Diagnosis, Ribeirao Preto, SP (Brazil); Feres, Omar [University of Sao Paulo (USP), Ribeirao Preto, SP (Brazil). School of Medicine. Dept. of Surgery and Anatomy

    2009-07-01

    Adenomatoid mesothelioma of the peritoneum (AMP) is a rare benign tumor originating from mesothelial cells.1 Most frequently, AMP occurs between 26 and 55 years of age, at a mean age of 41 years. In contrast to diffuse malignant mesothelioma, which has been linked to asbestos exposure, the etiology of AMP has not been established. Only a minority of patients have symptoms related to the tumor. AMP may present local recurrence, but it has no potential for malignant transformation. Although there are many case reports of abdominal mesotheliomas, to date, there have been no reports of MR imaging features of AMP. In this article, we present the MR imaging features of a case of AMP with histopathological correlation. (author)

  15. Automatic plankton image classification combining multiple view features via multiple kernel learning.

    Zheng, Haiyong; Wang, Ruchen; Yu, Zhibin; Wang, Nan; Gu, Zhaorui; Zheng, Bing

    2017-12-28

    Plankton, including phytoplankton and zooplankton, are the main source of food for organisms in the ocean and form the base of marine food chain. As the fundamental components of marine ecosystems, plankton is very sensitive to environment changes, and the study of plankton abundance and distribution is crucial, in order to understand environment changes and protect marine ecosystems. This study was carried out to develop an extensive applicable plankton classification system with high accuracy for the increasing number of various imaging devices. Literature shows that most plankton image classification systems were limited to only one specific imaging device and a relatively narrow taxonomic scope. The real practical system for automatic plankton classification is even non-existent and this study is partly to fill this gap. Inspired by the analysis of literature and development of technology, we focused on the requirements of practical application and proposed an automatic system for plankton image classification combining multiple view features via multiple kernel learning (MKL). For one thing, in order to describe the biomorphic characteristics of plankton more completely and comprehensively, we combined general features with robust features, especially by adding features like Inner-Distance Shape Context for morphological representation. For another, we divided all the features into different types from multiple views and feed them to multiple classifiers instead of only one by combining different kernel matrices computed from different types of features optimally via multiple kernel learning. Moreover, we also applied feature selection method to choose the optimal feature subsets from redundant features for satisfying different datasets from different imaging devices. We implemented our proposed classification system on three different datasets across more than 20 categories from phytoplankton to zooplankton. The experimental results validated that our system

  16. Genetic algorithms for thyroid gland ultrasound image feature reduction

    Tesař, Ludvík; Smutek, D.; Jiskra, J.

    2005-01-01

    Roč. 3612, č. - (2005), s. 841-844 ISSN 0302-9743. [International Conference ICNC 2005 /1./. Changsha, 27.08.2005-29.08.2005] R&D Projects: GA AV ČR 1ET101050403 Institutional research plan: CEZ:AV0Z10750506 Keywords : medical imaging * classification * Bayes classifier * Huzzolini feature * pattern recognition Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/prace/20050229.pdf

  17. Combining Deep and Handcrafted Image Features for Presentation Attack Detection in Face Recognition Systems Using Visible-Light Camera Sensors

    Dat Tien Nguyen

    2018-02-01

    Full Text Available Although face recognition systems have wide application, they are vulnerable to presentation attack samples (fake samples. Therefore, a presentation attack detection (PAD method is required to enhance the security level of face recognition systems. Most of the previously proposed PAD methods for face recognition systems have focused on using handcrafted image features, which are designed by expert knowledge of designers, such as Gabor filter, local binary pattern (LBP, local ternary pattern (LTP, and histogram of oriented gradients (HOG. As a result, the extracted features reflect limited aspects of the problem, yielding a detection accuracy that is low and varies with the characteristics of presentation attack face images. The deep learning method has been developed in the computer vision research community, which is proven to be suitable for automatically training a feature extractor that can be used to enhance the ability of handcrafted features. To overcome the limitations of previously proposed PAD methods, we propose a new PAD method that uses a combination of deep and handcrafted features extracted from the images by visible-light camera sensor. Our proposed method uses the convolutional neural network (CNN method to extract deep image features and the multi-level local binary pattern (MLBP method to extract skin detail features from face images to discriminate the real and presentation attack face images. By combining the two types of image features, we form a new type of image features, called hybrid features, which has stronger discrimination ability than single image features. Finally, we use the support vector machine (SVM method to classify the image features into real or presentation attack class. Our experimental results indicate that our proposed method outperforms previous PAD methods by yielding the smallest error rates on the same image databases.

  18. Combining Deep and Handcrafted Image Features for Presentation Attack Detection in Face Recognition Systems Using Visible-Light Camera Sensors.

    Nguyen, Dat Tien; Pham, Tuyen Danh; Baek, Na Rae; Park, Kang Ryoung

    2018-02-26

    Although face recognition systems have wide application, they are vulnerable to presentation attack samples (fake samples). Therefore, a presentation attack detection (PAD) method is required to enhance the security level of face recognition systems. Most of the previously proposed PAD methods for face recognition systems have focused on using handcrafted image features, which are designed by expert knowledge of designers, such as Gabor filter, local binary pattern (LBP), local ternary pattern (LTP), and histogram of oriented gradients (HOG). As a result, the extracted features reflect limited aspects of the problem, yielding a detection accuracy that is low and varies with the characteristics of presentation attack face images. The deep learning method has been developed in the computer vision research community, which is proven to be suitable for automatically training a feature extractor that can be used to enhance the ability of handcrafted features. To overcome the limitations of previously proposed PAD methods, we propose a new PAD method that uses a combination of deep and handcrafted features extracted from the images by visible-light camera sensor. Our proposed method uses the convolutional neural network (CNN) method to extract deep image features and the multi-level local binary pattern (MLBP) method to extract skin detail features from face images to discriminate the real and presentation attack face images. By combining the two types of image features, we form a new type of image features, called hybrid features, which has stronger discrimination ability than single image features. Finally, we use the support vector machine (SVM) method to classify the image features into real or presentation attack class. Our experimental results indicate that our proposed method outperforms previous PAD methods by yielding the smallest error rates on the same image databases.

  19. Combining Deep and Handcrafted Image Features for Presentation Attack Detection in Face Recognition Systems Using Visible-Light Camera Sensors

    Nguyen, Dat Tien; Pham, Tuyen Danh; Baek, Na Rae; Park, Kang Ryoung

    2018-01-01

    Although face recognition systems have wide application, they are vulnerable to presentation attack samples (fake samples). Therefore, a presentation attack detection (PAD) method is required to enhance the security level of face recognition systems. Most of the previously proposed PAD methods for face recognition systems have focused on using handcrafted image features, which are designed by expert knowledge of designers, such as Gabor filter, local binary pattern (LBP), local ternary pattern (LTP), and histogram of oriented gradients (HOG). As a result, the extracted features reflect limited aspects of the problem, yielding a detection accuracy that is low and varies with the characteristics of presentation attack face images. The deep learning method has been developed in the computer vision research community, which is proven to be suitable for automatically training a feature extractor that can be used to enhance the ability of handcrafted features. To overcome the limitations of previously proposed PAD methods, we propose a new PAD method that uses a combination of deep and handcrafted features extracted from the images by visible-light camera sensor. Our proposed method uses the convolutional neural network (CNN) method to extract deep image features and the multi-level local binary pattern (MLBP) method to extract skin detail features from face images to discriminate the real and presentation attack face images. By combining the two types of image features, we form a new type of image features, called hybrid features, which has stronger discrimination ability than single image features. Finally, we use the support vector machine (SVM) method to classify the image features into real or presentation attack class. Our experimental results indicate that our proposed method outperforms previous PAD methods by yielding the smallest error rates on the same image databases. PMID:29495417

  20. Associations between spondyloarthritis features and magnetic resonance imaging findings

    Arnbak, Bodil; Jurik, Anne Grethe; Hørslev-Petersen, Kim

    2016-01-01

    were 1) to estimate the prevalence of magnetic resonance imaging (MRI) findings and clinical features included in the ASAS criteria for SpA and 2) to explore the associations between MRI findings and clinical features. METHODS: We included patients ages 18-40 years with persistent low back pain who had...... been referred to the Spine Centre of Southern Denmark. We collected information on clinical features (including HLA-B27 and high-sensitivity C-reactive protein) and MRI findings in the spine and sacroiliac (SI) joints. RESULTS: Of 1,020 included patients, 537 (53%) had at least 1 of the clinical...... according to the ASAS definition was present in 217 patients (21%). Of those 217 patients, 91 (42%) had the minimum amount of bone marrow edema required according to the ASAS definition (a low bone marrow edema score). The presence of HLA-B27, peripheral arthritis, a good response to NSAIDs, and preceding...

  1. Hybrid Histogram Descriptor: A Fusion Feature Representation for Image Retrieval.

    Feng, Qinghe; Hao, Qiaohong; Chen, Yuqi; Yi, Yugen; Wei, Ying; Dai, Jiangyan

    2018-06-15

    Currently, visual sensors are becoming increasingly affordable and fashionable, acceleratingly the increasing number of image data. Image retrieval has attracted increasing interest due to space exploration, industrial, and biomedical applications. Nevertheless, designing effective feature representation is acknowledged as a hard yet fundamental issue. This paper presents a fusion feature representation called a hybrid histogram descriptor (HHD) for image retrieval. The proposed descriptor comprises two histograms jointly: a perceptually uniform histogram which is extracted by exploiting the color and edge orientation information in perceptually uniform regions; and a motif co-occurrence histogram which is acquired by calculating the probability of a pair of motif patterns. To evaluate the performance, we benchmarked the proposed descriptor on RSSCN7, AID, Outex-00013, Outex-00014 and ETHZ-53 datasets. Experimental results suggest that the proposed descriptor is more effective and robust than ten recent fusion-based descriptors under the content-based image retrieval framework. The computational complexity was also analyzed to give an in-depth evaluation. Furthermore, compared with the state-of-the-art convolutional neural network (CNN)-based descriptors, the proposed descriptor also achieves comparable performance, but does not require any training process.

  2. 3D shape recovery from image focus using Gabor features

    Mahmood, Fahad; Mahmood, Jawad; Zeb, Ayesha; Iqbal, Javaid

    2018-04-01

    Recovering an accurate and precise depth map from a set of acquired 2-D image dataset of the target object each having different focus information is an ultimate goal of 3-D shape recovery. Focus measure algorithm plays an important role in this architecture as it converts the corresponding color value information into focus information which will be then utilized for recovering depth map. This article introduces Gabor features as focus measure approach for recovering depth map from a set of 2-D images. Frequency and orientation representation of Gabor filter features is similar to human visual system and normally applied for texture representation. Due to its little computational complexity, sharp focus measure curve, robust to random noise sources and accuracy, it is considered as superior alternative to most of recently proposed 3-D shape recovery approaches. This algorithm is deeply investigated on real image sequences and synthetic image dataset. The efficiency of the proposed scheme is also compared with the state of art 3-D shape recovery approaches. Finally, by means of two global statistical measures, root mean square error and correlation, we claim that this approach, in spite of simplicity, generates accurate results.

  3. Unusual acute encephalitis involving the thalamus: imaging features

    Kim, Sam Soo [Kangwon National University Hospital, Chuncheon (Korea, Republic of); Chang, Kee Hyun; Kim, Kyung Won; Han Moon Hee [Seoul National University College of Medicine, Seoul (Korea, Republic of); Park, Sung Ho; Nam, Hyun Woo [Seoul City Boramae Hospital, Seoul (Korea, Republic of); Choi, Kyu Ho [Kangnam St. Mary' s Hospital, Seoul (Korea, Republic of); Cho, Woo Ho [Sanggyo Paik Hospital, Seoul (Korea, Republic of)

    2001-06-01

    To describe the brain CT and MR imaging findings of unusual acute encephalitis involving the thalamus. We retrospectively reviewed the medical records and CT and/or MR imaging findings of six patients with acute encephalitis involving the thalamus. CT (n=6) and MR imaging (n=6) were performed during the acute and/or convalescent stage of the illness. Brain CT showed brain swelling (n=2), low attenuation of both thalami (n=1) or normal findings (n=3). Initial MR imaging indicated that in all patients the thalamus was involved either bilaterally (n=5) or unilaterally (n=1). Lesions were also present in the midbrain (n=5), medial temporal lobe (n=4), pons (n=3), both hippocampi (n=3) the insular cortex (n=2), medulla (n=2), lateral temporal lobe cortex (n=1), both cingulate gyri (n=1), both basal ganglia (n=1), and the left hemispheric cortex (n=1). These CT or MR imaging findings of acute encephalitis of unknown etiology were similar to a combination of those of Japanese encephalitis and herpes simplex encephalitis. In order to document the specific causative agents which lead to the appearance of these imaging features, further investigation is required.

  4. MR imaging features of the congenital uterine anomalies

    Hamcan, S.; Akgun, V.; Battal, B.; Kocaoglu, M.

    2012-01-01

    Full text: Introduction: Congenital uterine anomalies are common and usually asymptomatic. The agenesis, malfusion or deficient resorption of the Mullerian canals during embryogenesis may lead to these anomalies. Although ultrasonography (US) is the first step imaging technique in assessment of the uterine pathologies, it can be insufficient in differentiation of them. Magnetic resonance (MR) imaging is an adequate imaging technique in depicting pelvic anatomy and different types of uterine anomalies. Objectives and tasks: In this article, we aimed to present imaging features of the uterine anomalies. Material and methods: Pelvic MR scans of the cases who were referred to our radiology department for suspicious uterine anomaly were evaluated retrospectively. Results: We determined uniconuate uterus (type II), uterus didelphys (type III), bicornuate uterus (type IV), uterine septum (type V) and arcuate uterus (type VI) anomalies according to ASRM (American Society of Reproductive Medicine) classification. Conclusion: In cases with such pathologies leading to obstruction, dysmenorrhea or palpable pelvic mass in the puberty are the main clinical presentations. In cases without obstruction, infertility or multiple abortions can be encountered in reproductive ages. The identification of the subtype of the uterine anomalies is important for the preoperative planning of the management. MR that has multiplanar imaging capability and high soft tissue resolution is a non-invasive and the most important imaging modality for the detection and classification of the uterine anomalies

  5. Image Relaxation Matching Based on Feature Points for DSM Generation

    ZHENG Shunyi; ZHANG Zuxun; ZHANG Jianqing

    2004-01-01

    In photogrammetry and remote sensing, image matching is a basic and crucial process for automatic DEM generation. In this paper we presented a image relaxation matching method based on feature points. This method can be considered as an extention of regular grid point based matching. It avoids the shortcome of grid point based matching. For example, with this method, we can avoid low or even no texture area where errors frequently appear in cross correlaton matching. In the mean while, it makes full use of some mature techniques such as probability relaxation, image pyramid and the like which have already been successfully used in grid point matching process. Application of the technique to DEM generaton in different regions proved that it is more reasonable and reliable.

  6. Multispectral image feature fusion for detecting land mines

    Clark, G.A.; Fields, D.J.; Sherwood, R.J. [Lawrence Livermore National Lab., CA (United States)] [and others

    1994-11-15

    Our system fuses information contained in registered images from multiple sensors to reduce the effect of clutter and improve the the ability to detect surface and buried land mines. The sensor suite currently consists if a camera that acquires images in sixible wavelength bands, du, dual-band infrared (5 micron and 10 micron) and ground penetrating radar. Past research has shown that it is extremely difficult to distinguish land mines from background clutter in images obtained from a single sensor. It is hypothesized, however, that information fused from a suite of various sensors is likely to provide better detection reliability, because the suite of sensors detects a variety of physical properties that are more separate in feature space. The materials surrounding the mines can include natural materials (soil, rocks, foliage, water, holes made by animals and natural processes, etc.) and some artifacts.

  7. CFA-aware features for steganalysis of color images

    Goljan, Miroslav; Fridrich, Jessica

    2015-03-01

    Color interpolation is a form of upsampling, which introduces constraints on the relationship between neighboring pixels in a color image. These constraints can be utilized to substantially boost the accuracy of steganography detectors. In this paper, we introduce a rich model formed by 3D co-occurrences of color noise residuals split according to the structure of the Bayer color filter array to further improve detection. Some color interpolation algorithms, AHD and PPG, impose pixel constraints so tight that extremely accurate detection becomes possible with merely eight features eliminating the need for model richification. We carry out experiments on non-adaptive LSB matching and the content-adaptive algorithm WOW on five different color interpolation algorithms. In contrast to grayscale images, in color images that exhibit traces of color interpolation the security of WOW is significantly lower and, depending on the interpolation algorithm, may even be lower than non-adaptive LSB matching.

  8. The ''botryoid sign'': a characteristic feature of rhabdomyosarcomas in the head and neck

    Hagiwara, A.; Inoue, Y.; Yamato, K.; Daikokuya, H.; Nakayama, K.; Yamada, R.; Nakayama, T.; Nemoto, Y.; Shakudo, M.

    2001-01-01

    We investigated nine patients with rhabomyosarcoma in the head and neck (6-53 years of age), using CT and MRI. The tumours originated in the paranasal sinuses (3), cheek (2), soft palate (1), orbit (1), sternocostoclavicular muscle (1) and parapharyngeal space (1). The histological subtype was embryonal in five, alveolar in three and pleomorphic in one case. The tumours enhanced markedly and heterogeneous on CT and MRI. The masses were isointense or gave slightly higher signal than surrounding muscles on T1- and heterogeneously high signal on T2-weighted images. In four tumours, multiple ring enhancement resembling bunches of grapes. This appears to be characteristic of rhabdomyosarcoma and probably reflects a component of botryoid-type rhabdomyosarcoma in which mucoid-rich stroma is covered with a thin layer of tumour cells. We have named this imaging feature the ''botryoid sign''. (orig.)

  9. Shape adaptive, robust iris feature extraction from noisy iris images.

    Ghodrati, Hamed; Dehghani, Mohammad Javad; Danyali, Habibolah

    2013-10-01

    In the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. Whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. To the best of our knowledge, the effect of noise factors on feature extraction has not been considered in the previous works. This paper investigates the effect of shape adaptive wavelet transform and shape adaptive Gabor-wavelet for feature extraction on the iris recognition performance. In addition, an effective noise-removing approach is proposed in this paper. The contribution is to detect eyelashes and reflections by calculating appropriate thresholds by a procedure called statistical decision making. The eyelids are segmented by parabolic Hough transform in normalized iris image to decrease computational burden through omitting rotation term. The iris is localized by an accurate and fast algorithm based on coarse-to-fine strategy. The principle of mask code generation is to assign the noisy bits in an iris code in order to exclude them in matching step is presented in details. An experimental result shows that by using the shape adaptive Gabor-wavelet technique there is an improvement on the accuracy of recognition rate.

  10. Comparison on imaging features of central serous chorioretinopathy fundus

    Ji-Jin Zhang

    2014-10-01

    Full Text Available AIM: To explore and analyze the image features, diagnosis and treatment of the central serous chorioretinopathy(CSCRfundus. METHODS: From May 2008 to May 2014, 97 cases of 121 eyes with central serous chorioretinopathy were treated in in our hospital. The imaging features were compared and analyzed through different methods. RESULTS: Sixty-one cases(61 eyeswere ≤45 years, including 13 case with disease in both eyes, single stove leak accounted for 48.6%, multifocal leakage(25.7%, atypical leakage accounted for 25.7%. Thirty-six cases(47 eyeswere >45 years, 11 cases with disease in both eyes, single focal leakage(8.5%, multifocal leakage(48.9%, atypical leakage accounted for 42.6%. FFA results showed acute hairstyle at the beginning of 89 eyes, chronic deferment type 32 eyes. OCT examination showed that the main features were neuroepithelial detachment, as well as the change of the retinal pigment epithelium(RPElayer, which was divided into RPE layer detachment 93 eyes, accounting for 76.9%, rough and RPE little ridges in 28 cases, accounting for 23.1%. The average thickness of macular center concave on the cortex of microns was 137.87±19.21μm, and there was no significant difference conpared with normal(137.32±4.98μmmicrons(t=0.30, P>0.05. The closer leakage area to macular fovea, the worse of eyesight.. CONCLUSION: Different imaging examination on central serous chorioretinopathy can show different features. For clinical diagnosis and treatment it had different and complementary roles, but were given significant help for diseases treatment.

  11. Differentiating characteristic microstructural features of cancerous tissues using Mueller matrix microscope.

    Wang, Ye; He, Honghui; Chang, Jintao; Zeng, Nan; Liu, Shaoxiong; Li, Migao; Ma, Hui

    2015-12-01

    Polarized light imaging can provide rich microstructural information of samples, and has been applied to the detections of various abnormal tissues. In this paper, we report a polarized light microscope based on Mueller matrix imaging by adding the polarization state generator and analyzer (PSG and PSA) to a commercial transmission optical microscope. The maximum errors for the absolute values of Mueller matrix elements are reduced to 0.01 after calibration. This Mueller matrix microscope has been used to examine human cervical and liver cancerous tissues with fibrosis. Images of the transformed Mueller matrix parameters provide quantitative assessment on the characteristic features of the pathological tissues. Contrast mechanism of the experimental results are backed up by Monte Carlo simulations based on the sphere-cylinder birefringence model, which reveal the relationship between the pathological features in the cancerous tissues at the cellular level and the polarization parameters. Both the experimental and simulated data indicate that the microscopic transformed Mueller matrix parameters can distinguish the breaking down of birefringent normal tissues for cervical cancer, or the formation of birefringent surrounding structures accompanying the inflammatory reaction for liver cancer. With its simple structure, fast measurement and high precision, polarized light microscope based on Mueller matrix shows a good diagnosis application prospect. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. New feature of the neutron color image intensifier

    Nittoh, Koichi; Konagai, Chikara; Noji, Takashi; Miyabe, Keisuke

    2009-06-01

    We developed prototype neutron color image intensifiers with high-sensitivity, wide dynamic range and long-life characteristics. In the prototype intensifier (Gd-Type 1), a terbium-activated Gd 2O 2S is used as the input-screen phosphor. In the upgraded model (Gd-Type 2), Gd 2O 3 and CsI:Na are vacuum deposited to form the phosphor layer, which improved the sensitivity and the spatial uniformity. A europium-activated Y 2O 2S multi-color scintillator, emitting red, green and blue photons with different intensities, is utilized as the output screen of the intensifier. By combining this image intensifier with a suitably tuned high-sensitive color CCD camera, higher sensitivity and wider dynamic range could be simultaneously attained than that of the conventional P20-phosphor-type image intensifier. The results of experiments at the JRR-3M neutron radiography irradiation port (flux: 1.5×10 8 n/cm 2/s) showed that these neutron color image intensifiers can clearly image dynamic phenomena with a 30 frame/s video picture. It is expected that the color image intensifier will be used as a new two-dimensional neutron sensor in new application fields.

  13. New feature of the neutron color image intensifier

    Nittoh, Koichi; Konagai, Chikara; Noji, Takashi; Miyabe, Keisuke

    2009-01-01

    We developed prototype neutron color image intensifiers with high-sensitivity, wide dynamic range and long-life characteristics. In the prototype intensifier (Gd-Type 1), a terbium-activated Gd 2 O 2 S is used as the input-screen phosphor. In the upgraded model (Gd-Type 2), Gd 2 O 3 and CsI:Na are vacuum deposited to form the phosphor layer, which improved the sensitivity and the spatial uniformity. A europium-activated Y 2 O 2 S multi-color scintillator, emitting red, green and blue photons with different intensities, is utilized as the output screen of the intensifier. By combining this image intensifier with a suitably tuned high-sensitive color CCD camera, higher sensitivity and wider dynamic range could be simultaneously attained than that of the conventional P20-phosphor-type image intensifier. The results of experiments at the JRR-3M neutron radiography irradiation port (flux: 1.5x10 8 n/cm 2 /s) showed that these neutron color image intensifiers can clearly image dynamic phenomena with a 30 frame/s video picture. It is expected that the color image intensifier will be used as a new two-dimensional neutron sensor in new application fields.

  14. Magnetic resonance characteristics and susceptibility weighted imaging of the brain in gadolinium encephalopathy.

    Samardzic, Dejan; Thamburaj, Krishnamoorthy

    2015-01-01

    To report the brain imaging features on magnetic resonance imaging (MRI) in inadvertent intrathecal gadolinium administration. A 67-year-old female with gadolinium encephalopathy from inadvertent high dose intrathecal gadolinium administration during an epidural steroid injection was studied with multisequence 3T MRI. T1-weighted imaging shows pseudo-T2 appearance with diffusion of gadolinium into the brain parenchyma, olivary bodies, and membranous labyrinth. Nulling of cerebrospinal fluid (CSF) signal is absent on fluid attenuation recovery (FLAIR). Susceptibility-weighted imaging (SWI) demonstrates features similar to subarachnoid hemorrhage. CT may demonstrate a pseudo-cerebral edema pattern given the high attenuation characteristics of gadolinium. Intrathecal gadolinium demonstrates characteristic imaging features on MRI of the brain and may mimic subarachnoid hemorrhage on susceptibility-weighted imaging. Identifying high dose gadolinium within the CSF spaces on MRI is essential to avoid diagnostic and therapeutic errors. Copyright © 2013 by the American Society of Neuroimaging.

  15. Features of current-voltage characteristic of nonequilibrium trench MOS barrier Schottky diode

    Mamedov, R. K.; Aslanova, A. R.

    2018-06-01

    The trench MOS barrier Schottky diodes (TMBS diode) under the influence of the voltage drop of the additional electric field (AEF) appearing in the near-contact region of the semiconductor are in a nonequilibrium state and their closed external circuit flows currents in the absence of an external voltage. When an external voltage is applied to the TMBS diode, the current transmission is described by the thermionic emission theory with a specific feature. Both forward and reverse I-V characteristics of the TMBS diode consist of two parts. In the initial first part of the forward I-V characteristic there are no forward currents, but reverse saturation currents flow, in its subsequent second part the currents increase exponentially with the voltage. In the initial first part of the reverse I-V characteristic, the currents increase in an abrupt way and in the subsequent second part the saturation currents flow under the action of the image force. The mathematical expressions for forward and reverse I-V characteristic of the TMBS diode and also narrow or nanostructure Schottky diode are proposed, which are in good agreement with the results of experimental and calculated I-V characteristics.

  16. CT imaging and histopathological features of renal epithelioid angiomyolipomas

    Cui, L.; Zhang, J.-G.; Hu, X.-Y.; Fang, X.-M.; Lerner, A.; Yao, X.-J.; Zhu, Z.-M.

    2012-01-01

    Aim: To describe computed tomography (CT) imaging and histopathological manifestations of renal epithelioid angiomyolipomas (EAMLs) for better understanding and cognition in the diagnosis of this new category of renal tumours. Materials and methods: Clinical data and CT images from 10 cases of EAML were retrospectively analysed. All patients underwent CT with and without contrast medium administration, with multiplanar reconstruction (MPR) when needed. Results: Plain CT manifestations of EAMLs were a higher density of mass (10–25 HU) than renal parenchyma, bulging contour of the involved kidney, absence of fat, distinct edges without a lobulate appearance. Contrast-enhanced CT features were markedly heterogeneous enhancement (from rapid wash-in to slow wash-out), large tumour size without lobular appearance, complete capsule with distinct margins and frequent mild necrotic areas. Histopathological features were epithelioid cells with eosinophilic cytoplasm, large and deeply stained nuclei, and dense arrangement of tumour cells with patchy necrosis; diffuse sheets of epithelioid cells were positive for HMB-45 (melanoma-associated antigen) and negative for epithelial membrane antigen (EMA) staining. Conclusion: Multiple specific CT features correlated well with the histopathology and may play an important role in the primary diagnosis of EAMLs.

  17. MRI of Creutzfeldt-Jakob disease: Imaging features and recommended MRI protocol

    Collie, D.A.; Sellar, R.J.; Zeidler, M.; Colchester, A.C.F.; Knight, R.; Will, R.G

    2001-09-01

    Creutzfeldt-Jakob Disease (CJD) is a rare, progressive and invariably fatal neurodegenerative disease characterized by specific histopathological features. Of the four subtypes of CJD described, the commonest is sporadic CJD (sCJD). More recently, a new clinically distinct form of the disease affecting younger patients, known as variant CJD (vCJD), has been identified, and this has been causally linked to the bovine spongiform encephalopathy (BSE) agent in cattle. Characteristic appearances on magnetic resonance imaging (MRI) have been identified in several forms of CJD; sCJD may be associated with high signal changes in the putamen and caudate head and vCJD is usually associated with hyperintensity of the pulvinar (posterior nuclei) of the thalamus. These appearances and other imaging features are described in this article. Using appropriate clinical and radiological criteria and tailored imaging protocols, MRI plays an important part in the in vivodiagnosis of this disease. Collie, D.A. et al. (2001)

  18. MRI of Creutzfeldt-Jakob disease: Imaging features and recommended MRI protocol

    Collie, D.A.; Sellar, R.J.; Zeidler, M.; Colchester, A.C.F.; Knight, R.; Will, R.G.

    2001-01-01

    Creutzfeldt-Jakob Disease (CJD) is a rare, progressive and invariably fatal neurodegenerative disease characterized by specific histopathological features. Of the four subtypes of CJD described, the commonest is sporadic CJD (sCJD). More recently, a new clinically distinct form of the disease affecting younger patients, known as variant CJD (vCJD), has been identified, and this has been causally linked to the bovine spongiform encephalopathy (BSE) agent in cattle. Characteristic appearances on magnetic resonance imaging (MRI) have been identified in several forms of CJD; sCJD may be associated with high signal changes in the putamen and caudate head and vCJD is usually associated with hyperintensity of the pulvinar (posterior nuclei) of the thalamus. These appearances and other imaging features are described in this article. Using appropriate clinical and radiological criteria and tailored imaging protocols, MRI plays an important part in the in vivodiagnosis of this disease. Collie, D.A. et al. (2001)

  19. Research on Remote Sensing Image Classification Based on Feature Level Fusion

    Yuan, L.; Zhu, G.

    2018-04-01

    Remote sensing image classification, as an important direction of remote sensing image processing and application, has been widely studied. However, in the process of existing classification algorithms, there still exists the phenomenon of misclassification and missing points, which leads to the final classification accuracy is not high. In this paper, we selected Sentinel-1A and Landsat8 OLI images as data sources, and propose a classification method based on feature level fusion. Compare three kind of feature level fusion algorithms (i.e., Gram-Schmidt spectral sharpening, Principal Component Analysis transform and Brovey transform), and then select the best fused image for the classification experimental. In the classification process, we choose four kinds of image classification algorithms (i.e. Minimum distance, Mahalanobis distance, Support Vector Machine and ISODATA) to do contrast experiment. We use overall classification precision and Kappa coefficient as the classification accuracy evaluation criteria, and the four classification results of fused image are analysed. The experimental results show that the fusion effect of Gram-Schmidt spectral sharpening is better than other methods. In four kinds of classification algorithms, the fused image has the best applicability to Support Vector Machine classification, the overall classification precision is 94.01 % and the Kappa coefficients is 0.91. The fused image with Sentinel-1A and Landsat8 OLI is not only have more spatial information and spectral texture characteristics, but also enhances the distinguishing features of the images. The proposed method is beneficial to improve the accuracy and stability of remote sensing image classification.

  20. Collaborative Tracking of Image Features Based on Projective Invariance

    Jiang, Jinwei

    -mode sensors for improving the flexibility and robustness of the system. From the experimental results during three field tests for the LASOIS system, we observed that most of the errors in the image processing algorithm are caused by the incorrect feature tracking. This dissertation addresses the feature tracking problem in image sequences acquired from cameras. Despite many alternatives to feature tracking problem, iterative least squares solution solving the optical flow equation has been the most popular approach used by many in the field. This dissertation attempts to leverage the former efforts to enhance feature tracking methods by introducing a view geometric constraint to the tracking problem, which provides collaboration among features. In contrast to alternative geometry based methods, the proposed approach provides an online solution to optical flow estimation in a collaborative fashion by exploiting Horn and Schunck flow estimation regularized by view geometric constraints. Proposed collaborative tracker estimates the motion of a feature based on the geometry of the scene and how the other features are moving. Alternative to this approach, a new closed form solution to tracking that combines the image appearance with the view geometry is also introduced. We particularly use invariants in the projective coordinates and conjecture that the traditional appearance solution can be significantly improved using view geometry. The geometric constraint is introduced by defining a new optical flow equation which exploits the scene geometry from a set drawn from tracked features. At the end of each tracking loop the quality of the tracked features is judged using both appearance similarity and geometric consistency. Our experiments demonstrate robust tracking performance even when the features are occluded or they undergo appearance changes due to projective deformation of the template. The proposed collaborative tracking method is also tested in the visual navigation

  1. Multimodal Ultrawide-Field Imaging Features in Waardenburg Syndrome.

    Choudhry, Netan; Rao, Rajesh C

    2015-06-01

    A 45-year-old woman was referred for bilateral irregular fundus pigmentation. Dilated fundus examination revealed irregular hypopigmentation posterior to the equator in both eyes, confirmed by fundus autofluorescence. A thickened choroid was seen on enhanced-depth imaging spectral-domain optical coherence tomography (EDI SD-OCT). Systemic evaluation revealed sensorineural deafness, telecanthus, and a white forelock. Further investigation revealed a first-degree relative with Waardenburg syndrome. Waardenburg syndrome is characterized by a group of features including telecanthus, a broad nasal root, synophrys of the eyebrows, piedbaldism, heterochromia irides, and deafness. Choroidal hypopigmentation is a unique feature that can be visualized with ultrawide-field fundus autofluorescence. The choroid may also be thickened and its thickness measured with EDI SD-OCT. Copyright 2015, SLACK Incorporated.

  2. Can Global Visual Features Improve Tag Recommendation for Image Annotation?

    Oge Marques

    2010-08-01

    Full Text Available Recent advances in the fields of digital photography, networking and computing, have made it easier than ever for users to store and share photographs. However without sufficient metadata, e.g., in the form of tags, photos are difficult to find and organize. In this paper, we describe a system that recommends tags for image annotation. We postulate that the use of low-level global visual features can improve the quality of the tag recommendation process when compared to a baseline statistical method based on tag co-occurrence. We present results from experiments conducted using photos and metadata sourced from the Flickr photo website that suggest that the use of visual features improves the mean average precision (MAP of the system and increases the system's ability to suggest different tags, therefore justifying the associated increase in complexity.

  3. Event characteristics and socio-demographic features of rape ...

    Objectives: On account of increasing awareness of the need for Post exposure prophylaxis (PEP) and availability of requisite drugs, victims of rape are now presenting at health facilities including ours to access PEP for HIV. This study set to document the socio-demographic features of these victims and the event ...

  4. Mutual information based feature selection for medical image retrieval

    Zhi, Lijia; Zhang, Shaomin; Li, Yan

    2018-04-01

    In this paper, authors propose a mutual information based method for lung CT image retrieval. This method is designed to adapt to different datasets and different retrieval task. For practical applying consideration, this method avoids using a large amount of training data. Instead, with a well-designed training process and robust fundamental features and measurements, the method in this paper can get promising performance and maintain economic training computation. Experimental results show that the method has potential practical values for clinical routine application.

  5. Clinical, imaging and histopathological features of isolated CNS lymphomatoid granulomatosis

    Patil, Anil Kumar; Alexander, Mathew; Nair, Bijesh; Chacko, Geeta; Mani, Sunithi; Sudhakar, Sniya

    2015-01-01

    Lymphomatoid granulomatosis is a rare systemic angiocentric/angiodestructive, B cell lymphoproliferative disorder. Central nervous system involvement occurs as part of systemic disease. Isolated central nervous system disease is rare with only few case reports. A 53-year-old male presented with progressive cognitive decline, extrapyramidal features, and altered sensorium with seizures over the last 4 years. His magnetic resonance imaging (MRI) of brain showed multiple small enhancing nodules in subependymal/ependymal regions and along the vessels. Brain biopsy showed atypical lymphohistiocytic infiltrate suggestive of lymphomatoid granulomatosis. There was no evidence of systemic disease; thus, isolated central nervous system lymphomatoid granulomatosis was diagnosed

  6. MR imaging features of chronically torn anterior cruciate ligament

    Niitsu, Mamoru; Kuramochi, Masashi; Ikeda, Kotaroh; Fukubayashi, Tohru; Anno, Izumi; Itai, Yuji

    1995-01-01

    Magnetic resonance (MR) images of 40 knee joints with arthroscopically proved chronic anterior cruciate ligament (ACL) tears were retrospectively evaluated. MRI demonstrated various features of chronic ACL tears: 19 knees revealed with no identifiable ligamentous structure, and 21 had residual ligamentous structures. These pseudoligaments, 14 discontinuous bands and seven continuous bands with elongation, were residual torn ligamentous fibers and/or synovial tissues. All the discontinuous bands were disrupted from the femoral attachment and were likely to traverse the lower intercondylar space. Six disrupted ligaments were attached to the lateral aspect of the posterior cruciate ligament (PCL). Coronal T2 * -weighted gradient echo images showed better delineation of the disrupted femoral attachment and adhesion to the PCL. A chronic ACL tear with minimal elongation or with PCL attachment at a higher position may occasionally be difficult to distinguish from an intact ligament. (author)

  7. [Clinical, pathological and imaging features of primary pelvic Ewing's sarcoma].

    Liu, J; Chen, Y; Ling, X L; Gong, Y; Ding, J P; Zhang, Z K; Wang, Y J

    2016-07-19

    To explore the clinical, pathological and imaging features of Ewing's sarcoma in pelvis and to improve knowledge and diagnosis of the disease. A retrospective analysis of the clinical, pathological and imaging data of pathologically confirmed 13 cases of Ewing's sarcoma in pelvis was carried out between May 2008 and March 2016 in the Affiliated Hospital of Hangzhou Normal University, the Third Hospital of Hebei Medical University and the Second Hospital of Hebei Medical University. The median age 13 cases of pelvic primary Ewing's sarcoma was 17 years old.The X-ray and CT imagings showed osteolytic and mixed bone destruction, CT showed mixed type in 10 cases, 8 cases of bone tumors as a flocculent, 10 cases of bone expansion failure, 10 cases of periosteal reaction, the layered 5 cases, radial in 5 cases.Thirteen cases showed soft tissue mass, soft tissue mass was equal or slightly lower density.Four cases showed heterogeneous contrast enhancement.The lesions showed low signal in T1WI and mixed high signal in T2WI of magnetic resonance imaging(MRI). The boundary of the lesions were obscure, and 5 cases had patchy necrosis area, and 9 cases had incomplete false capsule, surrounding soft tissue was violated.Four cases showed heterogeneous contrast enhancement after MRI enhancement scan. The age of onset of Ewing's sarcoma of the pelvis is more concentrated in about 15 years.The imaging feaures are mixed bone destruction and more bone is swelling and permeability damage, soft tissue mass is larger, bone tumor is cloudy or acicular, periosteal reaction in a layered and radial, most cases show that the false envelope is not complete.Combined with clinical and imaging examination, the diagnosis of the disease can be made.

  8. Water Extraction in High Resolution Remote Sensing Image Based on Hierarchical Spectrum and Shape Features

    Li, Bangyu; Zhang, Hui; Xu, Fanjiang

    2014-01-01

    This paper addresses the problem of water extraction from high resolution remote sensing images (including R, G, B, and NIR channels), which draws considerable attention in recent years. Previous work on water extraction mainly faced two difficulties. 1) It is difficult to obtain accurate position of water boundary because of using low resolution images. 2) Like all other image based object classification problems, the phenomena of ''different objects same image'' or ''different images same object'' affects the water extraction. Shadow of elevated objects (e.g. buildings, bridges, towers and trees) scattered in the remote sensing image is a typical noise objects for water extraction. In many cases, it is difficult to discriminate between water and shadow in a remote sensing image, especially in the urban region. We propose a water extraction method with two hierarchies: the statistical feature of spectral characteristic based on image segmentation and the shape feature based on shadow removing. In the first hierarchy, the Statistical Region Merging (SRM) algorithm is adopted for image segmentation. The SRM includes two key steps: one is sorting adjacent regions according to a pre-ascertained sort function, and the other one is merging adjacent regions based on a pre-ascertained merging predicate. The sort step is done one time during the whole processing without considering changes caused by merging which may cause imprecise results. Therefore, we modify the SRM with dynamic sort processing, which conducts sorting step repetitively when there is large adjacent region changes after doing merging. To achieve robust segmentation, we apply the merging region with six features (four remote sensing image bands, Normalized Difference Water Index (NDWI), and Normalized Saturation-value Difference Index (NSVDI)). All these features contribute to segment image into region of object. NDWI and NSVDI are discriminate between water and

  9. Featured Image: New Detail in the Toothbrush Cluster

    Kohler, Susanna

    2018-01-01

    This spectacular composite (click here for the full image) reveals the galaxy cluster 1RXS J0603.3+4214, known as the Toothbrush cluster due to the shape of its most prominent radio relic. Featured in a recent publication led by Kamlesh Rajpurohit (Thuringian State Observatory, Germany), this image contains new Very Large Array (VLA) 1.5-GHz observations (red) showing the radio emission within the cluster. This is composited with a Chandra view of the X-ray emitting gas of the cluster (blue) and an optical image of the background from Subaru data. The new deep VLA data totaling 26 hours of observations provides a detailed look at the complex structure within the Toothbrush relic, revealing enigmatic filaments and twists (see below). This new data will help us to explore the possible merger history of this cluster, which is theorized to have caused the unusual shapes we see today. For more information, check out the original article linked below.High resolution VLA 12 GHz image of the Toothbrush showing the complex, often filamentary structures. [Rajpurohit et al. 2018]CitationK. Rajpurohit et al 2018 ApJ 852 65. doi:10.3847/1538-4357/aa9f13

  10. Spinal focal lesion detection in multiple myeloma using multimodal image features

    Fränzle, Andrea; Hillengass, Jens; Bendl, Rolf

    2015-03-01

    Multiple myeloma is a tumor disease in the bone marrow that affects the skeleton systemically, i.e. multiple lesions can occur in different sites in the skeleton. To quantify overall tumor mass for determining degree of disease and for analysis of therapy response, volumetry of all lesions is needed. Since the large amount of lesions in one patient impedes manual segmentation of all lesions, quantification of overall tumor volume is not possible until now. Therefore development of automatic lesion detection and segmentation methods is necessary. Since focal tumors in multiple myeloma show different characteristics in different modalities (changes in bone structure in CT images, hypointensity in T1 weighted MR images and hyperintensity in T2 weighted MR images), multimodal image analysis is necessary for the detection of focal tumors. In this paper a pattern recognition approach is presented that identifies focal lesions in lumbar vertebrae based on features from T1 and T2 weighted MR images. Image voxels within bone are classified using random forests based on plain intensities and intensity value derived features (maximum, minimum, mean, median) in a 5 x 5 neighborhood around a voxel from both T1 and T2 weighted MR images. A test data sample of lesions in 8 lumbar vertebrae from 4 multiple myeloma patients can be classified at an accuracy of 95% (using a leave-one-patient-out test). The approach provides a reasonable delineation of the example lesions. This is an important step towards automatic tumor volume quantification in multiple myeloma.

  11. STUDY ON SHADOW EFFECTS OF VARIOUS FEATURES ON CLOSE RANGE THERMAL IMAGES

    C. L. Liao

    2012-07-01

    Full Text Available Thermal infrared data become more popular in remote sensing investigation, for it could be acquired both in day and night. The change of temperature has special characteristic in natural environment, so the thermal infrared images could be used in monitoring volcanic landform, the urban development, and disaster prevention. Heat shadow is formed by reflecting radiating capacity which followed the objects. Because of poor spatial resolution of thermal infrared images in satellite sensor, shadow effects were usually ignored. This research focus on discussing the shadow effects of various features, which include metals and nonmetallic materials. An area-based thermal sensor, FLIR-T360 was selected to acquire thermal images. Various features with different emissivity were chosen as reflective surface to obtain thermal shadow in normal atmospheric temperature. Experiments found that the shadow effects depend on the distance between sensors and features, depression angle, object temperature and emissivity of reflective surface. The causes of shadow effects have been altered in the experiment for analyzing the variance in thermal infrared images. The result shows that there were quite different impacts by shadow effects between metals and nonmetallic materials. The further research would be produced a math model to describe the shadow effects of different features in the future work.

  12. Phenotypic feature quantification of patient derived 3D cancer spheroids in fluorescence microscopy image

    Kang, Mi-Sun; Rhee, Seon-Min; Seo, Ji-Hyun; Kim, Myoung-Hee

    2017-03-01

    Patients' responses to a drug differ at the cellular level. Here, we present an image-based cell phenotypic feature quantification method for predicting the responses of patient-derived glioblastoma cells to a particular drug. We used high-content imaging to understand the features of patient-derived cancer cells. A 3D spheroid culture formation resembles the in vivo environment more closely than 2D adherent cultures do, and it allows for the observation of cellular aggregate characteristics. However, cell analysis at the individual level is more challenging. In this paper, we demonstrate image-based phenotypic screening of the nuclei of patient-derived cancer cells. We first stitched the images of each well of the 384-well plate with the same state. We then used intensity information to detect the colonies. The nuclear intensity and morphological characteristics were used for the segmentation of individual nuclei. Next, we calculated the position of each nucleus that is appeal of the spatial pattern of cells in the well environment. Finally, we compared the results obtained using 3D spheroid culture cells with those obtained using 2D adherent culture cells from the same patient being treated with the same drugs. This technique could be applied for image-based phenotypic screening of cells to determine the patient's response to the drug.

  13. Novel giant siphovirus from Bacillus anthracis features unusual genome characteristics.

    Holly H Ganz

    Full Text Available Here we present vB_BanS-Tsamsa, a novel temperate phage isolated from Bacillus anthracis, the agent responsible for anthrax infections in wildlife, livestock and humans. Tsamsa phage is a giant siphovirus (order Caudovirales, featuring a long, flexible and non-contractile tail of 440 nm (not including baseplate structure and an isometric head of 82 nm in diameter. We induced Tsamsa phage in samples from two different carcass sites in Etosha National Park, Namibia. The Tsamsa phage genome is the largest sequenced Bacillus siphovirus, containing 168,876 bp and 272 ORFs. The genome features an integrase/recombinase enzyme, indicative of a temperate lifestyle. Among bacterial strains tested, the phage infected only certain members of the Bacillus cereus sensu lato group (B. anthracis, B. cereus and B. thuringiensis and exhibited moderate specificity for B. anthracis. Tsamsa lysed seven out of 25 B. cereus strains, two out of five B. thuringiensis strains and six out of seven B. anthracis strains tested. It did not lyse B. anthracis PAK-1, an atypical strain that is also resistant to both gamma phage and cherry phage. The Tsamsa endolysin features a broader lytic spectrum than the phage host range, indicating possible use of the enzyme in Bacillus biocontrol.

  14. CT and MR imaging features in patients with intracranial dolichoectasia

    Tien, Kuang Lung; Yu, In Kyu; Yoon, Sook Ja; Yoon, Yong Kyu [Eulji College of Medicine, Eulji Hospital, Seoul (Korea, Republic of)

    2000-02-01

    To describe the CT and MR imaging features in patients with intracranial dolichoectasia. The CT (n=3D21), MR (n=3D20) and MRA (n=3D11) imaging features seen in 28 patients (M:F=3D12:16 aged between 65 and 82 (mean, 65) years) with intracranial dolichoectasia were retrospectively reviewed with regard to involved sites, arterial changes (maximum diameter, wall calcification, high signal intensity in the involved artery, as seen on T1-weighted MR images), infarction, hemorrhagic lesion, compression of brain parenchyma or cranial nerves, hydrocephalus and brain atrophy. Involved sites were classified as either type 1 (involvement of only the posterior circulation), type 2 (only the anterior circulation), or type 3 (both). In order of frequency, involved sites were type 1 (43%), type 3 (36%) and type 2 (22%). Dolichoectasia was more frequently seen in the posterior circulation (79%) than in the anterior (57%). Arterial changes as seen on T1-weighted MR images, included dolichoectasia (mean maximum diameter 7.4 mm in the distal internal carotid artery, and 6.7 mm in the basilar artery), wall calcification (100% in involved arteries) and high signal intensity in involved. Cerebral infarction in the territory of the involved artery was found in all patients, and a moderate degree of infarct was 87%. Hemorrhagic lesions were found in 19 patients (68%); these were either lobar (53%), petechial (37%), or subarachnoid (16%), and three patients showed intracranial aneurysms, including one case of dissecting aneurysm. In 19 patients (68%), lesions were compressed lesions by the dolichoectatic arteries, and were found-in order of descending frequency-in the medulla, pons, thalamus, and cerebellopontine angle cistern. Obstructive hydrocephalus was found in two patients (7%), and 23 (82%) showed a moderate degree of brain atrophy. In patients with intracranial dolichoectasia, moderate degrees of cerebral infarction and brain atrophy in the territory of involved arteries, as well as

  15. Reduction of false-positive recalls using a computerized mammographic image feature analysis scheme

    Tan, Maxine; Pu, Jiantao; Zheng, Bin

    2014-08-01

    The high false-positive recall rate is one of the major dilemmas that significantly reduce the efficacy of screening mammography, which harms a large fraction of women and increases healthcare cost. This study aims to investigate the feasibility of helping reduce false-positive recalls by developing a new computer-aided diagnosis (CAD) scheme based on the analysis of global mammographic texture and density features computed from four-view images. Our database includes full-field digital mammography (FFDM) images acquired from 1052 recalled women (669 positive for cancer and 383 benign). Each case has four images: two craniocaudal (CC) and two mediolateral oblique (MLO) views. Our CAD scheme first computed global texture features related to the mammographic density distribution on the segmented breast regions of four images. Second, the computed features were given to two artificial neural network (ANN) classifiers that were separately trained and tested in a ten-fold cross-validation scheme on CC and MLO view images, respectively. Finally, two ANN classification scores were combined using a new adaptive scoring fusion method that automatically determined the optimal weights to assign to both views. CAD performance was tested using the area under a receiver operating characteristic curve (AUC). The AUC = 0.793  ±  0.026 was obtained for this four-view CAD scheme, which was significantly higher at the 5% significance level than the AUCs achieved when using only CC (p = 0.025) or MLO (p = 0.0004) view images, respectively. This study demonstrates that a quantitative assessment of global mammographic image texture and density features could provide useful and/or supplementary information to classify between malignant and benign cases among the recalled cases, which may eventually help reduce the false-positive recall rate in screening mammography.

  16. Iterative feature refinement for accurate undersampled MR image reconstruction

    Wang, Shanshan; Liu, Jianbo; Liu, Qiegen; Ying, Leslie; Liu, Xin; Zheng, Hairong; Liang, Dong

    2016-05-01

    Accelerating MR scan is of great significance for clinical, research and advanced applications, and one main effort to achieve this is the utilization of compressed sensing (CS) theory. Nevertheless, the existing CSMRI approaches still have limitations such as fine structure loss or high computational complexity. This paper proposes a novel iterative feature refinement (IFR) module for accurate MR image reconstruction from undersampled K-space data. Integrating IFR with CSMRI which is equipped with fixed transforms, we develop an IFR-CS method to restore meaningful structures and details that are originally discarded without introducing too much additional complexity. Specifically, the proposed IFR-CS is realized with three iterative steps, namely sparsity-promoting denoising, feature refinement and Tikhonov regularization. Experimental results on both simulated and in vivo MR datasets have shown that the proposed module has a strong capability to capture image details, and that IFR-CS is comparable and even superior to other state-of-the-art reconstruction approaches.

  17. Iterative feature refinement for accurate undersampled MR image reconstruction

    Wang, Shanshan; Liu, Jianbo; Liu, Xin; Zheng, Hairong; Liang, Dong; Liu, Qiegen; Ying, Leslie

    2016-01-01

    Accelerating MR scan is of great significance for clinical, research and advanced applications, and one main effort to achieve this is the utilization of compressed sensing (CS) theory. Nevertheless, the existing CSMRI approaches still have limitations such as fine structure loss or high computational complexity. This paper proposes a novel iterative feature refinement (IFR) module for accurate MR image reconstruction from undersampled K-space data. Integrating IFR with CSMRI which is equipped with fixed transforms, we develop an IFR-CS method to restore meaningful structures and details that are originally discarded without introducing too much additional complexity. Specifically, the proposed IFR-CS is realized with three iterative steps, namely sparsity-promoting denoising, feature refinement and Tikhonov regularization. Experimental results on both simulated and in vivo MR datasets have shown that the proposed module has a strong capability to capture image details, and that IFR-CS is comparable and even superior to other state-of-the-art reconstruction approaches. (paper)

  18. Imaging Characteristics of Venous Parenchymal Abnormalities.

    Arnoux, Audrey; Triquenot-Bagan, Aude; Andriuta, Daniela; Wallon, David; Guegan-Massardier, Evelyne; Leclercq, Claire; Martinaud, Olivier; Castier-Amouyel, Mélody; Godefroy, Olivier; Bugnicourt, Jean-Marc

    2017-12-01

    There are few published data on the patterns of parenchymal imaging abnormalities in a context of cerebral venous thrombosis (CVT). The objectives of the present study were to describe the patterns of parenchymal lesions associated with CVT and to determine the lesion sites. We included 44 consecutively hospitalized patients with CVT and parenchymal lesions on magnetic resonance imaging. The diagnosis of CVT had been confirmed by magnetic resonance imaging/magnetic resonance venography. Magnetic resonance imaging patterns for CVT were retrospectively analyzed with regard to the lesion's type, shape, and site. The most frequent stroke subtype was hemorrhagic ischemia (in 56.8% of cases), followed by intracerebral hematoma (in 22.72% of cases) and nonhemorrhagic ischemia (in 20.45% of cases). Although there were no significant differences between these 3 groups with regard to the clinical and radiological characteristics, we observed a nonsignificant trend ( P =0.08) toward a shorter time interval between hospital admission and magnetic resonance imaging for nonhemorrhagic stroke. The CVT parenchymal abnormalities were centered on 6 main foci and were related to the site of venous occlusion: (1) the inferior parietal lobule (n=20; 44.5%), associated mainly with occlusion of the transverse sinus (n=10) or pure cortical veins (n=10); (2) the inferior and posterior temporal regions (n=10; 22.75%), associated mainly with occlusion of the transverse sinus (n=9); (3) the parasagittal frontal region (n=6; 13.6%), associated mainly with occlusion of the superior sagittal sinus (n=4) or the transverse sinus (n=4); (4) the thalamus (n=5; 11.3%) associated with occlusion of the straight sinus (n=5); (5) the cerebellar hemisphere (n=2; 4.5%), associated in both cases with occlusion of the transverse sinus; and (6) the deep hemispheric regions (n=3; 6.8%), associated with occlusion of the superior sagittal sinus in all cases. Parenchymal lesions caused by CVT display specific

  19. A kernel-based multi-feature image representation for histopathology image classification

    Moreno J; Caicedo J Gonzalez F

    2010-01-01

    This paper presents a novel strategy for building a high-dimensional feature space to represent histopathology image contents. Histogram features, related to colors, textures and edges, are combined together in a unique image representation space using kernel functions. This feature space is further enhanced by the application of latent semantic analysis, to model hidden relationships among visual patterns. All that information is included in the new image representation space. Then, support vector machine classifiers are used to assign semantic labels to images. Processing and classification algorithms operate on top of kernel functions, so that; the structure of the feature space is completely controlled using similarity measures and a dual representation. The proposed approach has shown a successful performance in a classification task using a dataset with 1,502 real histopathology images in 18 different classes. The results show that our approach for histological image classification obtains an improved average performance of 20.6% when compared to a conventional classification approach based on SVM directly applied to the original kernel.

  20. A KERNEL-BASED MULTI-FEATURE IMAGE REPRESENTATION FOR HISTOPATHOLOGY IMAGE CLASSIFICATION

    J Carlos Moreno

    2010-09-01

    Full Text Available This paper presents a novel strategy for building a high-dimensional feature space to represent histopathology image contents. Histogram features, related to colors, textures and edges, are combined together in a unique image representation space using kernel functions. This feature space is further enhanced by the application of Latent Semantic Analysis, to model hidden relationships among visual patterns. All that information is included in the new image representation space. Then, Support Vector Machine classifiers are used to assign semantic labels to images. Processing and classification algorithms operate on top of kernel functions, so that, the structure of the feature space is completely controlled using similarity measures and a dual representation. The proposed approach has shown a successful performance in a classification task using a dataset with 1,502 real histopathology images in 18 different classes. The results show that our approach for histological image classification obtains an improved average performance of 20.6% when compared to a conventional classification approach based on SVM directly applied to the original kernel.

  1. MR imaging characteristics of protoplasmic astrocytomas

    Tay, Kevin L. [Royal Melbourne Hospital, Department of Radiology, Parkville, Victoria (Australia); Royal North Shore Hospital, Department of Radiology, St Leonards, New South Wales (Australia); Tsui, Alpha [Royal Melbourne Hospital, Department of Pathology, Parkville, Victoria (Australia); Phal, Pramit M.; Tress, Brian M. [Royal Melbourne Hospital, Department of Radiology, Parkville, Victoria (Australia); Drummond, Katharine J. [Royal Melbourne Hospital, Department of Neurosurgery, Parkville, Victoria (Australia)

    2011-06-15

    Protoplasmic astrocytomas are a poorly recognized and uncommon subtype of astrocytoma. While usually categorized with other low-grade gliomas, there is literature to suggest that protoplasmic astrocytomas have differences in biology compared to other gliomas in this group. This paper presents the MR imaging characteristics of a series of eight protoplasmic astrocytomas. We retrospectively reviewed MR images and histopathology of eight consecutive cases of histologically proven protoplasmic astrocytomas. Patients ranged from 17 to 51 years of age with a 5:3 male to female ratio. The tumors were located in the frontal or temporal lobes and tended to be large, well defined, and had a very high signal on T2 (close to cerebrospinal fluid). Generally, a large proportion of the tumor showed substantial signal suppression on T2 fluid-attenuated inversion recovery (FLAIR). Six of the eight lesions also demonstrated a partial or complete rim of reduced apparent diffusion coefficient (ADC) around the T2 FLAIR suppressing portion. The possibility that a primary cerebral neoplasm represents a protoplasmic astrocytoma should be considered in a patient with a large frontal or temporal tumor that has a very high signal on T2 with a large proportion of the tumor showing substantial T2 FLAIR suppression. A further clue is a partial or complete rim of reduced ADC. (orig.)

  2. Characteristic features of computed tomography (CT) in hepatic schistosomiasis japonica

    Sakemi, Taisuke; Sakai, Terufumi; Majima, Yasuo [Kurume Univ., Fukuoka (Japan). School of Medicine

    1984-06-01

    Characteristic finding of CT in the liver of hepatic schistosomiasis japonica were compared with histological changes. The study was made on 7 cases with schistosomatic liver cirrhosis (SLC) and 7 SLC cases with hepatocellular carcinoma (HCC). Characteristic CT findings were high density funicular patterns showing turtle shell appearance (4 cases), high density spotty patterns (3 cases) and both mixed patterns (7 cases). These patterns were not changed by contrast medium study. Funicular and mixed patterns were observed in both lobes of the liver, however, spotty patterns were seen only in the right lobe. It was difficult to distinguish liver tissue surrounded by funicular patterns from HCC lesion. Histopathological study of autopsied livers and CT scanning of thin cut livers revealed that high density funicular patterns represent deposits of calcified schistosomal ova in the fibrous septa.

  3. Characteristic features of the geomagnetic field of the Earth

    Petrova, G.N.

    1978-01-01

    The laws of the earth magnetism permitting to make a model of the earth magnetic field are popularly investigated. The modern methods of investigations used in the development of geomagnetism and determining the quantity and direction of the earth magnetic field from the moment of rock formation are described. Considered are the characteristic peculiarities of geomagnetic field: the inclination of the magnetic axis to the rotational axis of the Earth, the western drift of the geomagnetic field, the magnetic field asymmetry, its pole exchange and secular variations. The sources of the continuous magnetic field are investigated. The theory of hydromagnatic dinamo operating in the earth core is described. According to the invariance of the geomagnetic field characteristics it is possible to assume that the core has not significantly evolved for milliard years

  4. Imaging features of ductal plate malformations in adults

    Venkatanarasimha, N., E-mail: nandashettykv@yahoo.com [Department of Radiology, Derriford Hospital, Plymouth (United Kingdom); Thomas, R.; Armstrong, E.M.; Shirley, J.F.; Fox, B.M.; Jackson, S.A. [Department of Radiology, Derriford Hospital, Plymouth (United Kingdom)

    2011-11-15

    Ductal plate malformations, also known as fibrocystic liver diseases, are a group of congenital disorders resulting from abnormal embryogenesis of the biliary ductal system. The abnormalities include choledochal cyst, Caroli's disease and Caroli's syndrome, adult autosomal dominant polycystic liver disease, and biliary hamartoma. The hepatic lesions can be associated with renal anomalies such as autosomal recessive polycystic kidney disease (ARPKD), medullary sponge kidney, and nephronophthisis. A clear knowledge of the embryology and pathogenesis of the ductal plate is central to the understanding of the characteristic imaging appearances of these complex disorders. Accurate diagnosis of ductal plate malformations is important to direct appropriate clinical management and prevent misdiagnosis.

  5. BCGitis and BCGosis in children with primary immunodeficiency - imaging characteristics

    Shrot, Shai; Soudack, Michalle [Sheba Medical Center, Department of Diagnostic Imaging, Ramat-Gan (Israel); Tel Aviv University, Sackler School of Medicine, Tel Aviv (Israel); Barkai, Galia [Sheba Medical Center, Pediatric Infectious Diseases Unit, Safra Children' s Hospital, Tel-Hashomer (Israel); Ben-Shlush, Aviva [Sheba Medical Center, Department of Diagnostic Imaging, Ramat-Gan (Israel)

    2016-02-15

    When administered to an immune-compromised patient, BCG (Bacille Calmette-Guerin) can cause disseminated and life-threatening infections. To describe the imaging findings in children with primary immunodeficiency and BCG-related infections. We reviewed the imaging findings of children with primary immunodeficiency treated at a children's hospital during 2012-2014 with localized or disseminated BCG infection. Imaging modalities included US, CT and radiography. Nine children with primary immunodeficiency had clinical signs of post-vaccination BCGitis; seven of these children showed disseminated disease and two showed only regional lesions with characteristic ipsilateral lymphadenopathy. Overall, lymphadenopathy was the most prevalent feature (n = 8) and characteristically appeared as a ring-enhancing hypodense (CT) or hypoechoic (US) lesion. Visceral involvement with multiple abscesses appeared in the spleen (n = 2), liver (n = 1) and bones (n = 1). All lesions regressed following appropriate anti-tuberculosis treatment. BCG infection needs to be considered in children with typical findings and with suspected primary immunodeficiency. (orig.)

  6. Cystic synovial sarcomas: imaging features with clinical and histopathologic correlation

    Nakanishi, Hirofumi; Araki, Nobuhito [Department of Orthopedic Surgery, Osaka Medical Center for Cancer and Cardiovascular Diseases, 1-3-3, Nakamichi, Higashinari-Ku, 537-8511, Osaka (Japan); Sawai, Yuka [Department of Radiology, Osaka Medical Center for Cancer and Cardiovascular Diseases, Osaka (Japan); Kudawara, Ikuo [Department of Orthopedic Surgery, Osaka National Hospital, Osaka (Japan); Mano, Masayuki; Ishiguro, Shingo [Department of Pathology, Osaka Medical Center for Cancer and Cardiovascular Diseases, Osaka (Japan); Ueda, Takafumi; Yoshikawa, Hideki [Department of Orthopedic Surgery, Osaka University Graduate School of Medicine, Suita, Osaka (Japan)

    2003-12-01

    To characterize the radiological and clinicopathologic features of cystic synovial sarcoma. Seven patients with primary cystic synovial sarcoma were evaluated. Computed tomography (CT) and magnetic resonance (MR) imaging were undertaken at the first presentation. The diagnosis of synovial sarcoma was made on the basis of histological examinations followed by molecular analysis. Radiological and clinicopathologic findings were reviewed. CT showed well-defined soft tissue mass without cortical bone erosion and invasion. Calcification was seen at the periphery of the mass in three cases. T2-weighted MR images showed multilocular inhomogeneous intensity mass in all cases, five of which showed fluid-fluid levels. On gross appearance, old and/or fresh hematomas were detected in six cases. In the one remaining case, microscopic hemorrhage in the cystic lumen was proven. Four cases had poorly differentiated areas. In five cases prominent hemangiopericytomatous vasculature was observed. Histologic grade was intermediate in one tumor and high in six. One case had a history of misdiagnosis for tarsal tunnel syndrome, one for lymphadenopathy, two for sciatica and two for hematoma. All cystic synovial sarcomas demonstrated multilocularity with well-circumscribed walls and internal septae. Synovial sarcoma should be taken into consideration in patients with deeply situated multicystic mass with triple signal intensity on T2-weighted MR imaging. (orig.)

  7. Cystic synovial sarcomas: imaging features with clinical and histopathologic correlation

    Nakanishi, Hirofumi; Araki, Nobuhito; Sawai, Yuka; Kudawara, Ikuo; Mano, Masayuki; Ishiguro, Shingo; Ueda, Takafumi; Yoshikawa, Hideki

    2003-01-01

    To characterize the radiological and clinicopathologic features of cystic synovial sarcoma. Seven patients with primary cystic synovial sarcoma were evaluated. Computed tomography (CT) and magnetic resonance (MR) imaging were undertaken at the first presentation. The diagnosis of synovial sarcoma was made on the basis of histological examinations followed by molecular analysis. Radiological and clinicopathologic findings were reviewed. CT showed well-defined soft tissue mass without cortical bone erosion and invasion. Calcification was seen at the periphery of the mass in three cases. T2-weighted MR images showed multilocular inhomogeneous intensity mass in all cases, five of which showed fluid-fluid levels. On gross appearance, old and/or fresh hematomas were detected in six cases. In the one remaining case, microscopic hemorrhage in the cystic lumen was proven. Four cases had poorly differentiated areas. In five cases prominent hemangiopericytomatous vasculature was observed. Histologic grade was intermediate in one tumor and high in six. One case had a history of misdiagnosis for tarsal tunnel syndrome, one for lymphadenopathy, two for sciatica and two for hematoma. All cystic synovial sarcomas demonstrated multilocularity with well-circumscribed walls and internal septae. Synovial sarcoma should be taken into consideration in patients with deeply situated multicystic mass with triple signal intensity on T2-weighted MR imaging. (orig.)

  8. Featured Image: A Detailed Look at the Crab Nebula

    Kohler, Susanna

    2017-07-01

    Planning on watching fireworks tomorrow? Heres an astronomical firework to help you start the celebrations! A new study has stunningly detailed the Crab Nebula (click for a closer look), a nebula 6,500 light-years away thought to have been formedby a supernova explosion and the subsequent ultrarelativistic wind emitted by the pulsar at its heart. Led by Gloria Dubner (University of Buenos Aires), the authors of this study obtained new observations of the Crab Nebula from five different telescopes. They compiled these observations to compare the details of the nebulas structure across different wavelengths, which allowedthem to learnabout the sources of various features within the nebula. In the images above, thetop left shows the 3 GHz data from the Very Large Array (radio). Moving clockise, the radio data (shown in red) is composited with: infrared data from Spitzer Space Telescope, optical continuum from Hubble Space Telescope, 500-nm optical datafrom Hubble, and ultraviolet data from XMM-Newton. The final two images are of the nebula center, and they are composites of the radio imagewith X-ray data from Chandra and near-infrared data from Hubble. To read more about what Dubner and collaborators learned (and to see more spectacular images!), check out the paper below.CitationG. Dubner et al 2017 ApJ 840 82. doi:10.3847/1538-4357/aa6983

  9. Biomedical imaging modality classification using combined visual features and textual terms.

    Han, Xian-Hua; Chen, Yen-Wei

    2011-01-01

    We describe an approach for the automatic modality classification in medical image retrieval task of the 2010 CLEF cross-language image retrieval campaign (ImageCLEF). This paper is focused on the process of feature extraction from medical images and fuses the different extracted visual features and textual feature for modality classification. To extract visual features from the images, we used histogram descriptor of edge, gray, or color intensity and block-based variation as global features and SIFT histogram as local feature. For textual feature of image representation, the binary histogram of some predefined vocabulary words from image captions is used. Then, we combine the different features using normalized kernel functions for SVM classification. Furthermore, for some easy misclassified modality pairs such as CT and MR or PET and NM modalities, a local classifier is used for distinguishing samples in the pair modality to improve performance. The proposed strategy is evaluated with the provided modality dataset by ImageCLEF 2010.

  10. Dysmorphic Facial Features and Other Clinical Characteristics in Two Patients with PEX1 Gene Mutations

    Gunduz, Mehmet

    2016-01-01

    Peroxisomal disorders are a group of genetically heterogeneous metabolic diseases related to dysfunction of peroxisomes. Dysmorphic features, neurological abnormalities, and hepatic dysfunction can be presenting signs of peroxisomal disorders. Here we presented dysmorphic facial features and other clinical characteristics in two patients with PEX1 gene mutation. Follow-up periods were 3.5 years and 1 year in the patients. Case I was one-year-old girl that presented with neurodevelopmental delay, hepatomegaly, bilateral hearing loss, and visual problems. Ophthalmologic examination suggested septooptic dysplasia. Cranial magnetic resonance imaging (MRI) showed nonspecific gliosis at subcortical and periventricular deep white matter. Case II was 2.5-year-old girl referred for investigation of global developmental delay and elevated liver enzymes. Ophthalmologic examination findings were consistent with bilateral nystagmus and retinitis pigmentosa. Cranial MRI was normal. Dysmorphic facial features including broad nasal root, low set ears, downward slanting eyes, downward slanting eyebrows, and epichantal folds were common findings in two patients. Molecular genetic analysis indicated homozygous novel IVS1-2A>G mutation in Case I and homozygous p.G843D (c.2528G>A) mutation in Case II in the PEX1 gene. Clinical findings and developmental prognosis vary in PEX1 gene mutation. Kabuki-like phenotype associated with liver pathology may indicate Zellweger spectrum disorders (ZSD). PMID:27882258

  11. Imaging and applied optics: introduction to the feature issue.

    Zalevsky, Zeev; Arnison, Matthew R; Javidi, Bahram; Testorf, Markus

    2018-03-01

    This special issue of Applied Optics contains selected papers from OSA's Imaging Congress with particular emphasis on work from mathematics in imaging, computational optical sensing and imaging, imaging systems and applications, and 3D image acquisition and display.

  12. Breast tissue classification in digital breast tomosynthesis images using texture features: a feasibility study

    Kontos, Despina; Berger, Rachelle; Bakic, Predrag R.; Maidment, Andrew D. A.

    2009-02-01

    Mammographic breast density is a known breast cancer risk factor. Studies have shown the potential to automate breast density estimation by using computerized texture-based segmentation of the dense tissue in mammograms. Digital breast tomosynthesis (DBT) is a tomographic x-ray breast imaging modality that could allow volumetric breast density estimation. We evaluated the feasibility of distinguishing between dense and fatty breast regions in DBT using computer-extracted texture features. Our long-term hypothesis is that DBT texture analysis can be used to develop 3D dense tissue segmentation algorithms for estimating volumetric breast density. DBT images from 40 women were analyzed. The dense tissue area was delineated within each central source projection (CSP) image using a thresholding technique (Cumulus, Univ. Toronto). Two (2.5cm)2 ROIs were manually selected: one within the dense tissue region and another within the fatty region. Corresponding (2.5cm)3 ROIs were placed within the reconstructed DBT images. Texture features, previously used for mammographic dense tissue segmentation, were computed. Receiver operating characteristic (ROC) curve analysis was performed to evaluate feature classification performance. Different texture features appeared to perform best in the 3D reconstructed DBT compared to the 2D CSP images. Fractal dimension was superior in DBT (AUC=0.90), while contrast was best in CSP images (AUC=0.92). We attribute these differences to the effects of tissue superimposition in CSP and the volumetric visualization of the breast tissue in DBT. Our results suggest that novel approaches, different than those conventionally used in projection mammography, need to be investigated in order to develop DBT dense tissue segmentation algorithms for estimating volumetric breast density.

  13. CT imaging features of tuberculous spondylitis in children

    Song Min; Liu Wen; Fang Weijun; Wang Fukang; Li Ziping

    2009-01-01

    Objective: To investigate CT imaging features of tuberculous spondylitis in children. Methods: The CT imagings of two groups of patients with Tuberculous Spondylitis between January 2004 and March 2008 were retrospectively reviewed. One group included 28 children from 0 to 14 years old. Another group included 159 adults. All the patients were diagnosed as tuberculous spondylitis by pathology or biopsy, or by anti-turboelectric therapy. The CT imagings of the two groups were read retrospectively, including infections of vertebras and its appendix, the proportion of the total length of paravertebral abscess to the height of relative vertebra, the information of paravertebral abscess and dura mate of spinal cord and nerve root compression. Results The ratio of kyphosis in children group was 75% (21/28), higher than that in adults'. Tuberculous spondylitis in children was most often involved thoracic vertebra (53.7%,51/95). In children, involvement was more often seen than that of cervical vertebra and lumbar. The ratio of tuberculous spondylitis of children's cervical vertebrae was 10.5% (10/95)and of lumbar was 31.6% (30/95, while in adults that of cervical vertebrae was 3.3% (16/479)and of lumbar was 44.5% (213/479). There was statistical difference between them. The percentages of central type of tuberculous vertebral osteitis in chlidren was 57.1% (16/28)and was different with that in adults'(P=0.001 0.05). The incidence of dura mate of spinal cord or nerve root compression in children was 78.6%(22/28), much higher than that in adults (49.7%(79/159), P=0.005 <0.05). Conclusion: Special features of tuberculous spondylitis in childrencan be observed on CT imaging, kyphosis is often seen. The incidence of tuberculous spondylitis of thoracic vertebra and cervical vertebrae is high, central type of tuberculous vertebral osteitis in children is more popular than that in adults, but there is higher ratio of dura mate of spinal cord or nerve root compression in children

  14. Characteristic features of net information measures for constrained Coulomb potentials

    Patil, S H; Sen, K D; Watson, N A; Jr, H E Montgomery

    2007-01-01

    The dimensional analyses of the position and momentum variance based quantum mechanical Heisenberg uncertainty measure and the other useful net entropic information measures for the bound states of two constrained Coulomb potentials are reported for the first time. The potentials describe an electron moving in the central field due to a nucleus of charge Z with radius R defining the constraints as (a) the truncated potential given by -Z/(r n +R n ) 1/n , and (b) the radius of the impenetrable spherical wall. The net information measures for the two potentials are explicitly shown to be independent of the scaling of the set [Z, R] at a fixed value of ZR. Analytic proof is presented, for the first time, showing the presence of a characteristic extremum in the variation of the net information entropy as a function of the radius R with its location scaling as Z -1 . Numerical results are presented which support the validity of the scaling properties

  15. SU-E-J-237: Image Feature Based DRR and Portal Image Registration

    Wang, X; Chang, J [NY Weill Cornell Medical Ctr, NY (United States)

    2014-06-01

    Purpose: Two-dimensional (2D) matching of the kV X-ray and digitally reconstructed radiography (DRR) images is an important setup technique for image-guided radiotherapy (IGRT). In our clinics, mutual information based methods are used for this purpose on commercial linear accelerators, but with often needs for manual corrections. This work proved the feasibility that feature based image transform can be used to register kV and DRR images. Methods: The scale invariant feature transform (SIFT) method was implemented to detect the matching image details (or key points) between the kV and DRR images. These key points represent high image intensity gradients, and thus the scale invariant features. Due to the poor image contrast from our kV image, direct application of the SIFT method yielded many detection errors. To assist the finding of key points, the center coordinates of the kV and DRR images were read from the DICOM header, and the two groups of key points with similar relative positions to their corresponding centers were paired up. Using these points, a rigid transform (with scaling, horizontal and vertical shifts) was estimated. We also artificially introduced vertical and horizontal shifts to test the accuracy of our registration method on anterior-posterior (AP) and lateral pelvic images. Results: The results provided a satisfactory overlay of the transformed kV onto the DRR image. The introduced vs. detected shifts were fit into a linear regression. In the AP image experiments, linear regression analysis showed a slope of 1.15 and 0.98 with an R2 of 0.89 and 0.99 for the horizontal and vertical shifts, respectively. The results are 1.2 and 1.3 with R2 of 0.72 and 0.82 for the lateral image shifts. Conclusion: This work provided an alternative technique for kV to DRR alignment. Further improvements in the estimation accuracy and image contrast tolerance are underway.

  16. Some characteristic features of Englishes in Lesotho, Malawi and Swaziland

    Kamwangamalu, Nkonko

    2003-12-01

    Full Text Available This article discusses the function of the English and the local form it takes in three Southern African countries, namely Lesotho, Malawi and Swaziland. English was introduced in these countries as a result of contacts between the indigenous people and British traders and missionaries during the 19th century. English, which had initially been the language of trade, became the official language in colonial administration. Since then, English has had shifting but always important roles alongside the indigenous languages. As usually happens with languages in contact, there has been a fair amount of mutual influence. In this article, we examine some of the changes in English, concentrating on the usage of non-L1 speakers. Kachru (1982 speaks of this process as ‘indigenisation’: changing the language to suit the communicative needs of non-native users in new, un-English contexts. That explanation is only partly satisfactory. Languages influence one another in sophisticated sociolinguistic ways that require more penetrating analysis. In this article, we are concerned mainly with examining and describing the transfer of syntactic, phonological, lexical and semantic features from indigenous languages into English. From observation, most of the Africanisms that apply in the three countries discussed, particularly in Malawi, could well apply to Zambia and Zimbabwe as well. Finally, we reflect on some future possibilities.

  17. Imaging features of lower limb malformations above the foot.

    Bergère, A; Amzallag-Bellenger, E; Lefebvre, G; Dieux-Coeslier, A; Mezel, A; Herbaux, B; Boutry, N

    2015-09-01

    Lower limb malformations are generally isolated or sporadic events. However, they are sometimes associated with other anomalies of the bones and/or viscera in patients with constitutional syndromes or disorders of the skeleton. This paper reviews the main imaging features of these abnormalities, which generally exhibit a broad spectrum. This paper focuses on several different bone malformations: proximal focal femoral deficiency, congenital short femur and femoral duplication for the femur, tibial hemimelia (aplasia/hypoplasia of the tibia) and congenital bowing for the tibia, fibular hemimelia (aplasia/hypoplasia) for the fibula, and aplasia, hypoplasia and congenital dislocation for the patella. Copyright © 2015 Éditions françaises de radiologie. Published by Elsevier Masson SAS. All rights reserved.

  18. Geomorphic domains and linear features on Landsat images, Circle Quadrangle, Alaska

    Simpson, S.L.

    1984-01-01

    A remote sensing study using Landsat images was undertaken as part of the Alaska Mineral Resource Assessment Program (AMRAP). Geomorphic domains A and B, identified on enhanced Landsat images, divide Circle quadrangle south of Tintina fault zone into two regional areas having major differences in surface characteristics. Domain A is a roughly rectangular, northeast-trending area of relatively low relief and simple, widely spaced drainages, except where igneous rocks are exposed. In contrast, domain B, which bounds two sides of domain A, is more intricately dissected showing abrupt changes in slope and relatively high relief. The northwestern part of geomorphic domain A includes a previously mapped tectonostratigraphic terrane. The southeastern boundary of domain A occurs entirely within the adjoining tectonostratigraphic terrane. The sharp geomorphic contrast along the southeastern boundary of domain A and the existence of known faults along this boundary suggest that the southeastern part of domain A may be a subdivision of the adjoining terrane. Detailed field studies would be necessary to determine the characteristics of the subdivision. Domain B appears to be divisible into large areas of different geomorphic terrains by east-northeast-trending curvilinear lines drawn on Landsat images. Segments of two of these lines correlate with parts of boundaries of mapped tectonostratigraphic terranes. On Landsat images prominent north-trending lineaments together with the curvilinear lines form a large-scale regional pattern that is transected by mapped north-northeast-trending high-angle faults. The lineaments indicate possible lithlogic variations and/or structural boundaries. A statistical strike-frequency analysis of the linear features data for Circle quadrangle shows that northeast-trending linear features predominate throughout, and that most northwest-trending linear features are found south of Tintina fault zone. A major trend interval of N.64-72E. in the linear

  19. Magnetic resonance imaging features of complex Chiari malformation variant of Chiari 1 malformation

    Moore, Hannah E. [Primary Children' s Medical Center, Department of Medical Imaging, Salt Lake City, UT (United States); Moore, Kevin R. [University of Utah School of Medicine, Department of Radiology, Salt Lake City, UT (United States); Primary Children' s Medical Center, Department of Medical Imaging, Salt Lake City, UT (United States)

    2014-11-15

    those with Chiari 1 malformation. Characteristic imaging features of complex Chiari malformation, especially obex level, permit its distinction from the more common uncomplicated Chiari 1 malformation. (orig.)

  20. BP network for atorvastatin effect evaluation from ultrasound images features classification

    Fang, Mengjie; Yang, Xin; Liu, Yang; Xu, Hongwei; Liang, Huageng; Wang, Yujie; Ding, Mingyue

    2013-10-01

    Atherosclerotic lesions at the carotid artery are a major cause of emboli or atheromatous debris, resulting in approximately 88% of ischemic strokes in the USA in 2006. Stroke is becoming the most common cause of death worldwide, although patient management and prevention strategies have reduced stroke rate considerably over the past decades. Many research studies have been carried out on how to quantitatively evaluate local arterial effects for potential carotid disease treatments. As an inexpensive, convenient and fast means of detection, ultrasonic medical testing has been widespread in the world, so it is very practical to use ultrasound technology in the prevention and treatment of carotid atherosclerosis. This paper is dedicated to this field. Currently, many ultrasound image characteristics on carotid plaque have been proposed. After screening a large number of features (including 26 morphological and 85 texture features), we have got six shape characteristics and six texture characteristics in the combination. In order to test the validity and accuracy of these combined features, we have established a Back-Propagation (BP) neural network to classify atherosclerosis plaques between atorvastatin group and placebo group. The leave-one-case-out protocol was utilized on a database of 768 carotid ultrasound images of 12 patients (5 subjects of placebo group and 7 subjects of atorvastatin group) for the evaluation. The classification results showed that the combined features and classification have good recognition ability, with the overall accuracy 83.93%, sensitivity 82.14%, specificity 85.20%, positive predictive value 79.86%, negative predictive value 86.98%, Matthew's correlation coefficient 67.08%, and Youden's index 67.34%. And the receiver operating characteristic (ROC) curve in our test also performed well.

  1. Steel syndrome: dislocated hips and radial heads, carpal coalition, scoliosis, short stature, and characteristic facial features.

    Flynn, John M; Ramirez, Norman; Betz, Randal; Mulcahey, Mary Jane; Pino, Franz; Herrera-Soto, Jose A; Carlo, Simon; Cornier, Alberto S

    2010-01-01

    A syndrome of children with short stature, bilateral hip dislocations, radial head dislocations, carpal coalitions, scoliosis, and cavus feet in Puerto Rican children, was reported by Steel et al in 1993. The syndrome was described as a unique entity with dismal results after conventional treatment of dislocated hips. The purpose of this study is to reevaluate this patient population with a longer follow-up and delineate the clinical and radiologic features, treatment outcomes, and the genetic characteristics. This is a retrospective cohort study of 32 patients in whom we evaluated the clinical, imaging data, and genetic characteristics. We compare the findings and quality of life in patients with this syndrome who have had attempts at reduction of the hips versus those who did not have the treatment. Congenital hip dislocations were present in 100% of the patients. There was no attempt at reduction in 39% (25/64) of the hips. In the remaining 61% (39/64), the hips were treated with a variety of modalities fraught with complications. Of those treated, 85% (33/39) remain dislocated, the rest of the hips continue subluxated with acetabular dysplasia and pain. The group of hips that were not treated reported fewer complaints and limitation in daily activities compared with the hips that had attempts at reduction. Steel syndrome is a distinct clinical entity characterized by short stature, bilateral hip and radial head dislocation, carpal coalition, scoliosis, cavus feet, and characteristic facial features with dismal results for attempts at reduction of the hips. Prognostic Study Level II.

  2. The imaging feature of multidrug-resistant tuberculosis

    Yang Jun; Zhou Xinhua; Li Xi; Fu Yuhong; Zheng Suhua; Lv Pingxin; Ma Daqing

    2004-01-01

    Objective: To evaluate the imaging features of multidrug-resistant tuberculosis by collecting multidrug-resistant tuberculosis verified by test of drug-sensitivity, which defined as resistance to three anti-tuberculosis drugs. Methods:Fifty-one cases of multidrug-resistant tuberculosis were categorized as group of observed, and 46 cases of drug sensitive tuberculosis were categorized as control. Cultures were positive for Mycobacterium tuberculosis in all cases with no other illness such as diabetes mellitus. All patients had chest radiographs available for review, while 64 cases had tomography and 30 cases had CT during the same time. All images were analyzed by three of the radiologists, disagreement among them was discussed and a consensus was reached. Results: There was no difference in the distribution of lesions between the multidrug-resistant tuberculosis group and control group. However, the radiological findings in the multidrug-resistant tuberculosis group were significantly more common than in control group, such as multiple nodules (10 cases), disseminated foci (23 cases), cavity (9 cases), and complications (10 cases). Comparing the dynamic cases, deteriorating cases were more commonly seen in observed group than in control group, while improved cases were less in observed group than in control group. Conclusion: Multidrug-resistant tuberculosis is the most serious tuberculosis, which is characterized with significant activity, more disseminated foci, cavity, and complications. The lesion deteriorated while correct anti-tuberculosis treatment is applied. (authors)

  3. Radiometric and geometric characteristics of Pleiades images

    Jacobsen, K.; Topan, H.; Cam, A.; Özendi, M.; Oruc, M.

    2014-11-01

    Pleiades images are distributed with 50 cm ground sampling distance (GSD) even if the physical resolution for nadir images is just 70 cm. By theory this should influence the effective GSD determined by means of point spread function at image edges. Nevertheless by edge enhancement the effective GSD can be improved, but this should cause enlarged image noise. Again image noise can be reduced by image restoration. Finally even optimized image restoration cannot improve the image information from 70 cm to 50 cm without loss of details, requiring a comparison of Pleiades image details with other very high resolution space images. The image noise has been determined by analysis of the whole images for any sub-area with 5 pixels times 5 pixels. Based on the standard deviation of grey values in the small sub-areas the image noise has been determined by frequency analysis. This leads to realistic results, checked by test targets. On the other hand the visual determination of image noise based on apparently homogenous sub-areas results in too high values because the human eye is not able to identify small grey value differences - it is limited to just approximately 40 grey value steps over the available gray value range, so small difference in grey values cannot be seen, enlarging results of a manual noise determination. A tri-stereo combination of Pleiades 1A in a mountainous, but partially urban, area has been analyzed and compared with images of the same area from WorldView-1, QuickBird and IKONOS. The image restoration of the Pleiades images is very good, so the effective image resolution resulted in a factor 1.0, meaning that the effective resolution corresponds to the nominal resolution of 50 cm. This does not correspond to the physical resolution of 70 cm, but by edge enhancement the steepness of the grey value profile across the edge can be enlarged, reducing the width of the point spread function. Without additional filtering edge enhancement enlarges the image

  4. Enhancement and feature extraction of RS images from seismic area and seismic disaster recognition technologies

    Zhang, Jingfa; Qin, Qiming

    2003-09-01

    Many types of feature extracting of RS image are analyzed, and the work procedure of pattern recognizing in RS images of seismic disaster is proposed. The aerial RS image of Tangshan Great Earthquake is processed, and the digital features of various typical seismic disaster on the RS image is calculated.

  5. Application of eigen value expansion to feature extraction from MRI images

    Kinosada, Yasutomi; Takeda, Kan; Nakagawa, Tsuyoshi

    1991-01-01

    The eigen value expansion technique was utilized for feature extraction of magnetic resonance (MR) images. The eigen value expansion is an orthonormal transformation method which decomposes a set of images into some statistically uncorrelated images. The technique was applied to MR images obtained with various imaging parameters at the same anatomical site. It generated one mean image and another set of images called bases for the images. Each basis corresponds to a feature in the images. A basis is, therefore, utilized for the feature extraction from MR images and a weighted sum of bases is also used for the feature enhancement. Furthermore, any MR image with specific feature can be obtained from a linear combination of the mean image and all of the bases. Images of hemorrhaged brain with a spin echo sequence and a series of cinematic cerebro spinal fluid flow images with ECG gated gradient refocused echo sequence were employed to estimate the ability of the feature extraction and the contrast enhancement. Results showed us that proposed application of an eigen value expansion technique to the feature extraction of MR images is good enough to clinical use and superior to other feature extraction methods such as producing a calculated MR image with a given TR and TE or the matched-filter method in processing speed and reproducibility of results. (author)

  6. SU-F-R-35: Repeatability of Texture Features in T1- and T2-Weighted MR Images

    Mahon, R; Weiss, E; Karki, K; Hugo, G; Ford, J

    2016-01-01

    Purpose: To evaluate repeatability of lung tumor texture features from inspiration/expiration MR image pairs for potential use in patient specific care models and applications. Repeatability is a desirable and necessary characteristic of features included in such models. Methods: T1-weighted Volumetric Interpolation Breath-Hold Examination (VIBE) and/or T2-weighted MRI scans were acquired for 15 patients with non-small cell lung cancer before and during radiotherapy for a total of 32 and 34 same session inspiration-expiration breath-hold image pairs respectively. Bias correction was applied to the VIBE (VIBE-BC) and T2-weighted (T2-BC) images. Fifty-nine texture features at five wavelet decomposition ratios were extracted from the delineated primary tumor including: histogram(HIST), gray level co-occurrence matrix(GLCM), gray level run length matrix(GLRLM), gray level size zone matrix(GLSZM), and neighborhood gray tone different matrix (NGTDM) based features. Repeatability of the texture features for VIBE, VIBE-BC, T2-weighted, and T2-BC image pairs was evaluated by the concordance correlation coefficient (CCC) between corresponding image pairs, with a value greater than 0.90 indicating repeatability. Results: For the VIBE image pairs, the percentage of repeatable texture features by wavelet ratio was between 20% and 24% of the 59 extracted features; the T2-weighted image pairs exhibited repeatability in the range of 44–49%. The percentage dropped to 10–20% for the VIBE-BC images, and 12–14% for the T2-BC images. In addition, five texture features were found to be repeatable in all four image sets including two GLRLM, two GLZSM, and one NGTDN features. No single texture feature category was repeatable among all three image types; however, certain categories performed more consistently on a per image type basis. Conclusion: We identified repeatable texture features on T1- and T2-weighted MRI scans. These texture features should be further investigated for use

  7. SU-F-R-35: Repeatability of Texture Features in T1- and T2-Weighted MR Images

    Mahon, R; Weiss, E; Karki, K; Hugo, G [Virginia Commonwealth University, Richmond, VA (United States); Ford, J [University of Miami Miller School of Medicine, Miami, FL (United States)

    2016-06-15

    Purpose: To evaluate repeatability of lung tumor texture features from inspiration/expiration MR image pairs for potential use in patient specific care models and applications. Repeatability is a desirable and necessary characteristic of features included in such models. Methods: T1-weighted Volumetric Interpolation Breath-Hold Examination (VIBE) and/or T2-weighted MRI scans were acquired for 15 patients with non-small cell lung cancer before and during radiotherapy for a total of 32 and 34 same session inspiration-expiration breath-hold image pairs respectively. Bias correction was applied to the VIBE (VIBE-BC) and T2-weighted (T2-BC) images. Fifty-nine texture features at five wavelet decomposition ratios were extracted from the delineated primary tumor including: histogram(HIST), gray level co-occurrence matrix(GLCM), gray level run length matrix(GLRLM), gray level size zone matrix(GLSZM), and neighborhood gray tone different matrix (NGTDM) based features. Repeatability of the texture features for VIBE, VIBE-BC, T2-weighted, and T2-BC image pairs was evaluated by the concordance correlation coefficient (CCC) between corresponding image pairs, with a value greater than 0.90 indicating repeatability. Results: For the VIBE image pairs, the percentage of repeatable texture features by wavelet ratio was between 20% and 24% of the 59 extracted features; the T2-weighted image pairs exhibited repeatability in the range of 44–49%. The percentage dropped to 10–20% for the VIBE-BC images, and 12–14% for the T2-BC images. In addition, five texture features were found to be repeatable in all four image sets including two GLRLM, two GLZSM, and one NGTDN features. No single texture feature category was repeatable among all three image types; however, certain categories performed more consistently on a per image type basis. Conclusion: We identified repeatable texture features on T1- and T2-weighted MRI scans. These texture features should be further investigated for use

  8. Imagiologic features and the relative imaging factors in hepatolenticular degeneration

    Gao Wenqing; Liu Pengcheng; Huang Rong; Yan Weiqiang; Zhao Yan; Liu Yuanjian; Luo Lili; Zou Liqiu; Liu Hanqiao

    2002-01-01

    Objective: To study the CT, MR and ultrasound features of hepatolenticular degeneration (HLD), and investigate relative factors affecting the imaging manifestations. Methods: Fifty-four HLD were reported, and the 35 male and 19 female patients ranged in the age from 3 to 40 years. CT was performed in 29 patients, MR in 11, both CT and MR in 5, ultrasound in 26. Six cases were hospitalized for 3 times, and 9 for twice. Results: (1) The putamen was affected on MR in all cases (100%), the caudate nucleus in 8. The thalami in 5, the globus pallidum in 2, the red nucleus in 2, the substantia nigra in 3, the midbrain in 1, the pons in 2, the white matter of frontal lobi in 1. According to the different basal ganglia involved in brain, resembling 'woodpecker' or 'butterfly spreading the wing' in appearance were showed on the MR images respectively. (2) Positive signs were found by CT scans in 18 cases (72%), but negative in 7 cases (28%). It is important manifestation that low density in brain occurred bilaterally and symmetrically. (3) The sonographic changes of chronic liver disease were showed on US in all 26 cases. Among the number, 12 cases were regarded as cirrhosis at the same time. Conclusion: (1) T 2 signal intensity and CT density changes are often not parallel to the clinical symptoms. T 1 WI is suitable for the follow-up, but quantitative analysis is still difficult. (2) Damage of liver occurs almost in all HLD, and earlier than that of brain. On the early stage, the liver damage is reversible, the brain lesions are symmetric. Moderately, the liver damage changes static. Lately, the brain presents atrophic. (3) The investigation suggests that there are 4 factors affecting CT and MR imaging features: the systemic disease resulting from metabolic disorder and the selected affinity caused by gene defect, deposition of copper together with cellular damage, endogenous and autonomous discharge of copper and histiocyte repaired, and extro-generate expelled copper

  9. Fundus Image Features Extraction for Exudate Mining in Coordination with Content Based Image Retrieval: A Study

    Gururaj, C.; Jayadevappa, D.; Tunga, Satish

    2018-06-01

    Medical field has seen a phenomenal improvement over the previous years. The invention of computers with appropriate increase in the processing and internet speed has changed the face of the medical technology. However there is still scope for improvement of the technologies in use today. One of the many such technologies of medical aid is the detection of afflictions of the eye. Although a repertoire of research has been accomplished in this field, most of them fail to address how to take the detection forward to a stage where it will be beneficial to the society at large. An automated system that can predict the current medical condition of a patient after taking the fundus image of his eye is yet to see the light of the day. Such a system is explored in this paper by summarizing a number of techniques for fundus image features extraction, predominantly hard exudate mining, coupled with Content Based Image Retrieval to develop an automation tool. The knowledge of the same would bring about worthy changes in the domain of exudates extraction of the eye. This is essential in cases where the patients may not have access to the best of technologies. This paper attempts at a comprehensive summary of the techniques for Content Based Image Retrieval (CBIR) or fundus features image extraction, and few choice methods of both, and an exploration which aims to find ways to combine these two attractive features, and combine them so that it is beneficial to all.

  10. Fundus Image Features Extraction for Exudate Mining in Coordination with Content Based Image Retrieval: A Study

    Gururaj, C.; Jayadevappa, D.; Tunga, Satish

    2018-02-01

    Medical field has seen a phenomenal improvement over the previous years. The invention of computers with appropriate increase in the processing and internet speed has changed the face of the medical technology. However there is still scope for improvement of the technologies in use today. One of the many such technologies of medical aid is the detection of afflictions of the eye. Although a repertoire of research has been accomplished in this field, most of them fail to address how to take the detection forward to a stage where it will be beneficial to the society at large. An automated system that can predict the current medical condition of a patient after taking the fundus image of his eye is yet to see the light of the day. Such a system is explored in this paper by summarizing a number of techniques for fundus image features extraction, predominantly hard exudate mining, coupled with Content Based Image Retrieval to develop an automation tool. The knowledge of the same would bring about worthy changes in the domain of exudates extraction of the eye. This is essential in cases where the patients may not have access to the best of technologies. This paper attempts at a comprehensive summary of the techniques for Content Based Image Retrieval (CBIR) or fundus features image extraction, and few choice methods of both, and an exploration which aims to find ways to combine these two attractive features, and combine them so that it is beneficial to all.

  11. Skeletal deformities of acardius anceps: the gross and imaging features

    Chen Chihping [Dept. of Medical Research, Mackay Memorial Hospital, Taipei (Taiwan, Province of China); Shih Shinlin [Dept. of Radiology, Mackay Memorial Hospital, Taipei (Taiwan, Province of China); Liu Fenfen [Dept. of Medical Research, Mackay Memorial Hospital, Taipei (Taiwan, Province of China); Jan Sheauwen [Dept. of Medical Research, Mackay Memorial Hospital, Taipei (Taiwan, Province of China); Lin Yunnan [Dept. of Pathology, Mackay Memorial Hospital, Taipei (Taiwan, Province of China); Lan Chungchi [Dept. of Obstetrics and Gynecology, Mackay Memorial Hospital, Taipei (Taiwan, Province of China)

    1997-03-01

    A morphology based imaging review is presented of the characteristic skeletal deformities associated with acardius anceps in three acardiac twins. These fetuses demonstrated poorly developed skulls, limb reduction defects, and phocomelia of the upper limbs, as well as narrow thoracic cages with or without the complete development of ribs, clavicles, scapulae, and cervical, thoracic, or lumbar vertebrae. However, their lower limbs and pelvic girdles were almost normal. The authors conclude that skeletal development is likely to be jeopardized in the area adjacent to the heart and in the cephalic portion of the body in fetuses with acardius anceps, and suggest vascular deficiency and hypoperfusion as pathogenetic mechanisms in this type of skeletal deformity. (orig.)

  12. Skeletal deformities of acardius anceps: the gross and imaging features

    Chen Chihping; Shih Shinlin; Liu Fenfen; Jan Sheauwen; Lin Yunnan; Lan Chungchi

    1997-01-01

    A morphology based imaging review is presented of the characteristic skeletal deformities associated with acardius anceps in three acardiac twins. These fetuses demonstrated poorly developed skulls, limb reduction defects, and phocomelia of the upper limbs, as well as narrow thoracic cages with or without the complete development of ribs, clavicles, scapulae, and cervical, thoracic, or lumbar vertebrae. However, their lower limbs and pelvic girdles were almost normal. The authors conclude that skeletal development is likely to be jeopardized in the area adjacent to the heart and in the cephalic portion of the body in fetuses with acardius anceps, and suggest vascular deficiency and hypoperfusion as pathogenetic mechanisms in this type of skeletal deformity. (orig.)

  13. Feature Extraction in Sequential Multimedia Images: with Applications in Satellite Images and On-line Videos

    Liang, Yu-Li

    Multimedia data is increasingly important in scientific discovery and people's daily lives. Content of massive multimedia is often diverse and noisy, and motion between frames is sometimes crucial in analyzing those data. Among all, still images and videos are commonly used formats. Images are compact in size but do not contain motion information. Videos record motion but are sometimes too big to be analyzed. Sequential images, which are a set of continuous images with low frame rate, stand out because they are smaller than videos and still maintain motion information. This thesis investigates features in different types of noisy sequential images, and the proposed solutions that intelligently combined multiple features to successfully retrieve visual information from on-line videos and cloudy satellite images. The first task is detecting supraglacial lakes above ice sheet in sequential satellite images. The dynamics of supraglacial lakes on the Greenland ice sheet deeply affect glacier movement, which is directly related to sea level rise and global environment change. Detecting lakes above ice is suffering from diverse image qualities and unexpected clouds. A new method is proposed to efficiently extract prominent lake candidates with irregular shapes, heterogeneous backgrounds, and in cloudy images. The proposed system fully automatize the procedure that track lakes with high accuracy. We further cooperated with geoscientists to examine the tracked lakes and found new scientific findings. The second one is detecting obscene content in on-line video chat services, such as Chatroulette, that randomly match pairs of users in video chat sessions. A big problem encountered in such systems is the presence of flashers and obscene content. Because of various obscene content and unstable qualities of videos capture by home web-camera, detecting misbehaving users is a highly challenging task. We propose SafeVchat, which is the first solution that achieves satisfactory

  14. Fourier transform infrared spectroscopy microscopic imaging classification based on spatial-spectral features

    Liu, Lian; Yang, Xiukun; Zhong, Mingliang; Liu, Yao; Jing, Xiaojun; Yang, Qin

    2018-04-01

    The discrete fractional Brownian incremental random (DFBIR) field is used to describe the irregular, random, and highly complex shapes of natural objects such as coastlines and biological tissues, for which traditional Euclidean geometry cannot be used. In this paper, an anisotropic variable window (AVW) directional operator based on the DFBIR field model is proposed for extracting spatial characteristics of Fourier transform infrared spectroscopy (FTIR) microscopic imaging. Probabilistic principal component analysis first extracts spectral features, and then the spatial features of the proposed AVW directional operator are combined with the former to construct a spatial-spectral structure, which increases feature-related information and helps a support vector machine classifier to obtain more efficient distribution-related information. Compared to Haralick’s grey-level co-occurrence matrix, Gabor filters, and local binary patterns (e.g. uniform LBPs, rotation-invariant LBPs, uniform rotation-invariant LBPs), experiments on three FTIR spectroscopy microscopic imaging datasets show that the proposed AVW directional operator is more advantageous in terms of classification accuracy, particularly for low-dimensional spaces of spatial characteristics.

  15. A methodology for texture feature-based quality assessment in nucleus segmentation of histopathology image

    Si Wen

    2017-01-01

    Full Text Available Context: Image segmentation pipelines often are sensitive to algorithm input parameters. Algorithm parameters optimized for a set of images do not necessarily produce good-quality-segmentation results for other images. Even within an image, some regions may not be well segmented due to a number of factors, including multiple pieces of tissue with distinct characteristics, differences in staining of the tissue, normal versus tumor regions, and tumor heterogeneity. Evaluation of quality of segmentation results is an important step in image analysis. It is very labor intensive to do quality assessment manually with large image datasets because a whole-slide tissue image may have hundreds of thousands of nuclei. Semi-automatic mechanisms are needed to assist researchers and application developers to detect image regions with bad segmentations efficiently. Aims: Our goal is to develop and evaluate a machine-learning-based semi-automated workflow to assess quality of nucleus segmentation results in a large set of whole-slide tissue images. Methods: We propose a quality control methodology, in which machine-learning algorithms are trained with image intensity and texture features to produce a classification model. This model is applied to image patches in a whole-slide tissue image to predict the quality of nucleus segmentation in each patch. The training step of our methodology involves the selection and labeling of regions by a pathologist in a set of images to create the training dataset. The image regions are partitioned into patches. A set of intensity and texture features is computed for each patch. A classifier is trained with the features and the labels assigned by the pathologist. At the end of this process, a classification model is generated. The classification step applies the classification model to unlabeled test images. Each test image is partitioned into patches. The classification model is applied to each patch to predict the patch

  16. Magnetic resonance imaging features of esthesioneuroblastoma in three dogs and one cat.

    Söffler, Charlotte; Hartmann, Antje; Gorgas, Daniela; Ludewig, Eberhard; von Pückler, Kerstin; Kramer, Martin; Schmidt, Martin J

    2016-10-12

    Esthesioneuroblastoma is a rare malignant intranasal tumor that originates from the olfactory neuroepithelium of the upper nasal cavity, and can destroy the cribriform plate and expand into the neurocranium. Descriptions of the magnetic resonance features of esthesioneuroblastomas in animals are scarce. The objectives of this study were to report the magnetic resonance imaging features of esthesioneuroblastomas in order to determine distinct imaging characteristics that may help distinguish it from other intracranial tumor types. Magnetic resonance images of four patients with confirmed esthesioneuroblastomas were reviewed and compared with previously reported cases. The esthesioneuroblastomas appeared as oval-shaped, solitary lesions in the caudal nasal cavity that caused osteolysis of the cribriform plate and extended into the brain in all cases. Signal intensity was variable. Contrast enhancement was mild and varied from homogeneous to heterogeneous. A peripheral cystic component was found in two patients and was reported in only one previous case. Mass effect and white matter edema were marked to severe. Osteolysis of facial bones and extension into the facial soft tissues or retrobulbar space were not present in any of the cases, although this has been reported in the literature. A definitive diagnosis of esthesioneuroblastoma based on signal intensity or contrast behavior was not possible. Nevertheless, the presence of a mass in the caudal nasal cavity with extension into the neurocranium seems to be a feature highly suspicious of esthesioneuroblastoma. In contrast to other extra-cranial lesions, the extra-cranial mass was relatively small and destruction of facial bones seems to be rare.

  17. Clinical features and imaging of central poststroke pain

    Ramesh Bhattacharyya

    2016-01-01

    Full Text Available Introduction: Central post stroke pain is a variety of neuropathic pain that occurs after stroke as a result of dysfunction of either spino-thalamic tract or thalamo-cortical sensory pathway. Hyperirritability in surviving cells along the affected pain pathways found with changes in inhibitory pathways, spinal and cortical reorganization and central sensitization. Aim: Clinical features like character of pain and other sensory features with neuroimaging findings of central post stroke pain for a part of Indian population were analyzed in this study. Materials and Method including analysis: 120 numbers of patients, who developed new onset pain symptoms after stroke, attending outpatient and inpatient department of a neurology department during a whole year were examined with history including extensive sensory symptoms analysis; sensory examinations including assessment of pain score and other neurological examinations were done and rechecked by neurologists. All were investigated by neuroimaging with either MRI or CT scan or both. Neuro imaging was interpreted by experienced neuroradiologist and corroborated by neurologists and pain physician. Results: 45% of the lesions were in Thalamus when 75% of the lesions were detected as infarction. 57.5% symptoms started within 3 months. Ataxia found with 60%, increased threshold to warm and cold were seen in 40% of patients, burning sensation was seen in 40% followed by numbness with 20%, dysesthesia found with 60%, reduced sensation to temperature changes found with 40% patients. Conclusion: CPSP patients may presents with various sensory symptoms beside pain. Distribution of sensory symptoms may be with any part of the body as well as over one half of the body. Most common trigger factor was mechanical; while thalamic lesions found in 45%, extra thalamic lesions werefound with 55% of patients.

  18. Fast hybrid fractal image compression using an image feature and neural network

    Zhou Yiming; Zhang Chao; Zhang Zengke

    2008-01-01

    Since fractal image compression could maintain high-resolution reconstructed images at very high compression ratio, it has great potential to improve the efficiency of image storage and image transmission. On the other hand, fractal image encoding is time consuming for the best matching search between range blocks and domain blocks, which limits the algorithm to practical application greatly. In order to solve this problem, two strategies are adopted to improve the fractal image encoding algorithm in this paper. Firstly, based on the definition of an image feature, a necessary condition of the best matching search and FFC algorithm are proposed, and it could reduce the search space observably and exclude most inappropriate domain blocks according to each range block before the best matching search. Secondly, on the basis of FFC algorithm, in order to reduce the mapping error during the best matching search, a special neural network is constructed to modify the mapping scheme for the subblocks, in which the pixel values fluctuate greatly (FNFC algorithm). Experimental results show that the proposed algorithms could obtain good quality of the reconstructed images and need much less time than the baseline encoding algorithm

  19. The water withdraws and spectral characteristic analysis of back groundsurface features in Zengcheng City

    Gao, Ai; Xia, Lihua

    2008-10-01

    Many achievements in studies of extracting water have been made in the past ten years.According to the foundation of remote sensing and spectrum theory, the general extracting principal of remote sensing information is introduced. Zengcheng was rich in water resources, and it is an idel back garden of Guangzhou city. Therefore, it is important to use the water resources rationally in Zengcheng.TM image dated 10 November 2006 was elected in this paper.Both interpreted maps were analyzed and managed by ENVI and ArcGIS software. Single-band threshold method, the relationship between spectrum, vegetation index and water index method were used in this paper. At last, Water index method was considered to be the most suitable one after a comparative analysis.In this paper landscape types within the study area were classified into (1) farmland, (2)forest land, (3)urban Inhabitant land and other land,(4)orchard land, (5)unused land, (6)water, with the help of Land cover map 2006 of Zengcheng. A reconnaissance survey of the study area was made to correlate the image characteristics and ground features by the standard technique of human-computer 'dialogue' interpretation.According to the foundation of remote sensing and spectrum theory, a model of water body extraction is set up in this paper.

  20. Imaging features of anterior cruciate ligament reconstruction graft insufficiency

    Shang Yao; Zhang Yue; Tian Chunyan; Zheng Zhuozhao

    2011-01-01

    Objective: To investigate the imaging features of anterior cruciate ligament (ACL) graft insufficiency. Methods: X-Ray and MR imaging examinations in 24 consecutive patients who had ACL reconstructive graft insufficiency were retrospectively evaluated for tunnel position, osteoarthrosis and its related complications. Follow-up arthroscopy showed 16 graft tears and 8 graft laxities. Fisher exact test was used to compare tunnel malpositions, the proportion of graft tear on MRI and osteoarthrosis between graft tear group and graft laxity group. Results: Two malpositions of tibial tunnel and 3 malpositions of femoral tunnel were seen in graft tear group. Three-malpositions of tibial tunnel and 4 malpositions of femoral tunnel were seen in graft laxity group. The proportion of tibial or femoral malposition showed no significant difference between the two groups (P=0.289, P=0.167). In graft tear group, 15 complete graft tears were diagnosed correctly, 1 partial tear was misdiagnosed as normal on MRI. In graft laxity group, 4 grafts were diagnosed as normal and 4 were considered as graft tear on MRI. A significant difference was seen between the two groups (P=0.028) in the proportion of graft tear diagnosed on MRI. Fourteen osteoarthrosis were seen in graft tear group and 5 in graft laxity group. No significant difference was seen between the two groups (P= 0.289) in the proportion of osteoarthrosis. Conclusion: The proportions of tunnel malposition and osteoarthrosis showed no significant difference between the graft tear group and graft Laxity group. Most graft tears can be diagnosed accurately on MRI, but some cases of graft laxity may be misdiagnosed for graft tear. (authors)

  1. W-transform method for feature-oriented multiresolution image retrieval

    Kwong, M.K.; Lin, B. [Argonne National Lab., IL (United States). Mathematics and Computer Science Div.

    1995-07-01

    Image database management is important in the development of multimedia technology. Since an enormous amount of digital images is likely to be generated within the next few decades in order to integrate computers, television, VCR, cables, telephone and various imaging devices. Effective image indexing and retrieval systems are urgently needed so that images can be easily organized, searched, transmitted, and presented. Here, the authors present a local-feature-oriented image indexing and retrieval method based on Kwong, and Tang`s W-transform. Multiresolution histogram comparison is an effective method for content-based image indexing and retrieval. However, most recent approaches perform multiresolution analysis for whole images but do not exploit the local features present in the images. Since W-transform is featured by its ability to handle images of arbitrary size, with no periodicity assumptions, it provides a natural tool for analyzing local image features and building indexing systems based on such features. In this approach, the histograms of the local features of images are used in the indexing, system. The system not only can retrieve images that are similar or identical to the query images but also can retrieve images that contain features specified in the query images, even if the retrieved images as a whole might be very different from the query images. The local-feature-oriented method also provides a speed advantage over the global multiresolution histogram comparison method. The feature-oriented approach is expected to be applicable in managing large-scale image systems such as video databases and medical image databases.

  2. Influence of distribution characteristics and associated seabed features on exploitation of cobalt-rich manganese deposits

    Yamazaki, T.; Sharma, R.; Tsurusaki, K.

    Method of exploitation, selection of mine site and desing of mining system of cobalt-rich manganese deposits on seamounts would be greatly influenced by the distribution characteristics as well as the associated seabed features, wuch as the seabed...

  3. An explorative childhood pneumonia analysis based on ultrasonic imaging texture features

    Zenteno, Omar; Diaz, Kristians; Lavarello, Roberto; Zimic, Mirko; Correa, Malena; Mayta, Holger; Anticona, Cynthia; Pajuelo, Monica; Oberhelman, Richard; Checkley, William; Gilman, Robert H.; Figueroa, Dante; Castañeda, Benjamín.

    2015-12-01

    According to World Health Organization, pneumonia is the respiratory disease with the highest pediatric mortality rate accounting for 15% of all deaths of children under 5 years old worldwide. The diagnosis of pneumonia is commonly made by clinical criteria with support from ancillary studies and also laboratory findings. Chest imaging is commonly done with chest X-rays and occasionally with a chest CT scan. Lung ultrasound is a promising alternative for chest imaging; however, interpretation is subjective and requires adequate training. In the present work, a two-class classification algorithm based on four Gray-level co-occurrence matrix texture features (i.e., Contrast, Correlation, Energy and Homogeneity) extracted from lung ultrasound images from children aged between six months and five years is presented. Ultrasound data was collected using a L14-5/38 linear transducer. The data consisted of 22 positive- and 68 negative-diagnosed B-mode cine-loops selected by a medical expert and captured in the facilities of the Instituto Nacional de Salud del Niño (Lima, Peru), for a total number of 90 videos obtained from twelve children diagnosed with pneumonia. The classification capacity of each feature was explored independently and the optimal threshold was selected by a receiver operator characteristic (ROC) curve analysis. In addition, a principal component analysis was performed to evaluate the combined performance of all the features. Contrast and correlation resulted the two more significant features. The classification performance of these two features by principal components was evaluated. The results revealed 82% sensitivity, 76% specificity, 78% accuracy and 0.85 area under the ROC.

  4. Image features of herniation pit of the femoral neck

    Zhang Xuezhe; Li Guangming; Wang Cunli; Wang Guimin

    2008-01-01

    Objective: To evaluate imaging appearances of herniation pit of the femoral neck. Methods: We retrospectively analyzed the X-ray, CT and MRI findings of 9 patients with herniation pit of the femoral neck. All nine patients were male with the age ranging from 21 to 73 years. They had pain in the hip from two months to two years duration. Results: The bilateral hips were affected in six patients, the right hips in the other 3 patients. Of the nine patients, X-ray plain films (2 cases), CT scanning(6 cases), and MR scanning (5 cases ) were performed. The size of the lesions ranged from 0.5 cm x 0.6 cm to 1.0 cm x 1.5 cm, located in the anterosuperior portion of the femoral neck (n=7) or anteroinferior portion (n=2). X-ray plain films showed an osteolytic lesion surrounded by a sclerotic rim. CT scanning showed the lesion just below the cortex of the femoral neck surrounded by a rim of sclerosis or associated with a small cortical break in two patients. MR scanning showed low signal intensity in five patients on T 1 WI and high signal intensity surrounded by a rim of low signal intensity (n=3) or low signal intensity (n=2) on T 2 WI, and high signal intensity on fat suppression MR image. A small joint effusion was observed in two cases on T 2 WI. Conclusion: The CT and MRI findings of herniation pit of the femoral neck are characteristic, it is useful in defining the diagnosis of the herniation pit of the femoral neck. (authors)

  5. Characteristics of circular features on comet 67P/Churyumov-Gerasimenko

    Deller, J. F.; Güttler, C.; Tubiana, C.; Hofmann, M.; Sierks, H.

    2017-09-01

    Comet 67P/Churyumov-Gerasimenko shows a large variety of circular structures such as pits, elevated roundish features in Imhotep, and even a single occurrence of a plausible fresh impact crater. Imaging the pits in the Ma'at region, aiming to understand their structure and origin drove the design of the final descent trajectory of the Rosetta spacecraft. The high-resolution images obtained during the last mission phase allow us to study these pits as exemplary circular features. A complete catalogue of circular features gives us the possibility to compare and classify these structures systematically.

  6. Atorvastatin effect evaluation based on feature combination of three-dimension ultrasound images

    Luo, Yongkang; Ding, Mingyue

    2016-03-01

    In the past decades, stroke has become the worldwide common cause of death and disability. It is well known that ischemic stroke is mainly caused by carotid atherosclerosis. As an inexpensive, convenient and fast means of detection, ultrasound technology is applied widely in the prevention and treatment of carotid atherosclerosis. Recently, many studies have focused on how to quantitatively evaluate local arterial effects of medicine treatment for carotid diseases. So the evaluation method based on feature combination was proposed to detect potential changes in the carotid arteries after atorvastatin treatment. And the support vector machine (SVM) and 10-fold cross-validation protocol were utilized on a database of 5533 carotid ultrasound images of 38 patients (17 atorvastatin groups and 21 placebo groups) at baseline and after 3 months of the treatment. With combination optimization of many features (including morphological and texture features), the evaluation results of single feature and different combined features were compared. The experimental results showed that the performance of single feature is poor and the best feature combination have good recognition ability, with the accuracy 92.81%, sensitivity 80.95%, specificity 95.52%, positive predictive value 80.47%, negative predictive value 95.65%, Matthew's correlation coefficient 76.27%, and Youden's index 76.48%. And the receiver operating characteristic (ROC) curve was also performed well with 0.9663 of the area under the ROC curve (AUC), which is better than all the features with 0.9423 of the AUC. Thus, it is proved that this novel method can reliably and accurately evaluate the effect of atorvastatin treatment.

  7. Diabetic mastopathy: Imaging features and the role of image-guided biopsy in its diagnosis

    Kim, Jong Hyeon; Kim, Eun Kyung; Kim, Min Jung; Moon, Hee Jung; Yoon, Jung Hyun

    2016-01-01

    The goal of this study was to evaluate the imaging features of diabetic mastopathy (DMP) and the role of image-guided biopsy in its diagnosis. Two experienced radiologists retrospectively reviewed the mammographic and sonographic images of 19 pathologically confirmed DMP patients. The techniques and results of the biopsies performed in each patient were also reviewed. Mammograms showed negative findings in 78% of the patients. On ultrasonography (US), 13 lesions were seen as masses and six as non-mass lesions. The US features of the mass lesions were as follows: irregular shape (69%), oval shape (31%), indistinct margin (69%), angular margin (15%), microlobulated margin (8%), well-defined margin (8%), heterogeneous echogenicity (62%), hypoechoic echogenicity (38%), posterior shadowing (92%), parallel orientation (100%), the absence of calcifications (100%), and the absence of vascularity (100%). Based on the US findings, 17 lesions (89%) were classified as Breast Imaging Reporting and Data System category 4 and two (11%) as category 3. US-guided core biopsy was performed in 18 patients, and 10 (56%) were diagnosed with DMP on that basis. An additional vacuum-assisted biopsy was performed in seven patients and all were diagnosed with DMP. The US features of DMP were generally suspicious for malignancy, whereas the mammographic findings were often negative or showed only focal asymmetry. Core biopsy is an adequate method for initial pathological diagnosis. However, since it yields non-diagnostic results in a considerable number of cases, the evaluation of correlations between imaging and pathology plays an important role in the diagnostic process

  8. Diabetic mastopathy: Imaging features and the role of image-guided biopsy in its diagnosis

    Kim, Jong Hyeon; Kim, Eun Kyung; Kim, Min Jung; Moon, Hee Jung; Yoon, Jung Hyun [Dept. of Radiology, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul (Korea, Republic of)

    2016-03-15

    The goal of this study was to evaluate the imaging features of diabetic mastopathy (DMP) and the role of image-guided biopsy in its diagnosis. Two experienced radiologists retrospectively reviewed the mammographic and sonographic images of 19 pathologically confirmed DMP patients. The techniques and results of the biopsies performed in each patient were also reviewed. Mammograms showed negative findings in 78% of the patients. On ultrasonography (US), 13 lesions were seen as masses and six as non-mass lesions. The US features of the mass lesions were as follows: irregular shape (69%), oval shape (31%), indistinct margin (69%), angular margin (15%), microlobulated margin (8%), well-defined margin (8%), heterogeneous echogenicity (62%), hypoechoic echogenicity (38%), posterior shadowing (92%), parallel orientation (100%), the absence of calcifications (100%), and the absence of vascularity (100%). Based on the US findings, 17 lesions (89%) were classified as Breast Imaging Reporting and Data System category 4 and two (11%) as category 3. US-guided core biopsy was performed in 18 patients, and 10 (56%) were diagnosed with DMP on that basis. An additional vacuum-assisted biopsy was performed in seven patients and all were diagnosed with DMP. The US features of DMP were generally suspicious for malignancy, whereas the mammographic findings were often negative or showed only focal asymmetry. Core biopsy is an adequate method for initial pathological diagnosis. However, since it yields non-diagnostic results in a considerable number of cases, the evaluation of correlations between imaging and pathology plays an important role in the diagnostic process.

  9. Advanced GPR imaging of sedimentary features: integrated attribute analysis applied to sand dunes

    Zhao, Wenke; Forte, Emanuele; Fontolan, Giorgio; Pipan, Michele

    2018-04-01

    We evaluate the applicability and the effectiveness of integrated GPR attribute analysis to image the internal sedimentary features of the Piscinas Dunes, SW Sardinia, Italy. The main objective is to explore the limits of GPR techniques to study sediment-bodies geometry and to provide a non-invasive high-resolution characterization of the different subsurface domains of dune architecture. On such purpose, we exploit the high-quality Piscinas data-set to extract and test different attributes of the GPR trace. Composite displays of multi-attributes related to amplitude, frequency, similarity and textural features are displayed with overlays and RGB mixed models. A multi-attribute comparative analysis is used to characterize different radar facies to better understand the characteristics of internal reflection patterns. The results demonstrate that the proposed integrated GPR attribute analysis can provide enhanced information about the spatial distribution of sediment bodies, allowing an enhanced and more constrained data interpretation.

  10. Single-level dynamic spiral CT of hepatocellular carcinoma: correlation between imaging features and tumor angiogenesis

    Chen Weixia; Min Pengqiu; Song Bin; Xiao Bangliang; Liu Yan; Wang Wendong; Chen Xian; Xu Jianying

    2001-01-01

    Objective: To investigate the correlation of the enhancement imaging features of hepatocellular carcinoma (HCC) and relevant parameters revealed by single-level dynamic spiral CT scanning with tumor microvessel counting (MVC). Methods: The study included 26 histopathologically proven HCC patients. Target-slice dynamic scanning and portal venous phase scanning were performed for all patients. The time-density curves were generated with measurement of relevant parameters including: peak value (PV) and contrast enhancement ratio (CER), and the gross enhancement morphology analyzed. Histopathological slides were carefully prepared for the standard F8RA and VEGF immunohistochemical staining and tumor microvessel counting and calculation of VEGF expression percentage of tumor cells. The enhancement imaging features of HCC lesions were correlatively studied with tumor MVC and VEGF expression. Results: Peak value of HCC lesions were 7.9 to 75.2 HU, CER were 3.8% to 36.0%. MVC were 6 to 91, and the VEGF expression percentage were 32.1% to 78.3%. The PV and CER were significantly correlated with tumor tissue MVC (r = 0.508 and 0.423, P < 0.01 and 0.05 respectively). There were no correlations between PV and CER and VEGF expression percentage. Both the patterns of time-density curve and the gross enhancement morphology of HCC lesions were also correlated with tumor MVC, and reflected the distribution characteristics of tumor microvessels within HCC lesions. A close association was found between the likelihood of intrahepatic metastasis of HCC lesions with densely enhanced pseudo capsules and the presence of rich tumor microvessels within these pseudo capsules. Conclusion: The parameters and the enhancement imaging features of HCC lesions on target-slice dynamic scanning are correlated with tumor MVC, and can reflect the distribution characteristics of tumor microvessels within HCC lesions. Dynamic spiral CT scanning is a valuable means to assess the angiogenic activity and

  11. Thermal imaging cameras characteristics and performance

    Williams, Thomas

    2009-01-01

    The ability to see through smoke and mist and the ability to use the variances in temperature to differentiate between targets and their backgrounds are invaluable in military applications and have become major motivators for the further development of thermal imagers. As the potential of thermal imaging is more clearly understood and the cost decreases, the number of industrial and civil applications being exploited is growing quickly. In order to evaluate the suitability of particular thermal imaging cameras for particular applications, it is important to have the means to specify and measur

  12. MR imaging of the neonatal brain: Pathologic features

    McArdle, C.B.; Richardson, C.J.; Nicholas, D.A.; Hayden, C.K.; Amparo, E.G.

    1986-01-01

    Seventy-three neonates, aged 29-43 weeks since conception, were studied. US and/or CT correlations were obtained in most infants with pathology. In the first 4-5 days after hemorrhage, US and CT were superior to MR imaging, but after that time MR imaging was the single best modality for imaging blood. In early premature infants with very watery white matter, US detected infarction and brain edema that were poorly seen on both MR imaging and CT. However, in late premature and full-term infants, MR imaging was better than CT in distinguishing between normal white matter and infarction. Only MR imaging disclosed delayed myelination in 13 term infants with hydrocephalus and severe asphyxia. MR imaging with play an important role in imaging neonates once MR imaging-compatible monitors and neonatal head coils become widely available

  13. Pleasant/Unpleasant Filtering for Affective Image Retrieval Based on Cross-Correlation of EEG Features

    Keranmu Xielifuguli

    2014-01-01

    Full Text Available People often make decisions based on sensitivity rather than rationality. In the field of biological information processing, methods are available for analyzing biological information directly based on electroencephalogram: EEG to determine the pleasant/unpleasant reactions of users. In this study, we propose a sensitivity filtering technique for discriminating preferences (pleasant/unpleasant for images using a sensitivity image filtering system based on EEG. Using a set of images retrieved by similarity retrieval, we perform the sensitivity-based pleasant/unpleasant classification of images based on the affective features extracted from images with the maximum entropy method: MEM. In the present study, the affective features comprised cross-correlation features obtained from EEGs produced when an individual observed an image. However, it is difficult to measure the EEG when a subject visualizes an unknown image. Thus, we propose a solution where a linear regression method based on canonical correlation is used to estimate the cross-correlation features from image features. Experiments were conducted to evaluate the validity of sensitivity filtering compared with image similarity retrieval methods based on image features. We found that sensitivity filtering using color correlograms was suitable for the classification of preferred images, while sensitivity filtering using local binary patterns was suitable for the classification of unpleasant images. Moreover, sensitivity filtering using local binary patterns for unpleasant images had a 90% success rate. Thus, we conclude that the proposed method is efficient for filtering unpleasant images.

  14. Biomedical Imaging Modality Classification Using Combined Visual Features and Textual Terms

    Xian-Hua Han

    2011-01-01

    extraction from medical images and fuses the different extracted visual features and textual feature for modality classification. To extract visual features from the images, we used histogram descriptor of edge, gray, or color intensity and block-based variation as global features and SIFT histogram as local feature. For textual feature of image representation, the binary histogram of some predefined vocabulary words from image captions is used. Then, we combine the different features using normalized kernel functions for SVM classification. Furthermore, for some easy misclassified modality pairs such as CT and MR or PET and NM modalities, a local classifier is used for distinguishing samples in the pair modality to improve performance. The proposed strategy is evaluated with the provided modality dataset by ImageCLEF 2010.

  15. Securing SIFT: Privacy-preserving Outsourcing Computation of Feature Extractions Over Encrypted Image Data.

    Hu, Shengshan; Wang, Qian; Wang, Jingjun; Qin, Zhan; Ren, Kui

    2016-05-13

    Advances in cloud computing have greatly motivated data owners to outsource their huge amount of personal multimedia data and/or computationally expensive tasks onto the cloud by leveraging its abundant resources for cost saving and flexibility. Despite the tremendous benefits, the outsourced multimedia data and its originated applications may reveal the data owner's private information, such as the personal identity, locations or even financial profiles. This observation has recently aroused new research interest on privacy-preserving computations over outsourced multimedia data. In this paper, we propose an effective and practical privacy-preserving computation outsourcing protocol for the prevailing scale-invariant feature transform (SIFT) over massive encrypted image data. We first show that previous solutions to this problem have either efficiency/security or practicality issues, and none can well preserve the important characteristics of the original SIFT in terms of distinctiveness and robustness. We then present a new scheme design that achieves efficiency and security requirements simultaneously with the preservation of its key characteristics, by randomly splitting the original image data, designing two novel efficient protocols for secure multiplication and comparison, and carefully distributing the feature extraction computations onto two independent cloud servers. We both carefully analyze and extensively evaluate the security and effectiveness of our design. The results show that our solution is practically secure, outperforms the state-of-theart, and performs comparably to the original SIFT in terms of various characteristics, including rotation invariance, image scale invariance, robust matching across affine distortion, addition of noise and change in 3D viewpoint and illumination.

  16. SecSIFT: Privacy-preserving Outsourcing Computation of Feature Extractions Over Encrypted Image Data.

    Hu, Shengshan; Wang, Qian; Wang, Jingjun; Qin, Zhan; Ren, Kui

    2016-05-13

    Advances in cloud computing have greatly motivated data owners to outsource their huge amount of personal multimedia data and/or computationally expensive tasks onto the cloud by leveraging its abundant resources for cost saving and flexibility. Despite the tremendous benefits, the outsourced multimedia data and its originated applications may reveal the data owner's private information, such as the personal identity, locations or even financial profiles. This observation has recently aroused new research interest on privacy-preserving computations over outsourced multimedia data. In this paper, we propose an effective and practical privacy-preserving computation outsourcing protocol for the prevailing scale-invariant feature transform (SIFT) over massive encrypted image data. We first show that previous solutions to this problem have either efficiency/security or practicality issues, and none can well preserve the important characteristics of the original SIFT in terms of distinctiveness and robustness. We then present a new scheme design that achieves efficiency and security requirements simultaneously with the preservation of its key characteristics, by randomly splitting the original image data, designing two novel efficient protocols for secure multiplication and comparison, and carefully distributing the feature extraction computations onto two independent cloud servers. We both carefully analyze and extensively evaluate the security and effectiveness of our design. The results show that our solution is practically secure, outperforms the state-of-theart, and performs comparably to the original SIFT in terms of various characteristics, including rotation invariance, image scale invariance, robust matching across affine distortion, addition of noise and change in 3D viewpoint and illumination.

  17. Adenoma malignum of the uterine cervix - Imaging features with clinicopathologic correlation

    Park, Sung Bin; Lee, Young Ho; Song, Mi Jin; Lee, Jong Hwa; Lim, Kyung Taek; Hong, Sung Ran; Kim, Jeong Kon

    2013-01-01

    Background: Adenoma malignum, also known as minimal deviation adenocarcinoma, is a subtype of mucinous adenocarcinoma of the cervix. Purpose: To evaluate the clinical, pathologic, and imaging features of the adenoma malignum of the uterine cervix. Material and Methods: We retrospectively analyzed the CT and MRI findings in 13 patients: size, endoluminal fluid, appearance of the solid and cystic component, margin, enhancement, characteristics of locules of the cystic lesion, tumor spread, and associated ovarian lesion. Clinical and pathologic features were determined in 24 patients. Results: The mean of the major tumor diameter was 4.1 cm (range, 2.2 - 6.5 cm). In the imaging features, 77% of 13 tumors demonstrated endoluminal fluid. All tumors showed enhancing solid components; 62% were multicystic and 38% had solid lesions. Most solid lesions exhibited an irregular margin (80%). The locules of the multicystic lesions tended to have smooth margins (75%), to have an average major diameter of ≤1 cm (88%), and to be 11 - 20 in number (75%). The solid lesions were associated with invasion and metastases (60%). Clinically, 38% of 24 patients had watery discharge and 13% had Peutz-Jeghers syndrome, while pathologically, most patients were low stage (I or II) (83%). Over the 2-year follow-up of 17 patients, 82% was free from disease. The patients with more aggressive tumors or an unfavorable prognosis that manifested as tumor recurrence or metastasis tended to have invasion, watery discharges, high stages (III or IV) (100%) and solid lesions, metastases, and associated ovarian lesions (67%). Conclusion: Awareness of imaging features as well as clinicopathologic manifestations of adenoma malignum can aid in accurate diagnosis, treatment, and prediction of prognosis

  18. A Modified Image Comparison Algorithm Using Histogram Features

    Al-Oraiqat, Anas M.; Kostyukova, Natalya S.

    2018-01-01

    This article discuss the problem of color image content comparison. Particularly, methods of image content comparison are analyzed, restrictions of color histogram are described and a modified method of images content comparison is proposed. This method uses the color histograms and considers color locations. Testing and analyzing of based and modified algorithms are performed. The modified method shows 97% average precision for a collection containing about 700 images without loss of the adv...

  19. Imaging characteristics in rotational panoramic radiography

    Sanderink, G.C.H.

    1987-01-01

    This study is concerned with imaging quality in rotational panoramic radiography. This imaging technique records an image of a curved layer within the object radiographed. The shape of this layer normally corresponds with the average form of the dental arch. In the centre of the layer a plane can be found which is depicted with a minimum of unsharpness. Unsharpness increases and the horizontal magnification changes as distance increases from that central plane. The image quality of the layer has been analyzed with the use of mathematical models to estimate the performance of the radiographic diagnostic system. Despite the application of these increasingly sophisticated models the question remains: will the results of the calculations based on these models adequately predict the diagnostic effectiveness of this type of imaging system? In this study a comparison is made between the theoretically determined quality of the system and the diagnostic quality using the observer as a measuring instrument. Experiments were carried out to measure the total unsharpness occurring in rotational panoramic radiography. 116 refs.; 114 figs.; 54 tabs

  20. Medical Image Fusion Algorithm Based on Nonlinear Approximation of Contourlet Transform and Regional Features

    Hui Huang

    2017-01-01

    Full Text Available According to the pros and cons of contourlet transform and multimodality medical imaging, here we propose a novel image fusion algorithm that combines nonlinear approximation of contourlet transform with image regional features. The most important coefficient bands of the contourlet sparse matrix are retained by nonlinear approximation. Low-frequency and high-frequency regional features are also elaborated to fuse medical images. The results strongly suggested that the proposed algorithm could improve the visual effects of medical image fusion and image quality, image denoising, and enhancement.

  1. Emotional textile image classification based on cross-domain convolutional sparse autoencoders with feature selection

    Li, Zuhe; Fan, Yangyu; Liu, Weihua; Yu, Zeqi; Wang, Fengqin

    2017-01-01

    We aim to apply sparse autoencoder-based unsupervised feature learning to emotional semantic analysis for textile images. To tackle the problem of limited training data, we present a cross-domain feature learning scheme for emotional textile image classification using convolutional autoencoders. We further propose a correlation-analysis-based feature selection method for the weights learned by sparse autoencoders to reduce the number of features extracted from large size images. First, we randomly collect image patches on an unlabeled image dataset in the source domain and learn local features with a sparse autoencoder. We then conduct feature selection according to the correlation between different weight vectors corresponding to the autoencoder's hidden units. We finally adopt a convolutional neural network including a pooling layer to obtain global feature activations of textile images in the target domain and send these global feature vectors into logistic regression models for emotional image classification. The cross-domain unsupervised feature learning method achieves 65% to 78% average accuracy in the cross-validation experiments corresponding to eight emotional categories and performs better than conventional methods. Feature selection can reduce the computational cost of global feature extraction by about 50% while improving classification performance.

  2. Extended local binary pattern features for improving settlement type classification of quickbird images

    Mdakane, L

    2012-11-01

    Full Text Available Despite the fact that image texture features extracted from high-resolution remotely sensed images over urban areas have demonstrated their ability to distinguish different classes, they are still far from being ideal. Multiresolution grayscale...

  3. Fibrous tumours in children: imaging features of a heterogeneous group of disorders

    Eich, G.F.; Hoeffel, J.C.; Tschaeppeler, H.; Gassner, I.; Willi, U.V. [Division of Diagnostic Imaging and Radiology, The University Children`s Hospital, Steinwiesstrasse 75, CH-8032 Zurich (Switzerland)

    1998-07-01

    Background. Fibrous tumours are predominantly soft tissue lesions which are relatively frequent in childhood but are little known. Imaging is often used in the evaluation of these tumours but their characteristics, particularly on US or MRI, have not been studied systematically. Objectives. To provide an overview of the clinical and imaging features of the different disorders, and to correlate them with the currently used classification schemes. Material and methods. Twenty-five patients with fibrous tumours were evaluated retrospectively. Clinical histories were studied for the histopathological diagnosis, age, signs and symptoms at presentation, mode of therapy and follow-up where available. Imaging findings were analysed for the following variables: number, location, size, margin and architecture of soft tissue and/or visceral lesions and the presence and pattern of osseous involvement. Comparison with the available literature was performed. Results. The following tumour types were encountered: desmoid fibromatosis (n = 9), myofibromatosis (n = 7), fibromatosis colli (n = 2), congenital-infantile fibrosarcoma (n = 2), adult-type fibrosarcoma (n = 2), fibrous hamartoma of infancy (n = 1), angiofibroma (n = 1) and hyaline fibromatosis (n = 1). Conclusions. While some tumours were non-specific in their clinical and radiological manifestation, others such as myofibromatosis, fibromatosis colli, fibrous hamartoma of infancy and angiofibroma exhibited a characteristic pattern which allowed a diagnosis to be made even without histology. (orig.) With 10 figs., 1 tab., 20 refs.

  4. Learning Rich Features from RGB-D Images for Object Detection and Segmentation

    Gupta, Saurabh; Girshick, Ross; Arbeláez, Pablo; Malik, Jitendra

    2014-01-01

    In this paper we study the problem of object detection for RGB-D images using semantically rich image and depth features. We propose a new geocentric embedding for depth images that encodes height above ground and angle with gravity for each pixel in addition to the horizontal disparity. We demonstrate that this geocentric embedding works better than using raw depth images for learning feature representations with convolutional neural networks. Our final object detection system achieves an av...

  5. CHARACTERISTIC FEATURES OF MUELLER MATRIX PATTERNS FOR POLARIZATION SCATTERING MODEL OF BIOLOGICAL TISSUES

    E DU

    2014-01-01

    Full Text Available We developed a model to describe polarized photon scattering in biological tissues. In this model, tissues are simplified to a mixture of scatterers and surrounding medium. There are two types of scatterers in the model: solid spheres and infinitely long solid cylinders. Variables related to the scatterers include: the densities and sizes of the spheres and cylinders, the orientation and angular distribution of cylinders. Variables related to the surrounding medium include: the refractive index, absorption coefficient and birefringence. In this paper, as a development we introduce an optical activity effect to the model. By comparing experiments and Monte Carlo simulations, we analyze the backscattering Mueller matrix patterns of several tissue-like media, and summarize the different effects coming from anisotropic scattering and optical properties. In addition, we propose a possible method to extract the optical activity values for tissues. Both the experimental and simulated results show that, by analyzing the Mueller matrix patterns, the microstructure and optical properties of the medium can be obtained. The characteristic features of Mueller matrix patterns are potentially powerful tools for studying the contrast mechanisms of polarization imaging for medical diagnosis.

  6. Neural network-based feature point descriptors for registration of optical and SAR images

    Abulkhanov, Dmitry; Konovalenko, Ivan; Nikolaev, Dmitry; Savchik, Alexey; Shvets, Evgeny; Sidorchuk, Dmitry

    2018-04-01

    Registration of images of different nature is an important technique used in image fusion, change detection, efficient information representation and other problems of computer vision. Solving this task using feature-based approaches is usually more complex than registration of several optical images because traditional feature descriptors (SIFT, SURF, etc.) perform poorly when images have different nature. In this paper we consider the problem of registration of SAR and optical images. We train neural network to build feature point descriptors and use RANSAC algorithm to align found matches. Experimental results are presented that confirm the method's effectiveness.

  7. Clinical Characteristics and Metabolic Features of Patients with Adrenal Incidentalomas with or without Subclinical Cushing's Syndrome

    Bo-Yeon Kim

    2014-12-01

    Full Text Available BackgroundThe aim of this study was to examine the clinical characteristics of adrenal incidentalomas discovered by computed tomography (CT and to investigate metabolic features of subclinical Cushing's syndrome (SCS in patients with adrenal incidentalomas in a tertiary hospital in Korea.MethodsThis retrospective study examined the clinical aspects of 268 patients with adrenal incidentalomas discovered by CT at Soonchunhyang University Bucheon Hospital. Clinical data and endocrine function of the patients as well as histological findings were obtained from medical records, while anatomic characteristics were analyzed by reviewing imaging studies. Hormonal tests for pheochromocytoma, Cushing's syndrome, and aldosterone-secreting adenoma were performed.ResultsMost (n=218, 81.3% cases were nonfunctioning tumors. Of the 50 patients with functioning tumors (18.7%, 19 (7.1% were diagnosed with SCS, nine (3.4% with overt Cushing's syndrome, 12 (4.5% with primary aldosteronism, and 10 (3.7% with pheochromocytoma. Malignant tumors (both primary and metastatic were rare (n=2, 0.7%. Body mass index, fasting glucose, hemoglobin A1c, and total cholesterol were significantly higher in patients with SCS in comparison with those with nonfunctioning tumors. The prevalence of type 2 diabetes mellitus and hypertension were significantly higher in patients with SCS compared with those with nonfunctioning tumors.ConclusionFunctioning tumors, especially those with subclinical cortisol excess, are commonly found in patients with adrenal incidentalomas, although malignancy is rare. In addition, patients with SCS in adrenal incidentalomas have adverse metabolic and cardiovascular profiles.

  8. Model-Based Learning of Local Image Features for Unsupervised Texture Segmentation

    Kiechle, Martin; Storath, Martin; Weinmann, Andreas; Kleinsteuber, Martin

    2018-04-01

    Features that capture well the textural patterns of a certain class of images are crucial for the performance of texture segmentation methods. The manual selection of features or designing new ones can be a tedious task. Therefore, it is desirable to automatically adapt the features to a certain image or class of images. Typically, this requires a large set of training images with similar textures and ground truth segmentation. In this work, we propose a framework to learn features for texture segmentation when no such training data is available. The cost function for our learning process is constructed to match a commonly used segmentation model, the piecewise constant Mumford-Shah model. This means that the features are learned such that they provide an approximately piecewise constant feature image with a small jump set. Based on this idea, we develop a two-stage algorithm which first learns suitable convolutional features and then performs a segmentation. We note that the features can be learned from a small set of images, from a single image, or even from image patches. The proposed method achieves a competitive rank in the Prague texture segmentation benchmark, and it is effective for segmenting histological images.

  9. ASSESSMENT OF LANDSCAPE CHARACTERISTICS ON THEMATIC IMAGE CLASSIFICATION ACCURACY

    Landscape characteristics such as small patch size and land cover heterogeneity have been hypothesized to increase the likelihood of misclassifying pixels during thematic image classification. However, there has been a lack of empirical evidence, to support these hypotheses. This...

  10. Image mosaicking based on feature points using color-invariant values

    Lee, Dong-Chang; Kwon, Oh-Seol; Ko, Kyung-Woo; Lee, Ho-Young; Ha, Yeong-Ho

    2008-02-01

    In the field of computer vision, image mosaicking is achieved using image features, such as textures, colors, and shapes between corresponding images, or local descriptors representing neighborhoods of feature points extracted from corresponding images. However, image mosaicking based on feature points has attracted more recent attention due to the simplicity of the geometric transformation, regardless of distortion and differences in intensity generated by camera motion in consecutive images. Yet, since most feature-point matching algorithms extract feature points using gray values, identifying corresponding points becomes difficult in the case of changing illumination and images with a similar intensity. Accordingly, to solve these problems, this paper proposes a method of image mosaicking based on feature points using color information of images. Essentially, the digital values acquired from a real digital color camera are converted to values of a virtual camera with distinct narrow bands. Values based on the surface reflectance and invariant to the chromaticity of various illuminations are then derived from the virtual camera values and defined as color-invariant values invariant to changing illuminations. The validity of these color-invariant values is verified in a test using a Macbeth Color-Checker under simulated illuminations. The test also compares the proposed method using the color-invariant values with the conventional SIFT algorithm. The accuracy of the matching between the feature points extracted using the proposed method is increased, while image mosaicking using color information is also achieved.

  11. New Analysis Method Application in Metallographic Images through the Construction of Mosaics Via Speeded Up Robust Features and Scale Invariant Feature Transform

    Pedro Pedrosa Rebouças Filho

    2015-06-01

    Full Text Available In many applications in metallography and analysis, many regions need to be considered and not only the current region. In cases where there are analyses with multiple images, the specialist should also evaluate neighboring areas. For example, in metallurgy, welding technology is derived from conventional testing and metallographic analysis. In welding, these tests allow us to know the features of the metal, especially in the Heat-Affected Zone (HAZ; the region most likely for natural metallurgical problems to occur in welding. The expanse of the Heat-Affected Zone exceeds the size of the area observed through a microscope and typically requires multiple images to be mounted on a larger picture surface to allow for the study of the entire heat affected zone. This image stitching process is performed manually and is subject to all the inherent flaws of the human being due to results of fatigue and distraction. The analyzing of grain growth is also necessary in the examination of multiple regions, although not necessarily neighboring regions, but this analysis would be a useful tool to aid a specialist. In areas such as microscopic metallography, which study metallurgical products with the aid of a microscope, the assembly of mosaics is done manually, which consumes a lot of time and is also subject to failures due to human limitations. The mosaic technique is used in the construct of environment or scenes with corresponding characteristics between themselves. Through several small images, and with corresponding characteristics between themselves, a new model is generated in a larger size. This article proposes the use of Digital Image Processing for the automatization of the construction of these mosaics in metallographic images. The use of this proposed method is meant to significantly reduce the time required to build the mosaic and reduce the possibility of failures in assembling the final image; therefore increasing efficiency in obtaining

  12. Diffusion-weighted imaging features in spinal cord infarction

    Zhang Jingsong; Huan Yi; Sun Lijun; Chang Yingjuan; Zhao Haitao; Yang Chunmin; Zhang Guangyun

    2005-01-01

    Objective: To analyze the diffusion-weighted MR imaging findings in ischemic spinal cord lesions and discuss the value of diffusion-weighted MR imaging in differentiating diagnosis with inflammatory diseases and tumors. Methods: Six patients (2 male, 4 female) with typical sudden onset of neurological deficits caused by spinal cord ischemia were evaluated. There were no definite etiologies in all patients. DW imaging was performed within 1 to 30 days after the initial neurological symptoms using a Philips Gyroscan 1.5 TMR system. Four patients had other scans including contrast-enhanced MR imaging (CE-MRI) and/or FLAIR scans. Two of them followed up with MR images in three months. All six patients were imaged using a multi-shot, navigator-corrected, echo-planar pulse sequence, and ADC values were calculated in sagittal-oriented plane. Results: MR abnormalities were demonstrated on sagittal T 2 -weighted images with 'patch-like' or 'strip-like' hyperintensities (6/6) and cord enlargement (5/6). Axial T 2 -weighted images showed bilateral (6/6) hyperintensities. In one patient only the posterior spinal artery (PSA) territory was involved. Spinal cord was mainly affected at the cervical (2/6) and thoracolumbar (4/6) region, two of them included the conus medullaris (T10-L1). DW images showed high signals in all infarct lesions, degree of intensity depended on scanning time from ill-onset and progress of illness and whether companied with hemorrhage. In this group, except one case with closely normal ADC value due to one month course of illness, the five others ADC values of lesions calculated from ADC maps arranged from 0.23 x 10 -3 mm 2 /s to 0.47 x 10 -3 mm 2 /s [average value (0.37 ± 0.10) x 10 -3 mm 2 /s], markedly lower than normal parts [ average value (0.89 ± 0.08) x 10 -3 mm 2 /s]. There were marked difference between lesions and normal regions (t=4.71, P 2 W images. Meanwhile, lesions could be displayed much better in DW images than in T 2 W images because

  13. ANALYSIS OF SPECTRAL CHARACTERISTICS AMONG DIFFERENT SENSORS BY USE OF SIMULATED RS IMAGES

    2000-01-01

    This research, by use of RS image-simulating method, simulated apparent reflectance images at sensor level and ground-reflectance images of SPOT-HRV,CBERS-CCD,Landsat-TM and NOAA14-AVHRR' s corresponding bands. These images were used to analyze sensor's differences caused by spectral sensitivity and atmospheric impacts. The differences were analyzed on Normalized Difference Vegetation Index(NDVI). The results showed that the differences of sensors' spectral characteristics cause changes of their NDVI and reflectance. When multiple sensors' data are applied to digital analysis, the error should be taken into account. Atmospheric effect makes NDVI smaller, and atn~pheric correction has the tendency of increasing NDVI values. The reflectance and their NDVIs of different sensors can be used to analyze the differences among sensor' s features. The spectral analysis method based on RS simulated images can provide a new way to design the spectral characteristics of new sensors.

  14. Clinicopathological and imaging features of breast cancer in Korean Women under 40 years of age

    Kim, Jun Woo; Jang, Mi Jung; Kim, Sun Mi; Yun, Bo La; Lee, Jong Yoon; Kim, Eun Kyu; Kang, Eun Young; Park, So Yeon [Seoul National University Bundang Hospital, Seongnam (Korea, Republic of)

    2017-06-15

    To evaluate the clinicopathological and imaging features of mammography, ultrasonography, and magnetic resonance imaging (MRI) for breast cancer in Korean women under 40 years of age according to molecular subtypes. We included 183 breast cancers in 176 consecutive women under 40 years old who had been diagnosed with breast cancer between January 2012 and November 2014. The patients' clinical and pathologic records were available as electronic medical records. A retrospective review of the pre-operative imaging studies was performed with 177 mammographies, 183 ultrasonographies, and 178 MRIs. Eighty-six percent (158/183) of lesions were symptomatic, with masses (147/183) as the most common presentation. Eighty percent (22/25) of the asymptomatic lesions were diagnosed via screening ultrasonography. The luminal A subtype was the most common (n = 79, 43%), human epidermal growth factor receptor 2-enriched subtype showed indistinct margins on mammography (p = 0.006), the triple negative subtype depicted a posterior enhancement on ultrasonography (p < 0.001) and rim enhancement on MRI (p < 0.001). Breast cancers in Korean women under 40 years of age are commonly presented with a palpable mass, and luminal A is the most common molecular subtype. In our study, the imaging and pathologic characteristics of breast cancer in younger women were similar to those previously reported for older patients.

  15. Clinicopathological and imaging features of breast cancer in Korean Women under 40 years of age

    Kim, Jun Woo; Jang, Mi Jung; Kim, Sun Mi; Yun, Bo La; Lee, Jong Yoon; Kim, Eun Kyu; Kang, Eun Young; Park, So Yeon

    2017-01-01

    To evaluate the clinicopathological and imaging features of mammography, ultrasonography, and magnetic resonance imaging (MRI) for breast cancer in Korean women under 40 years of age according to molecular subtypes. We included 183 breast cancers in 176 consecutive women under 40 years old who had been diagnosed with breast cancer between January 2012 and November 2014. The patients' clinical and pathologic records were available as electronic medical records. A retrospective review of the pre-operative imaging studies was performed with 177 mammographies, 183 ultrasonographies, and 178 MRIs. Eighty-six percent (158/183) of lesions were symptomatic, with masses (147/183) as the most common presentation. Eighty percent (22/25) of the asymptomatic lesions were diagnosed via screening ultrasonography. The luminal A subtype was the most common (n = 79, 43%), human epidermal growth factor receptor 2-enriched subtype showed indistinct margins on mammography (p = 0.006), the triple negative subtype depicted a posterior enhancement on ultrasonography (p < 0.001) and rim enhancement on MRI (p < 0.001). Breast cancers in Korean women under 40 years of age are commonly presented with a palpable mass, and luminal A is the most common molecular subtype. In our study, the imaging and pathologic characteristics of breast cancer in younger women were similar to those previously reported for older patients

  16. A Novel Technique for Shape Feature Extraction Using Content Based Image Retrieval

    Dhanoa Jaspreet Singh

    2016-01-01

    Full Text Available With the advent of technology and multimedia information, digital images are increasing very quickly. Various techniques are being developed to retrieve/search digital information or data contained in the image. Traditional Text Based Image Retrieval System is not plentiful. Since it is time consuming as it require manual image annotation. Also, the image annotation differs with different peoples. An alternate to this is Content Based Image Retrieval (CBIR system. It retrieves/search for image using its contents rather the text, keywords etc. A lot of exploration has been compassed in the range of Content Based Image Retrieval (CBIR with various feature extraction techniques. Shape is a significant image feature as it reflects the human perception. Moreover, Shape is quite simple to use by the user to define object in an image as compared to other features such as Color, texture etc. Over and above, if applied alone, no descriptor will give fruitful results. Further, by combining it with an improved classifier, one can use the positive features of both the descriptor and classifier. So, a tryout will be made to establish an algorithm for accurate feature (Shape extraction in Content Based Image Retrieval (CBIR. The main objectives of this project are: (a To propose an algorithm for shape feature extraction using CBIR, (b To evaluate the performance of proposed algorithm and (c To compare the proposed algorithm with state of art techniques.

  17. Computer-Based Image Analysis for Plus Disease Diagnosis in Retinopathy of Prematurity: Performance of the "i-ROP" System and Image Features Associated With Expert Diagnosis.

    Ataer-Cansizoglu, Esra; Bolon-Canedo, Veronica; Campbell, J Peter; Bozkurt, Alican; Erdogmus, Deniz; Kalpathy-Cramer, Jayashree; Patel, Samir; Jonas, Karyn; Chan, R V Paul; Ostmo, Susan; Chiang, Michael F

    2015-11-01

    We developed and evaluated the performance of a novel computer-based image analysis system for grading plus disease in retinopathy of prematurity (ROP), and identified the image features, shapes, and sizes that best correlate with expert diagnosis. A dataset of 77 wide-angle retinal images from infants screened for ROP was collected. A reference standard diagnosis was determined for each image by combining image grading from 3 experts with the clinical diagnosis from ophthalmoscopic examination. Manually segmented images were cropped into a range of shapes and sizes, and a computer algorithm was developed to extract tortuosity and dilation features from arteries and veins. Each feature was fed into our system to identify the set of characteristics that yielded the highest-performing system compared to the reference standard, which we refer to as the "i-ROP" system. Among the tested crop shapes, sizes, and measured features, point-based measurements of arterial and venous tortuosity (combined), and a large circular cropped image (with radius 6 times the disc diameter), provided the highest diagnostic accuracy. The i-ROP system achieved 95% accuracy for classifying preplus and plus disease compared to the reference standard. This was comparable to the performance of the 3 individual experts (96%, 94%, 92%), and significantly higher than the mean performance of 31 nonexperts (81%). This comprehensive analysis of computer-based plus disease suggests that it may be feasible to develop a fully-automated system based on wide-angle retinal images that performs comparably to expert graders at three-level plus disease discrimination. Computer-based image analysis, using objective and quantitative retinal vascular features, has potential to complement clinical ROP diagnosis by ophthalmologists.

  18. Scattering features for lung cancer detection in fibered confocal fluorescence microscopy images.

    Rakotomamonjy, Alain; Petitjean, Caroline; Salaün, Mathieu; Thiberville, Luc

    2014-06-01

    To assess the feasibility of lung cancer diagnosis using fibered confocal fluorescence microscopy (FCFM) imaging technique and scattering features for pattern recognition. FCFM imaging technique is a new medical imaging technique for which interest has yet to be established for diagnosis. This paper addresses the problem of lung cancer detection using FCFM images and, as a first contribution, assesses the feasibility of computer-aided diagnosis through these images. Towards this aim, we have built a pattern recognition scheme which involves a feature extraction stage and a classification stage. The second contribution relies on the features used for discrimination. Indeed, we have employed the so-called scattering transform for extracting discriminative features, which are robust to small deformations in the images. We have also compared and combined these features with classical yet powerful features like local binary patterns (LBP) and their variants denoted as local quinary patterns (LQP). We show that scattering features yielded to better recognition performances than classical features like LBP and their LQP variants for the FCFM image classification problems. Another finding is that LBP-based and scattering-based features provide complementary discriminative information and, in some situations, we empirically establish that performance can be improved when jointly using LBP, LQP and scattering features. In this work we analyze the joint capability of FCFM images and scattering features for lung cancer diagnosis. The proposed method achieves a good recognition rate for such a diagnosis problem. It also performs well when used in conjunction with other features for other classical medical imaging classification problems. Copyright © 2014 Elsevier B.V. All rights reserved.

  19. Curvature histogram features for retrieval of images of smooth 3D objects

    Zhdanov, I; Scherbakov, O; Potapov, A; Peterson, M

    2014-01-01

    We consider image features on the base of histograms of oriented gradients (HOG) with addition of contour curvature histogram (HOG-CH), and also compare it with results of known scale-invariant feature transform (SIFT) approach in application to retrieval of images of smooth 3D objects.

  20. Imaging characteristics of different mammographic screens.

    Kuhn, H; Knüpfer, W

    1992-01-01

    A study of mammography systems with green-emitting screens was conducted to determine how the image quality parameters (apart from dose requirement), such as modulation transfer function (MTF) and Wiener spectrum (WS), depend on the dye content of the compound and coating weight of the screen. In addition, the contribution to total noise of the individual components, i.e., film, screen, and quantum noise, was studied. The quantities derived from MTF and WS, namely detective quantum efficiency (DQE) and noise equivalent quanta (NEQ), were also investigated in regard to their dose dependency. It can be demonstrated that the MTF of the screens becomes more favorable when the dye content is increased, while noise is not significantly affected. This suggests the use of a mammography screen capable of greater detail recognition, requiring at least double the dose of today's conventional systems with approximately 80 microGy system dose. On the other hand, the manufacture of a screen with about 60% of the dose of the conventional system is possible with very little loss in image quality. For the systems in common use today (80 microGy), quantum noise represents a considerable share of the total noise at low spatial frequencies, whereas in high spatial frequencies, the graininess of the film dominates quantum noise and screen structure.

  1. Oriented Edge-Based Feature Descriptor for Multi-Sensor Image Alignment and Enhancement

    Myung-Ho Ju

    2013-10-01

    Full Text Available In this paper, we present an efficient image alignment and enhancement method for multi-sensor images. The shape of the object captured in a multi-sensor images can be determined by comparing variability of contrast using corresponding edges across multi-sensor image. Using this cue, we construct a robust feature descriptor based on the magnitudes of the oriented edges. Our proposed method enables fast image alignment by identifying matching features in multi-sensor images. We enhance the aligned multi-sensor images through the fusion of the salient regions from each image. The results of stitching the multi-sensor images and their enhancement demonstrate that our proposed method can align and enhance multi-sensor images more efficiently than previous methods.

  2. Intra-articular ganglion cysts of the knee: clinical and MR imaging features

    Kim, M.G.; Cho, W.H.; Kim, B.H.; Choi, J.A.; Lee, N.J.; Chung, K.B.; Choi, Y.S.; Cho, S.B.; Lim, H.C.

    2001-01-01

    The purpose of this study was to present clinical and MR imaging features of intra-articular ganglion cysts of the knee. Retrospective review of 1685 consecutive medical records and MR examinations of the knee performed at three imaging centers allowed identification of 20 patients (13 men and 7 women; mean age 35 years), in whom evidence of intra-articular ganglion cyst was seen. Of the 20 ganglion cysts, 5 were found in the infrapatellar fat pad, 10 arose from the posterior cruciate ligament, and 5 from the anterior cruciate ligament. Three of five patients with ganglion cyst in the infrapatellar fat pad had a palpable mass. In 7 of 15 patients with ganglion cyst in the intercondylar notch, exacerbation of pain occurred in a squatting position. On four MR arthrographies, ganglion cysts were an intra-articular round, lobulated, low signal intensity lesion. Five cases of fat-suppressed contrast-enhanced T1-weighted SE images demonstrated peripheral thin rim enhancement. The clinical presentation of intra-articular ganglion cyst is varied according to its intra-articular location. The MR appearance of intra-articular ganglion cyst is characteristic and usually associated with the cruciate ligament or the infrapatellar fat pad. Magnetic resonance arthrography has no definite advantage over conventional MR in the evaluation of the lesion. For intra-articular ganglion cyst in the infrapatellar fat pad, fat-suppressed contrast-enhanced MR imaging could be useful, because a thin, rim-enhancing feature of intra-articular ganglion cyst allows it to be distinguished from synovial hemangioma and synovial sarcoma. (orig.)

  3. No-reference image quality assessment based on statistics of convolution feature maps

    Lv, Xiaoxin; Qin, Min; Chen, Xiaohui; Wei, Guo

    2018-04-01

    We propose a Convolutional Feature Maps (CFM) driven approach to accurately predict image quality. Our motivation bases on the finding that the Nature Scene Statistic (NSS) features on convolution feature maps are significantly sensitive to distortion degree of an image. In our method, a Convolutional Neural Network (CNN) is trained to obtain kernels for generating CFM. We design a forward NSS layer which performs on CFM to better extract NSS features. The quality aware features derived from the output of NSS layer is effective to describe the distortion type and degree an image suffered. Finally, a Support Vector Regression (SVR) is employed in our No-Reference Image Quality Assessment (NR-IQA) model to predict a subjective quality score of a distorted image. Experiments conducted on two public databases demonstrate the promising performance of the proposed method is competitive to state of the art NR-IQA methods.

  4. Change Detection of High-Resolution Remote Sensing Images Based on Adaptive Fusion of Multiple Features

    Wang, G. H.; Wang, H. B.; Fan, W. F.; Liu, Y.; Chen, C.

    2018-04-01

    In view of the traditional change detection algorithm mainly depends on the spectral information image spot, failed to effectively mining and fusion of multi-image feature detection advantage, the article borrows the ideas of object oriented analysis proposed a multi feature fusion of remote sensing image change detection algorithm. First by the multi-scale segmentation of image objects based; then calculate the various objects of color histogram and linear gradient histogram; utilizes the color distance and edge line feature distance between EMD statistical operator in different periods of the object, using the adaptive weighted method, the color feature distance and edge in a straight line distance of combination is constructed object heterogeneity. Finally, the curvature histogram analysis image spot change detection results. The experimental results show that the method can fully fuse the color and edge line features, thus improving the accuracy of the change detection.

  5. The ship edge feature detection based on high and low threshold for remote sensing image

    Li, Xuan; Li, Shengyang

    2018-05-01

    In this paper, a method based on high and low threshold is proposed to detect the ship edge feature due to the low accuracy rate caused by the noise. Analyze the relationship between human vision system and the target features, and to determine the ship target by detecting the edge feature. Firstly, using the second-order differential method to enhance the quality of image; Secondly, to improvement the edge operator, we introduction of high and low threshold contrast to enhancement image edge and non-edge points, and the edge as the foreground image, non-edge as a background image using image segmentation to achieve edge detection, and remove the false edges; Finally, the edge features are described based on the result of edge features detection, and determine the ship target. The experimental results show that the proposed method can effectively reduce the number of false edges in edge detection, and has the high accuracy of remote sensing ship edge detection.

  6. Modeling multiple visual words assignment for bag-of-features based medical image retrieval

    Wang, Jim Jing-Yan

    2012-01-01

    In this paper, we investigate the bag-of-features based medical image retrieval methods, which represent an image as a collection of local features, such as image patch and key points with SIFT descriptor. To improve the bag-of-features method, we first model the assignment of local descriptor as contribution functions, and then propose a new multiple assignment strategy. By assuming the local feature can be reconstructed by its neighboring visual words in vocabulary, we solve the reconstruction weights as a QP problem and then use the solved weights as contribution functions, which results in a new assignment method called the QP assignment. We carry our experiments on ImageCLEFmed datasets. Experiments\\' results show that our proposed method exceeds the performances of traditional solutions and works well for the bag-of-features based medical image retrieval tasks.

  7. Modeling multiple visual words assignment for bag-of-features based medical image retrieval

    Wang, Jim Jing-Yan; Almasri, Islam

    2012-01-01

    In this paper, we investigate the bag-of-features based medical image retrieval methods, which represent an image as a collection of local features, such as image patch and key points with SIFT descriptor. To improve the bag-of-features method, we first model the assignment of local descriptor as contribution functions, and then propose a new multiple assignment strategy. By assuming the local feature can be reconstructed by its neighboring visual words in vocabulary, we solve the reconstruction weights as a QP problem and then use the solved weights as contribution functions, which results in a new assignment method called the QP assignment. We carry our experiments on ImageCLEFmed datasets. Experiments' results show that our proposed method exceeds the performances of traditional solutions and works well for the bag-of-features based medical image retrieval tasks.

  8. COLOR IMAGE RETRIEVAL BASED ON FEATURE FUSION THROUGH MULTIPLE LINEAR REGRESSION ANALYSIS

    K. Seetharaman

    2015-08-01

    Full Text Available This paper proposes a novel technique based on feature fusion using multiple linear regression analysis, and the least-square estimation method is employed to estimate the parameters. The given input query image is segmented into various regions according to the structure of the image. The color and texture features are extracted on each region of the query image, and the features are fused together using the multiple linear regression model. The estimated parameters of the model, which is modeled based on the features, are formed as a vector called a feature vector. The Canberra distance measure is adopted to compare the feature vectors of the query and target images. The F-measure is applied to evaluate the performance of the proposed technique. The obtained results expose that the proposed technique is comparable to the other existing techniques.

  9. Global image feature extraction using slope pattern spectra

    Toudjeu, IT

    2008-06-01

    Full Text Available Traditionally, granulometries are obtained using a series of openings or closings with convex structuring elements of increasing size. Granulometries constitute a useful tool for texture and image analysis since they are used to characterize size...

  10. Caroli's disease: magnetic resonance imaging features

    Guy, France; Cognet, Francois; Dranssart, Marie; Cercueil, Jean-Pierre; Conciatori, Laurent; Krause, Denis [Department of Radiology and Imaging, Dijon Le Bocage University Hospital, 2 Blvd. Marechal de Lattre de Tassigny, BP 1542, 21034 Dijon Cedex (France)

    2002-11-01

    Our objective was to describe the main aspects of MR imaging in Caroli's disease. Magnetic resonance cholangiography with a dynamic contrast-enhanced study was performed in nine patients with Caroli's disease. Bile duct abnormalities, lithiasis, dot signs, hepatic enhancement, renal abnormalities, and evidence of portal hypertension were evaluated. Three MR imaging patterns of Caroli's disease were found. In all but two patients, MR imaging findings were sufficient to confirm the diagnosis. Moreover, MR imaging provided information about the severity, location, and extent of liver involvement. This information was useful in planning the best therapeutic strategy. Magnetic resonance cholangiography with a dynamic contrast-enhanced study is a good screening tool for Caroli's disease. Direct cholangiography should be reserved for confirming doubtful cases. (orig.)

  11. Classified study and clinical value of the phase imaging features

    Dang Yaping; Ma Aiqun; Zheng Xiaopu; Yang Aimin; Xiao Jiang; Gao Xinyao

    2000-01-01

    445 patients with various heart diseases were examined by the gated cardiac blood pool imaging, and the phase was classified. The relationship between the seven types with left ventricular function index, clinical heart function, different heart diseases as well as electrocardiograph was studied. The results showed that the phase image classification could match with the clinical heart function. It can visually, directly and accurately indicate clinical heart function and can be used to identify diagnosis of heart disease

  12. DIFET: DISTRIBUTED FEATURE EXTRACTION TOOL FOR HIGH SPATIAL RESOLUTION REMOTE SENSING IMAGES

    S. Eken

    2017-11-01

    Full Text Available In this paper, we propose distributed feature extraction tool from high spatial resolution remote sensing images. Tool is based on Apache Hadoop framework and Hadoop Image Processing Interface. Two corner detection (Harris and Shi-Tomasi algorithms and five feature descriptors (SIFT, SURF, FAST, BRIEF, and ORB are considered. Robustness of the tool in the task of feature extraction from LandSat-8 imageries are evaluated in terms of horizontal scalability.

  13. Difet: Distributed Feature Extraction Tool for High Spatial Resolution Remote Sensing Images

    Eken, S.; Aydın, E.; Sayar, A.

    2017-11-01

    In this paper, we propose distributed feature extraction tool from high spatial resolution remote sensing images. Tool is based on Apache Hadoop framework and Hadoop Image Processing Interface. Two corner detection (Harris and Shi-Tomasi) algorithms and five feature descriptors (SIFT, SURF, FAST, BRIEF, and ORB) are considered. Robustness of the tool in the task of feature extraction from LandSat-8 imageries are evaluated in terms of horizontal scalability.

  14. US or MR Imaging Features of Polypoid Endometriosis: A Case Report

    Park, Jae Il; Cho, Jae Ho; Kim, Geum Rae; Kim, Mi Jin

    2009-01-01

    Polypoid endometriosis is a rare variant of endometriosis that is pathologically similar to an endometrial polyp. This lesion is frequently mistaken for a solid neoplasm in clinical, radiological and pathological examinations. The clinical and pathological features of the lesion have been well described in the English literature. However, its imaging features have not been reported in the Korean literature. We describe ultrasound and magnetic resonance imaging features of pathologically-confirmed polypoid endometriosis

  15. US or MR Imaging Features of Polypoid Endometriosis: A Case Report

    Park, Jae Il; Cho, Jae Ho; Kim, Geum Rae; Kim, Mi Jin [Yeungnam University, Gyeongsan (Korea, Republic of)

    2009-12-15

    Polypoid endometriosis is a rare variant of endometriosis that is pathologically similar to an endometrial polyp. This lesion is frequently mistaken for a solid neoplasm in clinical, radiological and pathological examinations. The clinical and pathological features of the lesion have been well described in the English literature. However, its imaging features have not been reported in the Korean literature. We describe ultrasound and magnetic resonance imaging features of pathologically-confirmed polypoid endometriosis.

  16. Variability of textural features in FDG PET images due to different acquisition modes and reconstruction parameters

    Galavis, P.E.; Hollensen, Christian; Jallow, N.

    2010-01-01

    Background. Characterization of textural features (spatial distributions of image intensity levels) has been considered as a tool for automatic tumor segmentation. The purpose of this work is to study the variability of the textural features in PET images due to different acquisition modes...... reconstruction parameters. Lesions were segmented on a default image using the threshold of 40% of maximum SUV. Fifty different texture features were calculated inside the tumors. The range of variations of the features were calculated with respect to the average value. Results. Fifty textural features were...... classified based on the range of variation in three categories: small, intermediate and large variability. Features with small variability (range 30%). Conclusion. Textural features such as entropy-first order, energy, maximal correlation coefficient, and low-gray level run emphasis exhibited small...

  17. Electrical imaging of deep crustal features of Kutch, India

    Sastry, R. S.; Nagarajan, Nandini; Sarma, S. V. S.

    2008-03-01

    A regional Magnetotelluric (MT) study, was carried out with 55 MT soundings, distributed along five traverses, across the Kutch Mainland Unit (KMU), on the west coast of India, a region characterized by a series of successive uplifts and intervening depressions in the form of half graben, bounded by master faults. We obtain the deeper electrical structure of the crust beneath Kutch, from 2-D modelling of MT data along the 5 traverses, in order to evaluate the geo-electrical signatures, if any, of the known primary tectonic structures in this region. The results show that the deeper electrical structure in the Kutch region presents a mosaic of high resistive crustal blocks separated by deep-rooted conductive features. Two such crustal conductive features spatially correlate with the known tectonic features, viz., the Kutch Mainland Fault (KMF), and the Katrol Hill Fault (KHF). An impressive feature of the geo-electrical sections is an additional, well-defined conductive feature, running between Jakhau and Mundra, located at the southern end of each of the five MT traverses and interpreted to be the electrical signature of yet another hidden fault at the southern margin of the KMU. This new feature is named as Jakhau-Mundra Fault (JMF). It is inferred that the presence of JMF together with the Kathiawar Fault (NKF), further south, located at the northern boundary of the Saurashtra Horst, would enhance the possibility of occurrence of a thick sedimentary column in the Gulf of Kutch. The region between the newly delineated fault (JMF) and the Kathiawar fault (NKF) could thus be significant for Hydrocarbon Exploration.

  18. Personality characteristics and body image in obese individuals.

    Sarısoy, Gökhan; Atmaca, Ayşegül; Ecemiş, Gülçin; Gümüş, Kübra; Pazvantoğlu, Ozan

    2014-06-01

    The aim of this study was to determine the personality characteristics of obese and morbidly obese individuals with no psychiatric disorder and the correlation between these characteristics and body image and self-esteem. Sixty-nine obese individuals and 69 healthy controls, matched in age, sex and marital status, were included in the study. Psychiatric disorders were excluded for all participants using SCID-I and II. Obese and healthy volunteers were compared in terms of body image, self-esteem and personality characteristics. TCI harm avoidance scores were higher in obese individuals compared to healthy controls. Harm avoidance scores were also higher in individuals with morbid obesity compared to non-morbid individuals, while self-directedness and persistence scores were lower. Body image dissatisfaction was higher in obese individuals. There was a negative correlation in obese individuals between body image and self-esteem scale scores and harm avoidance scores, and a positive correlation with self-directedness scores. An elevated harm avoidance temperament characteristic may be correlated with obesity. Furthermore, high harm avoidance, low self-directedness and low persistence may be significant personality characteristics in a process leading to morbid obesity. In addition, harm avoidance temperament and self-directedness personality characteristics may be correlated with body image dissatisfaction and self-esteem in obese individuals. Copyright © 2012 Wiley Publishing Asia Pty Ltd.

  19. Generating description with multi-feature fusion and saliency maps of image

    Liu, Lisha; Ding, Yuxuan; Tian, Chunna; Yuan, Bo

    2018-04-01

    Generating description for an image can be regard as visual understanding. It is across artificial intelligence, machine learning, natural language processing and many other areas. In this paper, we present a model that generates description for images based on RNN (recurrent neural network) with object attention and multi-feature of images. The deep recurrent neural networks have excellent performance in machine translation, so we use it to generate natural sentence description for images. The proposed method uses single CNN (convolution neural network) that is trained on ImageNet to extract image features. But we think it can not adequately contain the content in images, it may only focus on the object area of image. So we add scene information to image feature using CNN which is trained on Places205. Experiments show that model with multi-feature extracted by two CNNs perform better than which with a single feature. In addition, we make saliency weights on images to emphasize the salient objects in images. We evaluate our model on MSCOCO based on public metrics, and the results show that our model performs better than several state-of-the-art methods.

  20. Subpixel Mapping of Hyperspectral Image Based on Linear Subpixel Feature Detection and Object Optimization

    Liu, Zhaoxin; Zhao, Liaoying; Li, Xiaorun; Chen, Shuhan

    2018-04-01

    Owing to the limitation of spatial resolution of the imaging sensor and the variability of ground surfaces, mixed pixels are widesperead in hyperspectral imagery. The traditional subpixel mapping algorithms treat all mixed pixels as boundary-mixed pixels while ignoring the existence of linear subpixels. To solve this question, this paper proposed a new subpixel mapping method based on linear subpixel feature detection and object optimization. Firstly, the fraction value of each class is obtained by spectral unmixing. Secondly, the linear subpixel features are pre-determined based on the hyperspectral characteristics and the linear subpixel feature; the remaining mixed pixels are detected based on maximum linearization index analysis. The classes of linear subpixels are determined by using template matching method. Finally, the whole subpixel mapping results are iteratively optimized by binary particle swarm optimization algorithm. The performance of the proposed subpixel mapping method is evaluated via experiments based on simulated and real hyperspectral data sets. The experimental results demonstrate that the proposed method can improve the accuracy of subpixel mapping.

  1. Quality Evaluation in Wireless Imaging Using Feature-Based Objective Metrics

    Engelke, Ulrich; Zepernick, Hans-Jürgen

    2007-01-01

    This paper addresses the evaluation of image quality in the context of wireless systems using feature-based objective metrics. The considered metrics comprise of a weighted combination of feature values that are used to quantify the extend by which the related artifacts are present in a processed image. In view of imaging applications in mobile radio and wireless communication systems, reduced-reference objective quality metrics are investigated for quantifying user-perceived quality. The exa...

  2. COSMO-SkyMed Image Investigation of Snow Features in Alpine Environment

    Simonetta Paloscia

    2017-01-01

    Full Text Available In this work, X band images acquired by COSMO-SkyMed (CSK on alpine environment have been analyzed for investigating snow characteristics and their effect on backscattering variations. Preliminary results confirmed the capability of simultaneous optical and Synthetic Aperture Radar (SAR images (Landsat-8 and CSK in separating snow/no-snow areas and in detecting wet snow. The sensitivity of backscattering to snow depth has not always been confirmed, depending on snow characteristics related to the season. A model based on Dense Media Radiative Transfer theory (DMRT-QMS was applied for simulating the backscattering response on the X band from snow cover in different conditions of grain size, snow density and depth. By using DMRT-QMS and snow in-situ data collected on Cordevole basin in Italian Alps, the effect of grain size and snow density, beside snow depth and snow water equivalent, was pointed out, showing that the snow features affect the backscatter in different and sometimes opposite ways. Experimental values of backscattering were correctly simulated by using this model and selected intervals of ground parameters. The relationship between simulated and measured backscattering for the entire dataset shows slope >0.9, determination coefficient, R2 = 0.77, and root mean square error, RMSE = 1.1 dB, with p-value <0.05.

  3. Influences of rhythm- and timbre-related musical features on characteristics of music-induced movement.

    Burger, Birgitta; Thompson, Marc R; Luck, Geoff; Saarikallio, Suvi; Toiviainen, Petri

    2013-01-01

    Music makes us move. Several factors can affect the characteristics of such movements, including individual factors or musical features. For this study, we investigated the effect of rhythm- and timbre-related musical features as well as tempo on movement characteristics. Sixty participants were presented with 30 musical stimuli representing different styles of popular music, and instructed to move along with the music. Optical motion capture was used to record participants' movements. Subsequently, eight movement features and four rhythm- and timbre-related musical features were computationally extracted from the data, while the tempo was assessed in a perceptual experiment. A subsequent correlational analysis revealed that, for instance, clear pulses seemed to be embodied with the whole body, i.e., by using various movement types of different body parts, whereas spectral flux and percussiveness were found to be more distinctly related to certain body parts, such as head and hand movement. A series of ANOVAs with the stimuli being divided into three groups of five stimuli each based on the tempo revealed no significant differences between the groups, suggesting that the tempo of our stimuli set failed to have an effect on the movement features. In general, the results can be linked to the framework of embodied music cognition, as they show that body movements are used to reflect, imitate, and predict musical characteristics.

  4. Influences of rhythm- and timbre-related musical features on characteristics of music-induced movement

    Birgitta eBurger

    2013-04-01

    Full Text Available Music makes us move. Several factors can affect the characteristics of such movements, including individual factors or musical features. For this study, we investigated the effect of rhythm- and timbre-related musical features as well as tempo on movement characteristics. Sixty participants were presented with 30 musical stimuli representing different styles of popular music, and instructed to move along with the music. Optical motion capture was used to record participants’ movements. Subsequently, eight movement features and four rhythm- and timbre-related musical features were computationally extracted from the data, while the tempo was assessed in a perceptual experiment. A subsequent correlational analysis revealed that, for instance, clear pulses seemed to be embodied with the whole body, i.e., by using various movement types of different body parts, whereas spectral flux and percussiveness were found to be more distinctly related to certain body parts, such as head and hand movement. A series of ANOVAs with the stimuli being divided into three groups of five stimuli each based on the tempo revealed no significant differences between the groups, suggesting that the tempo of our stimuli set failed to have an effect on the movement features. In general, the results can be linked to the framework of embodied music cognition, as they show that body movements are used to reflect, imitate, and predict musical characteristics.

  5. Multi-scale Analysis of High Resolution Topography: Feature Extraction and Identification of Landscape Characteristic Scales

    Passalacqua, P.; Sangireddy, H.; Stark, C. P.

    2015-12-01

    With the advent of digital terrain data, detailed information on terrain characteristics and on scale and location of geomorphic features is available over extended areas. Our ability to observe landscapes and quantify topographic patterns has greatly improved, including the estimation of fluxes of mass and energy across landscapes. Challenges still remain in the analysis of high resolution topography data; the presence of features such as roads, for example, challenges classic methods for feature extraction and large data volumes require computationally efficient extraction and analysis methods. Moreover, opportunities exist to define new robust metrics of landscape characterization for landscape comparison and model validation. In this presentation we cover recent research in multi-scale and objective analysis of high resolution topography data. We show how the analysis of the probability density function of topographic attributes such as slope, curvature, and topographic index contains useful information for feature localization and extraction. The analysis of how the distributions change across scales, quantified by the behavior of modal values and interquartile range, allows the identification of landscape characteristic scales, such as terrain roughness. The methods are introduced on synthetic signals in one and two dimensions and then applied to a variety of landscapes of different characteristics. Validation of the methods includes the analysis of modeled landscapes where the noise distribution is known and features of interest easily measured.

  6. Imaging characteristics of supratentorial ependymomas: Study on a large single institutional cohort with histopathological correlation.

    Mangalore, Sandhya; Aryan, Saritha; Prasad, Chandrajit; Santosh, Vani

    2015-01-01

    Supratentorial ependymoma (STE) is a tumor whose unique clinical and imaging characteristics have not been studied. Histopathologically, they resemble ependymoma elsewhere. We retrospectively reviewed the imaging findings with clinicopathological correlation in a large number of patients with STE to identify these characteristics. Computed tomography (CT) magnetic resonance images (MRI), pathology reports, and clinical information from 41 patients with pathology-confirmed STE from a single institution were retrospectively reviewed. CT and MRI findings including location, size, signal intensity, hemorrhage, and enhancement pattern were tabulated and described separately in intraventricular and intraparenchymal forms. STE was more common in pediatric age group and intraparenchymal was more common than intraventricular form. The most common presentation was features of raised intracranial tension. There were equal numbers of Grade II and Grade III tumors. The imaging characteristics in adult and pediatric age group were similar. The tumor was large and had both solid and cystic components. Advanced imaging such as diffusion, perfusion, and spectroscopy were suggestive of high-grade tumor. Only differentiating factor between Grade II and Grade III was the presence of calcification. 1234 rule and periwinkle sign which we have described in this article may help characterize this tumor on imaging. This series expands the clinical and imaging spectrum of STE and identifies characteristics that should suggest consideration of this uncommon diagnosis.

  7. MR imaging features of foot involvement in patients with psoriasis

    Erdem, C. Zuhal [Department of Radiology, Zonguldak Karaelmas University, School of Medicine, Zonguldak (Turkey)], E-mail: sunarerdem@yahoo.com; Tekin, Nilgun Solak [Department of Dermatology, Zonguldak Karaelmas University, School of Medicine, Zonguldak (Turkey); Sarikaya, Selda [Department of Physical Therapy and Rehabilitation, Zonguldak Karaelmas University, School of Medicine, Zonguldak (Turkey); Erdem, L. Oktay; Gulec, Sezen [Department of Radiology, Zonguldak Karaelmas University, School of Medicine, Zonguldak (Turkey)

    2008-09-15

    Objective: To determine alterations of the soft tissues, tendons, cartilage, joint spaces, and bones of the foot using magnetic resonance (MR) imaging in patients with psoriasis. Materials and methods: Clinical and MR examination of the foot was performed in 26 consecutive patients (52 ft) with psoriasis. As a control group, 10 healthy volunteers (20 ft) were also studied. Joint effusion/synovitis, retrocalcaneal bursitis, retroachilles bursitis, Achilles tendonitis, soft-tissue edema, para-articular enthesophytes, bone marrow edema, sinus tarsi syndrome, enthesopathy at the Achilles attachment and at the plantar fascia attachment, plantar fasciitis, tenosynovitis, subchondral cysts, and bone erosions, joint space narrowing, subchondral signal changes, osteolysis, luxation, and sub-luxation were examined. Results: Clinical signs and symptoms (pain and swelling) due to foot involvement were present in none of the patients while frequency of involvement was 92% (24/26) by MR imaging. The most common MR imaging findings were Achilles tendonitis (acute and peritendinitis) (57%), retrocalcaneal bursitis (50%), joint effusion/synovitis (46%), soft-tissue edema (46%), and para-articular enthesophytes (38%). The most commonly involved anatomical region was the hindfoot (73%). Conclusion: Our data showed that the incidence of foot involvement was very high in asymptomatic patients with psoriasis on MR imaging. Further MR studies are needed to confirm these data. We conclude that MR imaging may be of importance especially in early diagnosis and treatment of inflammatory changes in the foot.

  8. MR imaging features of foot involvement in patients with psoriasis

    Erdem, C. Zuhal; Tekin, Nilgun Solak; Sarikaya, Selda; Erdem, L. Oktay; Gulec, Sezen

    2008-01-01

    Objective: To determine alterations of the soft tissues, tendons, cartilage, joint spaces, and bones of the foot using magnetic resonance (MR) imaging in patients with psoriasis. Materials and methods: Clinical and MR examination of the foot was performed in 26 consecutive patients (52 ft) with psoriasis. As a control group, 10 healthy volunteers (20 ft) were also studied. Joint effusion/synovitis, retrocalcaneal bursitis, retroachilles bursitis, Achilles tendonitis, soft-tissue edema, para-articular enthesophytes, bone marrow edema, sinus tarsi syndrome, enthesopathy at the Achilles attachment and at the plantar fascia attachment, plantar fasciitis, tenosynovitis, subchondral cysts, and bone erosions, joint space narrowing, subchondral signal changes, osteolysis, luxation, and sub-luxation were examined. Results: Clinical signs and symptoms (pain and swelling) due to foot involvement were present in none of the patients while frequency of involvement was 92% (24/26) by MR imaging. The most common MR imaging findings were Achilles tendonitis (acute and peritendinitis) (57%), retrocalcaneal bursitis (50%), joint effusion/synovitis (46%), soft-tissue edema (46%), and para-articular enthesophytes (38%). The most commonly involved anatomical region was the hindfoot (73%). Conclusion: Our data showed that the incidence of foot involvement was very high in asymptomatic patients with psoriasis on MR imaging. Further MR studies are needed to confirm these data. We conclude that MR imaging may be of importance especially in early diagnosis and treatment of inflammatory changes in the foot

  9. Imaging features of intraductal papillary neoplasm of the bile duct

    Liu Yubao; Li Meng; Zhong Xiaomei; Liu Zaiyi; Liang Changhong

    2014-01-01

    Objective: To investigate the CT and MRI features of intraductal papillary neoplasm of the bile duct (IPNB). Methods: Thirty eight patients with IPNB finally diagnosed by puncture biopsy or surgery were enrolled in this study. All the CT or MRI data were investigated retrospectively. Twenty one patients underwent CT examinations, 17 patients underwent MRI examinations. The features of IPNB including the distribution features of the nodules or masses, CT and MRI features of cholangiectasis, mucus were analyzed. The accuracy differences of CT and MRI for the preoperatively diagnosing mucus and tumor growing along mucous were compared by nonparametric test. Results: The lesions (including 5 patients with solitary lesions and 19 patients with multiple lesions) were located in intrahepatic bile duct in 24 patients, 3 patients occurred simultaneously in intrahepatic and portal bile duct, 2 lesions occurred in portal bile duct, 8 lesions occurred in common bile duct, the lesions of 1 patient occurred simultaneously in common bile duct, cystic duct and gallbladder. Seventeen and 11 patients appeared nodules locating in dilated bile duct on CT and MRI, respectively. Four and 5 patients appeared cystic lesions with multiple nodules of the liver on CT and MRI, respectively. Higher contrast enhancement on CT and MRI in arterial phase than that in portal vein and equilibrium phase were observed in 18 and 12 patients, respectively. Excluding the patients undergoing puncture, CT was better than MRI in evaluating whether the mucus was present, with the accuracies of 30.0% (6/20) and 6.3% (1/16) for CT and MRI, respectively (Z=2.58, P<0.05). CT was worse than MRI in preoperatively evaluating the features of tumor growing along mucous, with the accuracies of 77.8% (14/18) and 92.6% (13/14) for CT and MRI, respectively (Z=4.23, P<0.01). Conclusion: IPNB had the features of growing along mucous of the bile duct, nodule or mass in dilated bile duct and other features, CT and MRI are

  10. Blind image quality assessment based on aesthetic and statistical quality-aware features

    Jenadeleh, Mohsen; Masaeli, Mohammad Masood; Moghaddam, Mohsen Ebrahimi

    2017-07-01

    The main goal of image quality assessment (IQA) methods is the emulation of human perceptual image quality judgments. Therefore, the correlation between objective scores of these methods with human perceptual scores is considered as their performance metric. Human judgment of the image quality implicitly includes many factors when assessing perceptual image qualities such as aesthetics, semantics, context, and various types of visual distortions. The main idea of this paper is to use a host of features that are commonly employed in image aesthetics assessment in order to improve blind image quality assessment (BIQA) methods accuracy. We propose an approach that enriches the features of BIQA methods by integrating a host of aesthetics image features with the features of natural image statistics derived from multiple domains. The proposed features have been used for augmenting five different state-of-the-art BIQA methods, which use statistical natural scene statistics features. Experiments were performed on seven benchmark image quality databases. The experimental results showed significant improvement of the accuracy of the methods.

  11. Image Retrieval based on Integration between Color and Geometric Moment Features

    Saad, M.H.; Saleh, H.I.; Konbor, H.; Ashour, M.

    2012-01-01

    Content based image retrieval is the retrieval of images based on visual features such as colour, texture and shape. .the Current approaches to CBIR differ in terms of which image features are extracted; recent work deals with combination of distances or scores from different and usually independent representations in an attempt to induce high level semantics from the low level descriptors of the images. content-based image retrieval has many application areas such as, education, commerce, military, searching, commerce, and biomedicine and Web image classification. This paper proposes a new image retrieval system, which uses color and geometric moment feature to form the feature vectors. Bhattacharyya distance and histogram intersection are used to perform feature matching. This framework integrates the color histogram which represents the global feature and geometric moment as local descriptor to enhance the retrieval results. The proposed technique is proper for precisely retrieving images even in deformation cases such as geometric deformations and noise. It is tested on a standard the results shows that a combination of our approach as a local image descriptor with other global descriptors outperforms other approaches.

  12. Improved Feature Detection in Fused Intensity-Range Images with Complex SIFT (ℂSIFT

    Boris Jutzi

    2011-09-01

    Full Text Available The real and imaginary parts are proposed as an alternative to the usual Polar representation of complex-valued images. It is proven that the transformation from Polar to Cartesian representation contributes to decreased mutual information, and hence to greater distinctiveness. The Complex Scale-Invariant Feature Transform (ℂSIFT detects distinctive features in complex-valued images. An evaluation method for estimating the uniformity of feature distributions in complex-valued images derived from intensity-range images is proposed. In order to experimentally evaluate the proposed methodology on intensity-range images, three different kinds of active sensing systems were used: Range Imaging, Laser Scanning, and Structured Light Projection devices (PMD CamCube 2.0, Z+F IMAGER 5003, Microsoft Kinect.

  13. Characterization of mammographic masses based on level set segmentation with new image features and patient information

    Shi Jiazheng; Sahiner, Berkman; Chan Heangping; Ge Jun; Hadjiiski, Lubomir; Helvie, Mark A.; Nees, Alexis; Wu Yita; Wei Jun; Zhou Chuan; Zhang Yiheng; Cui Jing

    2008-01-01

    Computer-aided diagnosis (CAD) for characterization of mammographic masses as malignant or benign has the potential to assist radiologists in reducing the biopsy rate without increasing false negatives. The purpose of this study was to develop an automated method for mammographic mass segmentation and explore new image based features in combination with patient information in order to improve the performance of mass characterization. The authors' previous CAD system, which used the active contour segmentation, and morphological, textural, and spiculation features, has achieved promising results in mass characterization. The new CAD system is based on the level set method and includes two new types of image features related to the presence of microcalcifications with the mass and abruptness of the mass margin, and patient age. A linear discriminant analysis (LDA) classifier with stepwise feature selection was used to merge the extracted features into a classification score. The classification accuracy was evaluated using the area under the receiver operating characteristic curve. The authors' primary data set consisted of 427 biopsy-proven masses (200 malignant and 227 benign) in 909 regions of interest (ROIs) (451 malignant and 458 benign) from multiple mammographic views. Leave-one-case-out resampling was used for training and testing. The new CAD system based on the level set segmentation and the new mammographic feature space achieved a view-based A z value of 0.83±0.01. The improvement compared to the previous CAD system was statistically significant (p=0.02). When patient age was included in the new CAD system, view-based and case-based A z values were 0.85±0.01 and 0.87±0.02, respectively. The study also demonstrated the consistency of the newly developed CAD system by evaluating the statistics of the weights of the LDA classifiers in leave-one-case-out classification. Finally, an independent test on the publicly available digital database for screening

  14. Iris image enhancement for feature recognition and extraction

    Mabuza, GP

    2012-10-01

    Full Text Available the employment of other algorithms and commands so as to better present and demonstrate the obtained results. Edge detection and enhancing images for use in an iris recognition system allow for efficient recognition and extraction of iris patterns. REFERENCES... Gonzalez, R.C. and Woods, R.E. 2002. Digital Image Processing 2nd Edition, Instructor?s manual .Englewood Cliffs, Prentice Hall, pp 17-36. Proen?a, H. and Alexandre, L.A. 2007. Toward Noncooperative Iris Recognition: A classification approach using...

  15. Interpretation of archaeological small-scale features in spectral images

    Grøn, Ole; Palmer, Susanna; Stylegar, Frans-Arne

    2011-01-01

    The paper's focus is the use of spectral images for the distinction of small archaeological anomalies on the basis of the authors work. Special attention is given to the ground-truthing perspective in the discussion of a number of cases from Norway. Different approaches to pattern-recognition are......The paper's focus is the use of spectral images for the distinction of small archaeological anomalies on the basis of the authors work. Special attention is given to the ground-truthing perspective in the discussion of a number of cases from Norway. Different approaches to pattern...

  16. Fast image matching algorithm based on projection characteristics

    Zhou, Lijuan; Yue, Xiaobo; Zhou, Lijun

    2011-06-01

    Based on analyzing the traditional template matching algorithm, this paper identified the key factors restricting the speed of matching and put forward a brand new fast matching algorithm based on projection. Projecting the grayscale image, this algorithm converts the two-dimensional information of the image into one-dimensional one, and then matches and identifies through one-dimensional correlation, meanwhile, because of normalization has been done, when the image brightness or signal amplitude increasing in proportion, it could also perform correct matching. Experimental results show that the projection characteristics based image registration method proposed in this article could greatly improve the matching speed, which ensuring the matching accuracy as well.

  17. Features Speech Signature Image Recognition on Mobile Devices

    Alexander Mikhailovich Alyushin

    2015-12-01

    Full Text Available The algorithms fordynamic spectrograms images recognition, processing and soundspeech signature (SS weredeveloped. The software for mobile phones, thatcan recognize speech signatureswas prepared. The investigation of the SS recognition speed on its boundarytypes was conducted. Recommendations on the boundary types choice in the optimal ratio of recognitionspeed and required space were given.

  18. Posteromedial impingement (POMI) of the ankle: MR imaging features

    Koulouris, G.; Connell, D.

    2002-01-01

    Full text: The purpose of this study is to describe the normal MR Imaging appearance of the supporting ligaments of the first carpometacarpal joint in asymptomatic volunteers and the ligamentous injury in patients following dislocation. Three healthy volunteers underwent MR Imaging of the first carpometacarpal joint in order to describe the normal ligaments and optimise the scanning technique for assessment of this joint. Six patients underwent MR Imaging after injury to the ligament. All patients were injured after a fall in which the thumb was subluxed during hyperextension.The Anterior Oblique Ligament (AOL) was evaluated for abnormal morphology and signal intensity, including the site of the injury and the degree of tearing. Joint alignment was assessed for instability. The four ligaments felt to contribute to the stability of the first joint were reliably identified. The normal ligament is a continuous band of low signal running from one bone attachment to another. With injury, there is disruption of the ligament, hyperintensity and perforated stripping. The AOL was shown to be consistently injured after dislocation close to the metacarpal side. MR Imaging allows accurate evaluation of injuries of the AOL of the first carpometacarpal joint and identifies patients who would benefit from surgical reconstruction. Copyright (2002) Blackwell Science Pty Ltd

  19. Olfactory and imaging features in atypical Alzheimer’s disease

    Huihong Zhang

    2018-02-01

    Full Text Available Cognition and speech disorders are the most common symptoms of dementia in neurodegenerative disease. Here, we present a detailed clinical evaluation of a case of logopenic variant of primary progressive aphasia (lv-PPA, an atypical form of Alzheimer disease (AD, including cognitive testing over time, brain imaging, electrophysiology, and tests of olfactory function.

  20. MR imaging features of foot involvement in ankylosing spondylitis

    Erdem, C. Zuhal E-mail: sunarerdem@yahoo.com; Sarikaya, Selda; Erdem, L. Oktay; Ozdolap, Senay; Gundogdu, Sadi

    2005-01-01

    Objective: To determine alterations of the soft tissue, tendon, cartilage, joint space, and bone of the foot using magnetic resonance (MR) imaging in ankylosing spondylitis (AS) patients. Materials and Method: Clinical and MR examination of the foot was performed in 23 AS patients (46 feet). Ten asymptomatic volunteers (20 feet) were studied on MR imaging, as a control group. MR imaging protocol included; T1-weighted spin-echo, T2-weighted fast-field echo (FFE) and fat-suppressed short tau inversion recovery (STIR) sequences in sagittal, sagittal oblique, and coronal planes using a head coil. Specifically, we examined: bone erosions, tendinitis (acute and chronic), para-articular enthesophyte, joint effusion, plantar fasciitis, joint space narrowing, soft tissue edema, bone marrow edema, enthesopathy in the Achilles tendon and plantar fascia attachment, subchondral signal intensity abnormalities (edema and sclerosis), tenosynovitis, retrocalcaneal bursitis, subchondral cysts, subchondral fissures, and bony ankylosis. Midfoot, hindfoot, and ankle were included in examined anatomic regions. Results: Clinical signs and symptoms (pain and swelling) due to foot involvement were present in 3 (13%) of the patients while frequency of involvement was 21 (91%) with MR imaging assessment. The MR imaging findings were bone erosions (65%), Achilles tendinitis (acute and chronic) (61%), para-articular enthesophyte (48%), joint effusion (43%), plantar fasciitis (40%), joint space narrowing (40%), subchondral sclerosis (35%), soft tissue edema (30%), bone marrow edema (30%), enthesopathy of the Achilles attachment (30%), subchondral edema (26%), enthesopathy in the plantar fascia attachment (22%), retrocalcaneal bursitis (22%), subchondral cysts (17%), subchondral fissures (17%), tendinitis and enthesopathy of the plantar ligament (13%), and bony ankylosis (9%). The most common involved anatomical region was the hindfoot (83%) following by midfoot (69% ) and ankle (22

  1. MR imaging features of foot involvement in ankylosing spondylitis

    Erdem, C. Zuhal; Sarikaya, Selda; Erdem, L. Oktay; Ozdolap, Senay; Gundogdu, Sadi

    2005-01-01

    Objective: To determine alterations of the soft tissue, tendon, cartilage, joint space, and bone of the foot using magnetic resonance (MR) imaging in ankylosing spondylitis (AS) patients. Materials and Method: Clinical and MR examination of the foot was performed in 23 AS patients (46 feet). Ten asymptomatic volunteers (20 feet) were studied on MR imaging, as a control group. MR imaging protocol included; T1-weighted spin-echo, T2-weighted fast-field echo (FFE) and fat-suppressed short tau inversion recovery (STIR) sequences in sagittal, sagittal oblique, and coronal planes using a head coil. Specifically, we examined: bone erosions, tendinitis (acute and chronic), para-articular enthesophyte, joint effusion, plantar fasciitis, joint space narrowing, soft tissue edema, bone marrow edema, enthesopathy in the Achilles tendon and plantar fascia attachment, subchondral signal intensity abnormalities (edema and sclerosis), tenosynovitis, retrocalcaneal bursitis, subchondral cysts, subchondral fissures, and bony ankylosis. Midfoot, hindfoot, and ankle were included in examined anatomic regions. Results: Clinical signs and symptoms (pain and swelling) due to foot involvement were present in 3 (13%) of the patients while frequency of involvement was 21 (91%) with MR imaging assessment. The MR imaging findings were bone erosions (65%), Achilles tendinitis (acute and chronic) (61%), para-articular enthesophyte (48%), joint effusion (43%), plantar fasciitis (40%), joint space narrowing (40%), subchondral sclerosis (35%), soft tissue edema (30%), bone marrow edema (30%), enthesopathy of the Achilles attachment (30%), subchondral edema (26%), enthesopathy in the plantar fascia attachment (22%), retrocalcaneal bursitis (22%), subchondral cysts (17%), subchondral fissures (17%), tendinitis and enthesopathy of the plantar ligament (13%), and bony ankylosis (9%). The most common involved anatomical region was the hindfoot (83%) following by midfoot (69% ) and ankle (22

  2. Hyperspectral Image Classification Based on the Combination of Spatial-spectral Feature and Sparse Representation

    YANG Zhaoxia

    2015-07-01

    Full Text Available In order to avoid the problem of being over-dependent on high-dimensional spectral feature in the traditional hyperspectral image classification, a novel approach based on the combination of spatial-spectral feature and sparse representation is proposed in this paper. Firstly, we extract the spatial-spectral feature by reorganizing the local image patch with the first d principal components(PCs into a vector representation, followed by a sorting scheme to make the vector invariant to local image rotation. Secondly, we learn the dictionary through a supervised method, and use it to code the features from test samples afterwards. Finally, we embed the resulting sparse feature coding into the support vector machine(SVM for hyperspectral image classification. Experiments using three hyperspectral data show that the proposed method can effectively improve the classification accuracy comparing with traditional classification methods.

  3. Imaging features of gossypiboma: report of two cases.

    Prasad S

    1999-01-01

    Full Text Available Recognition of postoperatively retained foreign body referred euphemistically as gossypiboma is essential but is very often considerably delayed. Legal implications as well as confusing configuration patterns cause considerable dilemma in the accurate diagnosis. We present computed tomographic features of gossypiboma in two patients who presented with symptoms of fever and pain in the immediate post-operative period. A prospective radiological diagnosis is essential for further management in these patients.

  4. A standardised protocol for texture feature analysis of endoscopic images in gynaecological cancer

    Pattichis Marios S

    2007-11-01

    Full Text Available Abstract Background In the development of tissue classification methods, classifiers rely on significant differences between texture features extracted from normal and abnormal regions. Yet, significant differences can arise due to variations in the image acquisition method. For endoscopic imaging of the endometrium, we propose a standardized image acquisition protocol to eliminate significant statistical differences due to variations in: (i the distance from the tissue (panoramic vs close up, (ii difference in viewing angles and (iii color correction. Methods We investigate texture feature variability for a variety of targets encountered in clinical endoscopy. All images were captured at clinically optimum illumination and focus using 720 × 576 pixels and 24 bits color for: (i a variety of testing targets from a color palette with a known color distribution, (ii different viewing angles, (iv two different distances from a calf endometrial and from a chicken cavity. Also, human images from the endometrium were captured and analysed. For texture feature analysis, three different sets were considered: (i Statistical Features (SF, (ii Spatial Gray Level Dependence Matrices (SGLDM, and (iii Gray Level Difference Statistics (GLDS. All images were gamma corrected and the extracted texture feature values were compared against the texture feature values extracted from the uncorrected images. Statistical tests were applied to compare images from different viewing conditions so as to determine any significant differences. Results For the proposed acquisition procedure, results indicate that there is no significant difference in texture features between the panoramic and close up views and between angles. For a calibrated target image, gamma correction provided an acquired image that was a significantly better approximation to the original target image. In turn, this implies that the texture features extracted from the corrected images provided for better

  5. Radiomic features analysis in computed tomography images of lung nodule classification.

    Chia-Hung Chen

    Full Text Available Radiomics, which extract large amount of quantification image features from diagnostic medical images had been widely used for prognostication, treatment response prediction and cancer detection. The treatment options for lung nodules depend on their diagnosis, benign or malignant. Conventionally, lung nodule diagnosis is based on invasive biopsy. Recently, radiomics features, a non-invasive method based on clinical images, have shown high potential in lesion classification, treatment outcome prediction.Lung nodule classification using radiomics based on Computed Tomography (CT image data was investigated and a 4-feature signature was introduced for lung nodule classification. Retrospectively, 72 patients with 75 pulmonary nodules were collected. Radiomics feature extraction was performed on non-enhanced CT images with contours which were delineated by an experienced radiation oncologist.Among the 750 image features in each case, 76 features were found to have significant differences between benign and malignant lesions. A radiomics signature was composed of the best 4 features which included Laws_LSL_min, Laws_SLL_energy, Laws_SSL_skewness and Laws_EEL_uniformity. The accuracy using the signature in benign or malignant classification was 84% with the sensitivity of 92.85% and the specificity of 72.73%.The classification signature based on radiomics features demonstrated very good accuracy and high potential in clinical application.

  6. Convolutional deep belief network with feature encoding for classification of neuroblastoma histological images

    Soheila Gheisari

    2018-01-01

    Full Text Available Background: Neuroblastoma is the most common extracranial solid tumor in children younger than 5 years old. Optimal management of neuroblastic tumors depends on many factors including histopathological classification. The gold standard for classification of neuroblastoma histological images is visual microscopic assessment. In this study, we propose and evaluate a deep learning approach to classify high-resolution digital images of neuroblastoma histology into five different classes determined by the Shimada classification. Subjects and Methods: We apply a combination of convolutional deep belief network (CDBN with feature encoding algorithm that automatically classifies digital images of neuroblastoma histology into five different classes. We design a three-layer CDBN to extract high-level features from neuroblastoma histological images and combine with a feature encoding model to extract features that are highly discriminative in the classification task. The extracted features are classified into five different classes using a support vector machine classifier. Data: We constructed a dataset of 1043 neuroblastoma histological images derived from Aperio scanner from 125 patients representing different classes of neuroblastoma tumors. Results: The weighted average F-measure of 86.01% was obtained from the selected high-level features, outperforming state-of-the-art methods. Conclusion: The proposed computer-aided classification system, which uses the combination of deep architecture and feature encoding to learn high-level features, is highly effective in the classification of neuroblastoma histological images.

  7. Uniform competency-based local feature extraction for remote sensing images

    Sedaghat, Amin; Mohammadi, Nazila

    2018-01-01

    Local feature detectors are widely used in many photogrammetry and remote sensing applications. The quantity and distribution of the local features play a critical role in the quality of the image matching process, particularly for multi-sensor high resolution remote sensing image registration. However, conventional local feature detectors cannot extract desirable matched features either in terms of the number of correct matches or the spatial and scale distribution in multi-sensor remote sensing images. To address this problem, this paper proposes a novel method for uniform and robust local feature extraction for remote sensing images, which is based on a novel competency criterion and scale and location distribution constraints. The proposed method, called uniform competency (UC) local feature extraction, can be easily applied to any local feature detector for various kinds of applications. The proposed competency criterion is based on a weighted ranking process using three quality measures, including robustness, spatial saliency and scale parameters, which is performed in a multi-layer gridding schema. For evaluation, five state-of-the-art local feature detector approaches, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), scale-invariant feature operator (SFOP), maximally stable extremal region (MSER) and hessian-affine, are used. The proposed UC-based feature extraction algorithms were successfully applied to match various synthetic and real satellite image pairs, and the results demonstrate its capability to increase matching performance and to improve the spatial distribution. The code to carry out the UC feature extraction is available from href="https://www.researchgate.net/publication/317956777_UC-Feature_Extraction.

  8. Haralick texture features from apparent diffusion coefficient (ADC) MRI images depend on imaging and pre-processing parameters.

    Brynolfsson, Patrik; Nilsson, David; Torheim, Turid; Asklund, Thomas; Karlsson, Camilla Thellenberg; Trygg, Johan; Nyholm, Tufve; Garpebring, Anders

    2017-06-22

    In recent years, texture analysis of medical images has become increasingly popular in studies investigating diagnosis, classification and treatment response assessment of cancerous disease. Despite numerous applications in oncology and medical imaging in general, there is no consensus regarding texture analysis workflow, or reporting of parameter settings crucial for replication of results. The aim of this study was to assess how sensitive Haralick texture features of apparent diffusion coefficient (ADC) MR images are to changes in five parameters related to image acquisition and pre-processing: noise, resolution, how the ADC map is constructed, the choice of quantization method, and the number of gray levels in the quantized image. We found that noise, resolution, choice of quantization method and the number of gray levels in the quantized images had a significant influence on most texture features, and that the effect size varied between different features. Different methods for constructing the ADC maps did not have an impact on any texture feature. Based on our results, we recommend using images with similar resolutions and noise levels, using one quantization method, and the same number of gray levels in all quantized images, to make meaningful comparisons of texture feature results between different subjects.

  9. Imaging features of posterior mediastinal chordoma in a child

    Soudack, Michalle; Guralnik, Ludmilla; Engel, Ahuva [Rambam Health Care Campus, Department of Diagnostic Imaging, Haifa (Israel); Ben-Nun, Alon [Rambam Health Care Campus, Department of Thoracic Surgery, Haifa (Israel); Berkowitz, Drora [Rambam Health Care Campus, Department of Pediatrics B, Haifa (Israel); Postovsky, Sergey [Rambam Health Care Campus, Department of Pediatric Hemato-Oncology, Haifa (Israel); Vlodavsky, Eugene [Rambam Health Care Campus, Department of Pathology, Haifa (Israel)

    2007-05-15

    A 51/2-year-old boy presented with repeated episodes of stridor and cough. Chest radiography demonstrated a widened mediastinum. Evaluation by CT revealed a low-density posterior mediastinal mass initially diagnosed as benign tumor. Histopathological analysis of the resected mass disclosed a malignant chordoma. Our radiological results are described with an analysis of the imaging findings in the medical literature. We present our suggestions for preoperative evaluation of posterior mediastinal tumors. (orig.)

  10. TRADEMARK IMAGE RETRIEVAL USING LOW LEVEL FEATURE EXTRACTION IN CBIR

    Latika Pinjarkar*, Manisha Sharma, Smita Selot

    2016-01-01

    Trademarks work as significant responsibility in industry and commerce. Trademarks are important component of its industrial property, and violation can have severe penalty. Therefore designing an efficient trademark retrieval system and its assessment for uniqueness is thus becoming very important task now a days. Trademark image retrieval system where a new candidate trademark is compared with already registered trademarks to check that there is no possibility of resembl...

  11. Bubble feature extracting based on image processing of coal flotation froth

    Wang, F.; Wang, Y.; Lu, M.; Liu, W. [China University of Mining and Technology, Beijing (China). Dept of Chemical Engineering and Environment

    2001-11-01

    Using image processing the contrast ratio between the bubble on the surface of flotation froth and the image background was enhanced, and the edges of bubble were extracted. Thus a model about the relation between the statistic feature of the bubbles in the image and the cleaned coal can be established. It is feasible to extract the bubble by processing the froth image of coal flotation on the basis of analysing the shape of the bubble. By means of processing the 51 group images sampled from laboratory column, it is thought that the use of the histogram equalization of image gradation and the medium filtering can obviously improve the dynamic contrast range and the brightness of bubbles. Finally, the method of threshold value cut and the bubble edge detecting for extracting the bubble were also discussed to describe the bubble feature, such as size and shape, in the froth image and to distinguish the froth image of coal flotation. 6 refs., 3 figs.

  12. CT and MR imaging characteristics of infantile hepatic hemangioendothelioma

    Feng Shiting; Chan Tao; Ching, A.S.C.; Sun Canhui; Guo Huanyi; Fan Miao; Meng Quanfei; Li Ziping

    2010-01-01

    Aim: This study aims to analyze computed tomography (CT) and magnetic resonance (MR) imaging features of infantile hepatic hemangioendotheliomas before and after treatment. Materials and methods: CT and MR examinations of seven infants with biopsy proven hepatic hemangioendotheliomas were retrospectively analyzed. The distribution, number, size, imaging appearance, enhancement pattern and post-treatment changes of the tumors were evaluated. Results: A total of 153 hepatic hemangioendotheliomas were detected on CT (111) and MR (42) imaging. In six infants, 109/111 (98.2%) tumors were hypodense and 2/111 (1.8%) lesions contained calcification on unenhanced CT. On MR imaging, all 42 lesions in one infant were heterogeneously T1-hypointense and T2-hyperintense compared to the normal liver parenchyma. Contrast-enhanced CT and MRI showed peripheral rim (51.6%), uniform (48.4%), fibrillary (33.3%), and nodular (28.8%) contrast enhancement in the hepatic arterial phase. Homogeneous (100%), rim (98.2%) and mixed enhancement patterns were noted in tumors 2.0 cm and 1.0-2.0 cm in diameter respectively in the hepatic arterial phase. In three patients who underwent steroid therapy, follow-up CT examination demonstrated tumor size reduction and increased intra-tumoral calcification in two patients. Conclusion: Infantile hepatic hemangioendotheliomas show some typical imaging features and size-dependent pattern of contrast enhancement on CT and MR imaging, which allow accurate imaging diagnosis and post-treatment evaluation.

  13. A Novel Feature Extraction Technique Using Binarization of Bit Planes for Content Based Image Classification

    Sudeep Thepade

    2014-01-01

    Full Text Available A number of techniques have been proposed earlier for feature extraction using image binarization. Efficiency of the techniques was dependent on proper threshold selection for the binarization method. In this paper, a new feature extraction technique using image binarization has been proposed. The technique has binarized the significant bit planes of an image by selecting local thresholds. The proposed algorithm has been tested on a public dataset and has been compared with existing widely used techniques using binarization for extraction of features. It has been inferred that the proposed method has outclassed all the existing techniques and has shown consistent classification performance.

  14. Significance of the impact of motion compensation on the variability of PET image features

    Carles, M.; Bach, T.; Torres-Espallardo, I.; Baltas, D.; Nestle, U.; Martí-Bonmatí, L.

    2018-03-01

    In lung cancer, quantification by positron emission tomography/computed tomography (PET/CT) imaging presents challenges due to respiratory movement. Our primary aim was to study the impact of motion compensation implied by retrospectively gated (4D)-PET/CT on the variability of PET quantitative parameters. Its significance was evaluated by comparison with the variability due to (i) the voxel size in image reconstruction and (ii) the voxel size in image post-resampling. The method employed for feature extraction was chosen based on the analysis of (i) the effect of discretization of the standardized uptake value (SUV) on complementarity between texture features (TF) and conventional indices, (ii) the impact of the segmentation method on the variability of image features, and (iii) the variability of image features across the time-frame of 4D-PET. Thirty-one PET-features were involved. Three SUV discretization methods were applied: a constant width (SUV resolution) of the resampling bin (method RW), a constant number of bins (method RN) and RN on the image obtained after histogram equalization (method EqRN). The segmentation approaches evaluated were 40% of SUVmax and the contrast oriented algorithm (COA). Parameters derived from 4D-PET images were compared with values derived from the PET image obtained for (i) the static protocol used in our clinical routine (3D) and (ii) the 3D image post-resampled to the voxel size of the 4D image and PET image derived after modifying the reconstruction of the 3D image to comprise the voxel size of the 4D image. Results showed that TF complementarity with conventional indices was sensitive to the SUV discretization method. In the comparison of COA and 40% contours, despite the values not being interchangeable, all image features showed strong linear correlations (r  >  0.91, p\\ll 0.001 ). Across the time-frames of 4D-PET, all image features followed a normal distribution in most patients. For our patient cohort, the

  15. Feature learning and change feature classification based on deep learning for ternary change detection in SAR images

    Gong, Maoguo; Yang, Hailun; Zhang, Puzhao

    2017-07-01

    Ternary change detection aims to detect changes and group the changes into positive change and negative change. It is of great significance in the joint interpretation of spatial-temporal synthetic aperture radar images. In this study, sparse autoencoder, convolutional neural networks (CNN) and unsupervised clustering are combined to solve ternary change detection problem without any supervison. Firstly, sparse autoencoder is used to transform log-ratio difference image into a suitable feature space for extracting key changes and suppressing outliers and noise. And then the learned features are clustered into three classes, which are taken as the pseudo labels for training a CNN model as change feature classifier. The reliable training samples for CNN are selected from the feature maps learned by sparse autoencoder with certain selection rules. Having training samples and the corresponding pseudo labels, the CNN model can be trained by using back propagation with stochastic gradient descent. During its training procedure, CNN is driven to learn the concept of change, and more powerful model is established to distinguish different types of changes. Unlike the traditional methods, the proposed framework integrates the merits of sparse autoencoder and CNN to learn more robust difference representations and the concept of change for ternary change detection. Experimental results on real datasets validate the effectiveness and superiority of the proposed framework.

  16. Noise characteristics of neutron images obtained by cooled CCD device

    Taniguchi, Ryoichi; Sasaki, Ryoya; Okuda, Shuichi; Okamoto, Ken-Ichi; Ogawa, Yoshihiro; Tsujimoto, Tadashi

    2009-01-01

    The noise characteristics of a cooled CCD device induced by neutron and gamma ray irradiation have been investigated. In the cooled CCD images, characteristic white spot noises (CCD noise) frequently appeared, which have a shape like a pixel in most cases and their brightness is extremely high compared with that of the image pattern. They could be divided into the two groups, fixed pattern noise (FPN) and random noise. The former always appeared in the same position in the image and the latter appeared at any position. In the background image, nearly all of the CCD noises were found to be the FPN, while many of them were the random noise during the irradiation. The random CCD noises increased with irradiation and decreased soon after the irradiation. In the case of large irradiation, a part of the CCD noise remained as the FPN. These facts suggest that the CCD noise is a phenomenon strongly relating to radiation damage of the CCD device.

  17. Polarimetric SAR Image Classification Using Multiple-feature Fusion and Ensemble Learning

    Sun Xun

    2016-12-01

    Full Text Available In this paper, we propose a supervised classification algorithm for Polarimetric Synthetic Aperture Radar (PolSAR images using multiple-feature fusion and ensemble learning. First, we extract different polarimetric features, including extended polarimetric feature space, Hoekman, Huynen, H/alpha/A, and fourcomponent scattering features of PolSAR images. Next, we randomly select two types of features each time from all feature sets to guarantee the reliability and diversity of later ensembles and use a support vector machine as the basic classifier for predicting classification results. Finally, we concatenate all prediction probabilities of basic classifiers as the final feature representation and employ the random forest method to obtain final classification results. Experimental results at the pixel and region levels show the effectiveness of the proposed algorithm.

  18. Features Of Household Lexics, Their Characteristics And Structural Analysis In The Modern English Language

    Aygun Yusifova

    2014-04-01

    Full Text Available The present paper aims to analyze the most inherent features and characteristics of household lexis in English. Special emphasis has been placed on their names of the objects used in everyday life, kitchen utensils, animal and birds. Lexical units concerning ceremonies, habits and traditions are also among the scope of the paper. Moreover, the study deals with the structural features of the units under consideration. It is believed that the thematic-semantic characterization of every-day lexis can have both pedagogical and linguistic implications, especially when dealing with comparative structures.

  19. Compact Representation of High-Dimensional Feature Vectors for Large-Scale Image Recognition and Retrieval.

    Zhang, Yu; Wu, Jianxin; Cai, Jianfei

    2016-05-01

    In large-scale visual recognition and image retrieval tasks, feature vectors, such as Fisher vector (FV) or the vector of locally aggregated descriptors (VLAD), have achieved state-of-the-art results. However, the combination of the large numbers of examples and high-dimensional vectors necessitates dimensionality reduction, in order to reduce its storage and CPU costs to a reasonable range. In spite of the popularity of various feature compression methods, this paper shows that the feature (dimension) selection is a better choice for high-dimensional FV/VLAD than the feature (dimension) compression methods, e.g., product quantization. We show that strong correlation among the feature dimensions in the FV and the VLAD may not exist, which renders feature selection a natural choice. We also show that, many dimensions in FV/VLAD are noise. Throwing them away using feature selection is better than compressing them and useful dimensions altogether using feature compression methods. To choose features, we propose an efficient importance sorting algorithm considering both the supervised and unsupervised cases, for visual recognition and image retrieval, respectively. Combining with the 1-bit quantization, feature selection has achieved both higher accuracy and less computational cost than feature compression methods, such as product quantization, on the FV and the VLAD image representations.

  20. Reversible acute methotrexate leukoencephalopathy: atypical brain MR imaging features

    Ziereisen, France; Damry, Nash; Christophe, Catherine; Dan, Bernard; Azzi, Nadira; Ferster, Alina

    2006-01-01

    Unusual acute symptomatic and reversible early-delayed leukoencephalopathy has been reported to be induced by methotrexate (MTX). We aimed to identify the occurrence of such atypical MTX neurotoxicity in children and document its MR presentation. We retrospectively reviewed the clinical findings and brain MRI obtained in 90 children treated with MTX for acute lymphoblastic leukaemia or non-B malignant non-Hodgkin lymphoma. All 90 patients had normal brain imaging before treatment. In these patients, brain imaging was performed after treatment completion and/or relapse and/or occurrence of neurological symptoms. Of the 90 patients, 15 (16.7%) showed signs of MTX neurotoxicity on brain MRI, 9 (10%) were asymptomatic, and 6 (6.7%) showed signs of acute leukoencephalopathy. On the routine brain MRI performed at the end of treatment, all asymptomatic patients had classical MR findings of reversible MTX neurotoxicity, such as abnormal high-intensity areas localized in the deep periventricular white matter on T2-weighted images. In contrast, the six symptomatic patients had atypical brain MRI characterized by T2 high-intensity areas in the supratentorial cortex and subcortical white matter (n=6), cerebellar cortex and white matter (n=4), deep periventricular white matter (n=2) and thalamus (n=1). MR normalization occurred later than clinical recovery in these six patients. In addition to mostly asymptomatic classical MTX neurotoxicity, MTX may induce severe but reversible unusual leukoencephalopathy. It is important to recognize this clinicoradiological presentation in the differential diagnosis of acute neurological deterioration in children treated with MTX. (orig.)

  1. Efficient and robust model-to-image alignment using 3D scale-invariant features.

    Toews, Matthew; Wells, William M

    2013-04-01

    This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized out in computing a maximum a posteriori alignment solution. The model is learned from features extracted in pre-aligned training images, then fit to features extracted from a new image to identify a globally optimal locally linear alignment solution. Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D. Experiments involving difficult magnetic resonance (MR) images of the human brain demonstrate FBA achieves alignment accuracy similar to widely-used registration methods, while requiring a fraction of the memory and computation resources and offering a more robust, globally optimal solution. Experiments on CT human body scans demonstrate FBA as an effective system for automatic human body alignment where other alignment methods break down. Copyright © 2012 Elsevier B.V. All rights reserved.

  2. Differential diagnostic features of the radionuclide scrotal image

    Mishkin, F.S.

    1977-01-01

    Differential diagnosis of scrotal lesions is aided by correlating radionuclide images with clinical findings. Subacute torsion is associated with peripheral hyperemia and can be mistaken for an inflammatory process; however, in a review of 128 studies, torsion and orchiectomy were the only processes encountered which had a center truly devoid of activity on the tissue phase compared to the normal side. Other lesions such as acute inflammation, abscess, hematoma, and hemorrhagic tumor may superficially appear to lack central activity but invariably contain at least as much activity when compared to the normal side.

  3. Clinical and CT imaging features of abdominal fat necrosis

    Zhao Jinkun; Bai Renju

    2013-01-01

    Fat necrosis is a common pathological change at abdominal cross-sectional imaging, and it may cause abdominal pain, mimic pathological change of acute abdomen, or be asymptomatic and accompany other pathophysiologic processes. Fat necrosis is actually the result of steatosis by metabolism or mechanical injury. Common processes that are present in fat necrosis include epiploic appendagitis, infarction of the greater omentum, pancreatitis, and fat necrosis related to trauma or ischemia. As a common fat disease, fat necrosis should be known by clinicians and radiologists. Main content of this text is the clinical symptoms and CT findings of belly fat necrosis and related diseases. (authors)

  4. Differential diagnostic features of the radionuclide scrotal image

    Mishkin, F.S.

    1977-01-01

    Differential diagnosis of scrotal lesions is aided by correlating radionuclide images with clinical findings. Subacute torsion is associated with peripheral hyperemia and can be mistaken for an inflammatory process; however, in a review of 128 studies, torsion and orchiectomy were the only processes encountered which had a center truly devoid of activity on the tissue phase compared to the normal side. Other lesions such as acute inflammation, abscess, hematoma, and hemorrhagic tumor may superficially appear to lack central activity but invariably contain at least as much activity when compared to the normal side

  5. Prostate cancer multi-feature analysis using trans-rectal ultrasound images

    Mohamed, S S; Salama, M M A; Kamel, M; El-Saadany, E F; Rizkalla, K; Chin, J

    2005-01-01

    This note focuses on extracting and analysing prostate texture features from trans-rectal ultrasound (TRUS) images for tissue characterization. One of the principal contributions of this investigation is the use of the information of the images' frequency domain features and spatial domain features to attain a more accurate diagnosis. Each image is divided into regions of interest (ROIs) by the Gabor multi-resolution analysis, a crucial stage, in which segmentation is achieved according to the frequency response of the image pixels. The pixels with a similar response to the same filter are grouped to form one ROI. Next, from each ROI two different statistical feature sets are constructed; the first set includes four grey level dependence matrix (GLDM) features and the second set consists of five grey level difference vector (GLDV) features. These constructed feature sets are then ranked by the mutual information feature selection (MIFS) algorithm. Here, the features that provide the maximum mutual information of each feature and class (cancerous and non-cancerous) and the minimum mutual information of the selected features are chosen, yeilding a reduced feature subset. The two constructed feature sets, GLDM and GLDV, as well as the reduced feature subset, are examined in terms of three different classifiers: the condensed k-nearest neighbour (CNN), the decision tree (DT) and the support vector machine (SVM). The accuracy classification results range from 87.5% to 93.75%, where the performance of the SVM and that of the DT are significantly better than the performance of the CNN. (note)

  6. Combining low level features and visual attributes for VHR remote sensing image classification

    Zhao, Fumin; Sun, Hao; Liu, Shuai; Zhou, Shilin

    2015-12-01

    Semantic classification of very high resolution (VHR) remote sensing images is of great importance for land use or land cover investigation. A large number of approaches exploiting different kinds of low level feature have been proposed in the literature. Engineers are often frustrated by their conclusions and a systematic assessment of various low level features for VHR remote sensing image classification is needed. In this work, we firstly perform an extensive evaluation of eight features including HOG, dense SIFT, SSIM, GIST, Geo color, LBP, Texton and Tiny images for classification of three public available datasets. Secondly, we propose to transfer ground level scene attributes to remote sensing images. Thirdly, we combine both low-level features and mid-level visual attributes to further improve the classification performance. Experimental results demonstrate that i) Dene SIFT and HOG features are more robust than other features for VHR scene image description. ii) Visual attribute competes with a combination of low level features. iii) Multiple feature combination achieves the best performance under different settings.

  7. Comparison of image features calculated in different dimensions for computer-aided diagnosis of lung nodules

    Xu, Ye; Lee, Michael C.; Boroczky, Lilla; Cann, Aaron D.; Borczuk, Alain C.; Kawut, Steven M.; Powell, Charles A.

    2009-02-01

    Features calculated from different dimensions of images capture quantitative information of the lung nodules through one or multiple image slices. Previously published computer-aided diagnosis (CADx) systems have used either twodimensional (2D) or three-dimensional (3D) features, though there has been little systematic analysis of the relevance of the different dimensions and of the impact of combining different dimensions. The aim of this study is to determine the importance of combining features calculated in different dimensions. We have performed CADx experiments on 125 pulmonary nodules imaged using multi-detector row CT (MDCT). The CADx system computed 192 2D, 2.5D, and 3D image features of the lesions. Leave-one-out experiments were performed using five different combinations of features from different dimensions: 2D, 3D, 2.5D, 2D+3D, and 2D+3D+2.5D. The experiments were performed ten times for each group. Accuracy, sensitivity and specificity were used to evaluate the performance. Wilcoxon signed-rank tests were applied to compare the classification results from these five different combinations of features. Our results showed that 3D image features generate the best result compared with other combinations of features. This suggests one approach to potentially reducing the dimensionality of the CADx data space and the computational complexity of the system while maintaining diagnostic accuracy.

  8. Thin plate spline feature point matching for organ surfaces in minimally invasive surgery imaging

    Lin, Bingxiong; Sun, Yu; Qian, Xiaoning

    2013-03-01

    Robust feature point matching for images with large view angle changes in Minimally Invasive Surgery (MIS) is a challenging task due to low texture and specular reflections in these images. This paper presents a new approach that can improve feature matching performance by exploiting the inherent geometric property of the organ surfaces. Recently, intensity based template image tracking using a Thin Plate Spline (TPS) model has been extended for 3D surface tracking with stereo cameras. The intensity based tracking is also used here for 3D reconstruction of internal organ surfaces. To overcome the small displacement requirement of intensity based tracking, feature point correspondences are used for proper initialization of the nonlinear optimization in the intensity based method. Second, we generate simulated images from the reconstructed 3D surfaces under all potential view positions and orientations, and then extract feature points from these simulated images. The obtained feature points are then filtered and re-projected to the common reference image. The descriptors of the feature points under different view angles are stored to ensure that the proposed method can tolerate a large range of view angles. We evaluate the proposed method with silicon phantoms and in vivo images. The experimental results show that our method is much more robust with respect to the view angle changes than other state-of-the-art methods.

  9. Spectral characteristics and feature selection of satellite remote sensing data for climate and anthropogenic changes assessment in Bucharest area

    Zoran, Maria; Savastru, Roxana; Savastru, Dan; Tautan, Marina; Miclos, Sorin; Cristescu, Luminita; Carstea, Elfrida; Baschir, Laurentiu

    2010-05-01

    Urban systems play a vital role in social and economic development in all countries. Their environmental changes can be investigated on different spatial and temporal scales. Urban and peri-urban environment dynamics is of great interest for future planning and decision making as well as in frame of local and regional changes. Changes in urban land cover include changes in biotic diversity, actual and potential primary productivity, soil quality, runoff, and sedimentation rates, and cannot be well understood without the knowledge of land use change that drives them. The study focuses on the assessment of environmental features changes for Bucharest metropolitan area, Romania by satellite remote sensing and in-situ monitoring data. Rational feature selection from the varieties of spectral channels in the optical wavelengths of electromagnetic spectrum (VIS and NIR) is very important for effective analysis and information extraction of remote sensing data. Based on comprehensively analyses of the spectral characteristics of remote sensing data is possibly to derive environmental changes in urban areas. The information quantity contained in a band is an important parameter in evaluating the band. The deviation and entropy are often used to show information amount. Feature selection is one of the most important steps in recognition and classification of remote sensing images. Therefore, it is necessary to select features before classification. The optimal features are those that can be used to distinguish objects easily and correctly. Three factors—the information quantity of bands, the correlation between bands and the spectral characteristic (e.g. absorption specialty) of classified objects in test area Bucharest have been considered in our study. As, the spectral characteristic of an object is influenced by many factors, being difficult to define optimal feature parameters to distinguish all the objects in a whole area, a method of multi-level feature selection

  10. Stress fractures: pathophysiology, clinical presentation, imaging features, and treatment options.

    Matcuk, George R; Mahanty, Scott R; Skalski, Matthew R; Patel, Dakshesh B; White, Eric A; Gottsegen, Christopher J

    2016-08-01

    Stress fracture, in its most inclusive description, includes both fatigue and insufficiency fracture. Fatigue fractures, sometimes equated with the term "stress fractures," are most common in runners and other athletes and typically occur in the lower extremities. These fractures are the result of abnormal, cyclical loading on normal bone leading to local cortical resorption and fracture. Insufficiency fractures are common in elderly populations, secondary to osteoporosis, and are typically located in and around the pelvis. They are a result of normal or traumatic loading on abnormal bone. Subchondral insufficiency fractures of the hip or knee may cause acute pain that may present in the emergency setting. Medial tibial stress syndrome is a type of stress injury of the tibia related to activity and is a clinical syndrome encompassing a range of injuries from stress edema to frank-displaced fracture. Atypical subtrochanteric femoral fracture associated with long-term bisphosphonate therapy is also a recently discovered entity that needs early recognition to prevent progression to a complete fracture. Imaging recommendations for evaluation of stress fractures include initial plain radiographs followed, if necessary, by magnetic resonance imaging (MRI), which is preferred over computed tomography (CT) and bone scintigraphy. Radiographs are the first-line modality and may reveal linear sclerosis and periosteal reaction prior to the development of a frank fracture. MRI is highly sensitive with findings ranging from periosteal edema to bone marrow and intracortical signal abnormality. Additionally, a brief description of relevant clinical management of stress fractures is included.

  11. Featured Image: A Molecular Cloud Outside Our Galaxy

    Kohler, Susanna

    2018-06-01

    What do molecular clouds look like outside of our own galaxy? See for yourself in the images above and below of N55, a molecular cloud located in the Large Magellanic Cloud (LMC). In a recent study led by Naslim Neelamkodan (Academia Sinica Institute of Astronomy and Astrophysics, Taiwan), a team of scientists explore N55 to determine how its cloud properties differ from clouds within the Milky Way. The image above reveals the distribution of infrared-emitting gas and dust observed in three bands by the Spitzer Space Telescope. Overplotted in cyan are observations from the Atacama Submillimeter Telescope Experiment tracing the clumpy, warm molecular gas. Below, new observations from the Atacama Large Millimeter/submillimeter Array (ALMA) reveal the sub-parsec-scale molecular clumps in greater detail, showing the correlation of massive clumps with Spitzer-identified young stellar objects (crosses). The study presented here indicates that this cloud in the LMC is the site of massive star formation, with properties similar to equivalent clouds in the Milky Way. To learn more about the authors findings, check out the article linked below.CitationNaslim N. et al 2018 ApJ 853 175. doi:10.3847/1538-4357/aaa5b0

  12. Featured Image: A New Dark Vortex on Neptune

    Kohler, Susanna

    2018-03-01

    This remarkable series of images by the Hubble Space Telescope (click for the full view) track a dark vortex only the fifth ever observed on Neptune as it evolves in Neptunes atmosphere. These Hubble images, presented in a recent study led by Michael Wong (University of California, Berkeley), were taken in 2015 September, 2016 May, 2016 October, and 2017 October; the observations have monitored the evolution of the vortex as it has gradually weakened and drifted polewards. Confirmation of the vortex solved a puzzle that arose in 2015, when astronomers spotted an unexplained outburst of cloud activity on Neptune. This outburst was likely a group of bright companion clouds that form as air flows over high-pressure dark vortices, causing gases to freeze into methane ice crystals. To learn more about what the authors have since learned by studying this vortex, check out the paper below.CitationMichael H. Wong et al 2018 AJ 155 117. doi:10.3847/1538-3881/aaa6d6

  13. Automatic brain MR image denoising based on texture feature-based artificial neural networks.

    Chang, Yu-Ning; Chang, Herng-Hua

    2015-01-01

    Noise is one of the main sources of quality deterioration not only for visual inspection but also in computerized processing in brain magnetic resonance (MR) image analysis such as tissue classification, segmentation and registration. Accordingly, noise removal in brain MR images is important for a wide variety of subsequent processing applications. However, most existing denoising algorithms require laborious tuning of parameters that are often sensitive to specific image features and textures. Automation of these parameters through artificial intelligence techniques will be highly beneficial. In the present study, an artificial neural network associated with image texture feature analysis is proposed to establish a predictable parameter model and automate the denoising procedure. In the proposed approach, a total of 83 image attributes were extracted based on four categories: 1) Basic image statistics. 2) Gray-level co-occurrence matrix (GLCM). 3) Gray-level run-length matrix (GLRLM) and 4) Tamura texture features. To obtain the ranking of discrimination in these texture features, a paired-samples t-test was applied to each individual image feature computed in every image. Subsequently, the sequential forward selection (SFS) method was used to select the best texture features according to the ranking of discrimination. The selected optimal features were further incorporated into a back propagation neural network to establish a predictable parameter model. A wide variety of MR images with various scenarios were adopted to evaluate the performance of the proposed framework. Experimental results indicated that this new automation system accurately predicted the bilateral filtering parameters and effectively removed the noise in a number of MR images. Comparing to the manually tuned filtering process, our approach not only produced better denoised results but also saved significant processing time.

  14. A novel algorithm to detect glaucoma risk using texton and local configuration pattern features extracted from fundus images.

    Acharya, U Rajendra; Bhat, Shreya; Koh, Joel E W; Bhandary, Sulatha V; Adeli, Hojjat

    2017-09-01

    Glaucoma is an optic neuropathy defined by characteristic damage to the optic nerve and accompanying visual field deficits. Early diagnosis and treatment are critical to prevent irreversible vision loss and ultimate blindness. Current techniques for computer-aided analysis of the optic nerve and retinal nerve fiber layer (RNFL) are expensive and require keen interpretation by trained specialists. Hence, an automated system is highly desirable for a cost-effective and accurate screening for the diagnosis of glaucoma. This paper presents a new methodology and a computerized diagnostic system. Adaptive histogram equalization is used to convert color images to grayscale images followed by convolution of these images with Leung-Malik (LM), Schmid (S), and maximum response (MR4 and MR8) filter banks. The basic microstructures in typical images are called textons. The convolution process produces textons. Local configuration pattern (LCP) features are extracted from these textons. The significant features are selected using a sequential floating forward search (SFFS) method and ranked using the statistical t-test. Finally, various classifiers are used for classification of images into normal and glaucomatous classes. A high classification accuracy of 95.8% is achieved using six features obtained from the LM filter bank and the k-nearest neighbor (kNN) classifier. A glaucoma integrative index (GRI) is also formulated to obtain a reliable and effective system. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Two-Level Evaluation on Sensor Interoperability of Features in Fingerprint Image Segmentation

    Ya-Shuo Li

    2012-03-01

    Full Text Available Features used in fingerprint segmentation significantly affect the segmentation performance. Various features exhibit different discriminating abilities on fingerprint images derived from different sensors. One feature which has better discriminating ability on images derived from a certain sensor may not adapt to segment images derived from other sensors. This degrades the segmentation performance. This paper empirically analyzes the sensor interoperability problem of segmentation feature, which refers to the feature’s ability to adapt to the raw fingerprints captured by different sensors. To address this issue, this paper presents a two-level feature evaluation method, including the first level feature evaluation based on segmentation error rate and the second level feature evaluation based on decision tree. The proposed method is performed on a number of fingerprint databases which are obtained from various sensors. Experimental results show that the proposed method can effectively evaluate the sensor interoperability of features, and the features with good evaluation results acquire better segmentation accuracies of images originating from different sensors.

  16. Clinicopathological and imaging features of lipoastrocytoma: Case report.

    Sivaraju, Laxminadh; Aryan, Saritha; Ghosal, Nandita; Hegde, Alangar S

    2018-02-01

    Lipidized tumors of the central nervous system are very uncommon, with only a few cases described. We report a case of a 25-year-old woman with a tumor involving the left premotor area. She underwent gross total excision. Histologically, the tumor was composed of glial fibrillary acidic protein-positive glial cells with areas of lipidization. A diagnosis of lipoastrocytoma was rendered. At three-year follow-up she was doing well, supporting the presumed favorable prognosis of these uncommon tumors. Absence of xanthochromic appearance, mitotic activity, necrosis and poor reticulin activity are the differentiating features from the pleomorphic xanthoastrocytoma. We highlighted that these tumors involve the adult and pediatric population and distribute in both supratentorial and infratentorial compartments as well as in the spinal cord.

  17. Unusual magnetic resonance imaging features in Menkes disease

    Barnerias, C.; Desguerre, I.; Dulac, O.; Bahi-Buisson, N.; Boddaert, N.; Hertz-Pannier, L.; Boddaert, N.; Guiraud, P.; Hertz-Pannier, L.; Dulac, O.; Bahi-Buisson, N.; Hertz-Pannier, L.; Dulac, O.; Bahi-Buisson, N.; De Lonlay, P.

    2008-01-01

    We present a case of an inherited disorder of copper metabolism, Menkes disease in which MRI studies revealed the coexistence of T2 hyper-signal in the temporal white matter with an increase of apparent diffusion coefficient indicative of vasogenic oedema combined with T2 hyper-signal of the putamen and head of the caudate and decreased apparent diffusion coefficient indicative of cytotoxic oedema. These unusual MRI features emphasize the interest of newly developed techniques in early diagnosis in Menkes disease. The acute cerebral damage might result from the combined effects of acute metabolic stress due to infectious disease and prolonged status epilepticus, acting on a highly susceptible developing brain. Vasogenic oedema in the temporal white matter could be related to prolonged status epilepticus and vascular abnormalities. Cytotoxic oedema of the putamen and head caudate could result from energetic failure. (authors)

  18. Unusual magnetic resonance imaging features in Menkes disease

    Barnerias, C; Desguerre, I; Dulac, O; Bahi-Buisson, N [Hop Necker Enfants Malades, AP-HP, Dept Paediat Neurol and Metab Dis, F-75743 Paris 15 (France); Boddaert, N; Hertz-Pannier, L [Hop Necker Enfants Malad, AP-HP, Dept Pediat Radiol, F-75743 Paris (France); Boddaert, N [CEA, Serv Hosp Frederic Joliot, INSERM, U797, F-91406 Orsay (France); Guiraud, P [Univ Grenoble, Serv Biochim, Genet Hop, Grenoble (France); Hertz-Pannier, L; Dulac, O; Bahi-Buisson, N [INSERM, U663, F-75015 Paris (France); Hertz-Pannier, L; Dulac, O; Bahi-Buisson, N [Univ Paris 05, F-75005 Paris (France); De Lonlay, P [Hop Necker Enfants Malades, AP-HP, Dept Paediat Neurol and Metab Dis, F-75743 Paris 15 (France); Hop Necker Enfants Malades, AP HP, Ctr Reference Malad Metab, F-75743 Paris 15 (France)

    2008-07-01

    We present a case of an inherited disorder of copper metabolism, Menkes disease in which MRI studies revealed the coexistence of T2 hyper-signal in the temporal white matter with an increase of apparent diffusion coefficient indicative of vasogenic oedema combined with T2 hyper-signal of the putamen and head of the caudate and decreased apparent diffusion coefficient indicative of cytotoxic oedema. These unusual MRI features emphasize the interest of newly developed techniques in early diagnosis in Menkes disease. The acute cerebral damage might result from the combined effects of acute metabolic stress due to infectious disease and prolonged status epilepticus, acting on a highly susceptible developing brain. Vasogenic oedema in the temporal white matter could be related to prolonged status epilepticus and vascular abnormalities. Cytotoxic oedema of the putamen and head caudate could result from energetic failure. (authors)

  19. Ultrasound introscopic image quantitative characteristics for medical diagnosis

    Novoselets, Mikhail K.; Sarkisov, Sergey S.; Gridko, Alexander N.; Tcheban, Anatoliy K.

    1993-09-01

    The results on computer aided extraction of quantitative characteristics (QC) of ultrasound introscopic images for medical diagnosis are presented. Thyroid gland (TG) images of Chernobil Accident sufferers are considered. It is shown that TG diseases can be associated with some values of selected QCs of random echo distribution in the image. The possibility of these QCs usage for TG diseases recognition in accordance with calculated values is analyzed. The role of speckle noise elimination in the solution of the problem on TG diagnosis is considered too.

  20. An improved feature extraction algorithm based on KAZE for multi-spectral image

    Yang, Jianping; Li, Jun

    2018-02-01

    Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.

  1. Identification of natural images and computer-generated graphics based on statistical and textural features.

    Peng, Fei; Li, Jiao-ting; Long, Min

    2015-03-01

    To discriminate the acquisition pipelines of digital images, a novel scheme for the identification of natural images and computer-generated graphics is proposed based on statistical and textural features. First, the differences between them are investigated from the view of statistics and texture, and 31 dimensions of feature are acquired for identification. Then, LIBSVM is used for the classification. Finally, the experimental results are presented. The results show that it can achieve an identification accuracy of 97.89% for computer-generated graphics, and an identification accuracy of 97.75% for natural images. The analyses also demonstrate the proposed method has excellent performance, compared with some existing methods based only on statistical features or other features. The method has a great potential to be implemented for the identification of natural images and computer-generated graphics. © 2014 American Academy of Forensic Sciences.

  2. Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

    Guo, Shengwen; Lai, Chunren; Wu, Congling; Cen, Guiyin; Hariharan, A.; Vijayakumari, Anupa A.; Aarabi, Mohammad Hadi; Aballi, John; Nour, Abd Elazeim Abd Alla Mohamed; Abdelaziz, Mohammed; Abdolalizadeh, AmirHussein; Abdollahi, Mahsa; Abdul Aziz, Siti Aishah; Salam, Amritha Abdul; Abdulaziz, Nidhal; Abdulkadir, Ahmed; Abdullah, Sachal; Abdullah, Osama; Abrigo, Jill; Adachi, Noriaki; Adamson, Christopher; Adduru, Viraj; Adel, Tameem; Aderghal, Karim; Ades-Aron, Benjamin; Adeyosoye, Michael; Adlard, Paul; Srinivasa, Ag; Aganj, Iman; Agarwal, Ayush; Agarwal, Anupam; Agarwal, Anchit; Aguero, Cinthya; Aguiar, Pablo; Ahdidan, Jamila; Ahmad, Fayyaz; Ahmad, Rziwan; Ahmadi, Hessam; Ahmed, Nisar; Sid, Farid Ahmed; Ai, Edward; Ai, Qing; Aicha, Benyahia; Aitharaju, Sai; Aiyer, Aditya; Akkus, Zeynettin; Akodad, Sanae; Akramifard, Hamid; Aksman, Leon; Aktas, Said; Al-Janabi, Omar; Al-Nuaimi, Ali; AlAila, BahaaEddin; Alakwaa, Fadhl; Alam, Saruar; Alam, Fakhre; Alam Zaidi, Syed Farhan; Alan, Wiener; Alansari, Mukhtar; Alareqi, Ebrahim; Alberdi, Ane; Albsoul, Mohammad; Alderson, Thomas; Aleem, Hassan; Alex, Aishwarya; Alexander, Jacob; Alexopoulos, Panagiotis; Alfoldi, Jessica; Ali, Ayesha; Ali, Imdad; Alimoradian, Shirin; Aljabar, Paul; Aljabbouli, Hasan; Aljovic, Almir; Allen, Genevera; Alliende, Luz Maria; Almaguel, Frankis; Almgren, Hannes; Montes, Carmen Alonso; Alowaisheq, Tasneem; Alryalat, Saif Aldeen; Alsado, Majd; Alsaedi, Abdalrahman; Alshehri, Haifa; Altaf, Tooba; Altendahl, Marie; Altmann, Andre; Alvand, Ashkan; Filho, Manoel Alves; Alzubi, Raid; Amaral, Robert; Ambatipudi, Mythri; Amernath, Remya; Amlien, Inge; Amoroso, Nicola; Amri, Hakima; Anastasiou, Athanasios; Anbarasi, Jani; Anbarjafari, Gholamreza; Anderson, Wes; Anderson, Jeff; Anderson, Valerie; Anderson, Loretta; Andonov, Jovan; Andova, Vesna; Andreopoulou, Irene; Andrews, K. Abigail; Andrews, Cameron; Angeles, Michel; Anne-Laure, Aziz; Ansari, Ghulam Jillani; Ansari, Sharaf; Anstey, Kaarin; Antunes, Augusto; Aoshuang, Zhang; Aouf, Mazin; Aow Yong, Li Yew; Aporntewan, Chatchawit; Apostolova, Liana; Appiah, Frank; Apsvalka, Dace; Arab, Abazar; Araque Caballero, Miguel Ángel; Arbabyazd, Mohammad; Arbelaez, Pablo; Archer, Kellie; Ardekani, Babak; Aretouli, Eleni; Arfanakis, Konstantinos; Arisi, Ivan; Armentrout, Steven; Arnold, Matthias; Arnold, Steven; Arslan, Salim; Artacho-Perula, Emilio; Arthofer, Christoph; Aruchamy, Srinivasan; Arya, Zobair; Pizarro, Carlos Asensio; Ashford, Wes; Ashraf, Azhaar; Askland, Kathleen; Aslaksen, Per; Aslakson, Eric; Aso, Toshihiko; Astphan, Michele; Ataloglou, Dimitrios; Atay, Meltem; Athanas, Argus; Atri, Roozbeh; Au, April; Aurich, Maike; Avants, Brian; Awasthi, Niharika; Awate, Suyash; Ayaz, Aymen; Son, Yesim Aydin; Aydogan, Dogu Baran; Ayhan, Murat; Ayton, Scott; Aziz, Adel; Azmi, Mohd Hafrizal; Ba, Maowen; Bach, Kevin; Badea, Alexandra; Bag, Asim; Bagewadi, Shweta; Bai, Xiangqi; Bai, Zilong; Bai, Haoli; Baird, Geoffrey; Baiwen, Zhang; Baker, Elizabeth; Baker, John; Bakker, Arnold; Ball, Erika; Ballén Galindo, Miguel Ángel; Banaei, Amin; Bandyopadhyay, Dipankar; Bang, Ki Hun; Bangen, Katherine; Banks, Sarah; Banning, Leonie; Bao, Wan Yun; Barakat, Rita; Barbará, Eduardo; Barber, Philip; Barber, Robert; de Araujo, Flavia Roberta Barbosa; Barnes, Josephine; Barredo, Jennifer; Barret, Olivier; Barrett, Matthew; Barsamian, Barsam; Barsky, Andrey; Bartel, Fabian; Bartoszewicz, Jakub; Bartram-Shaw, David; Barwood, Caroline; Basavaraj, Suryakanth; Basavaraj, Arshitha; Basiouny, Ahmed; Baskaran, Bhuvaneshwari; Basu, Arindam; Baths, Veeky; Bathula, Deepti; Batmanghelich, Nematollah Kayhan; Bauer, Roman; Bauer, Corinna; Bawa, Vanshika; Bayley, Peter; Bayram, Ali; Bazi, Yakoub; Beach, Thomas; Beaudoin, Kristin; Beaulieu, Christian; Becker, Cassiano; Beckett, Laurel; Bedding, Alun; Beer, Simone; Beer, Joanne; Beg, Mirza Faisal; Behfar, Qumars; Behjat, Hamed; Behjat, Hamid; Behseta, Sam; Bekris, Lynn; Suresh, Mahanand Belathur; Belichenko, Nadia; Bellio, Maura; Belyaev, Mikhail; Bemiller, Shane; Ahmed, Olfa Ben; Ben Bouallègue, Fayçal; Benedikt, Michael; Benge, Jared; Benitez, Andreana; Benlloch, Jose María; Benn, Marianne; Benyoussef, El Mehdi; Bergeron, David; Bermudez, Elaine; Bessadok, Alaa; Betzel, Richard; Bezuidenhoudt, Mauritz; Bhagwat, Nikhil; Bhalerao, Shailesh; Bhandari, Anindya; Bhasin, Harsh; Bhati, Radhika; Bhatkoti, Pushkar; Bhatt, Priya; Bhattacharjee, Debotosh; Bhattacharyya, Sudeepa; Bi, Rui; Bi, Jinbo; Bi, Harvy; Biancardi, Alberto; Bidart, Rene; Bilgel, Murat; Billiet, Thibo; Binczyk, Franciszek; Bingsheng, Huang; Bird, Christopher; Bischof, Gérard; Bishnoi, Ram; Biswas, Shameek; Bjelke, David; Black, Sandra; Blackwood, Jennifer; Blaese, Elise; Blair, James; Blanchard, Gilles; Bloom, Toby; Blujus, Jenna; Blusztajn, Jan Krzysztof; Bo, Wu; Bo, Jun; Boda, Ravi; Boellaard, Ronald; Bogorodzki, Piotr; Bokde, Arun; Bolhasani, Ehsan; Bonakdarpour, Borna; Bonazzoli, Matthew; Bône, Alexandre; Borkowsky, Jennifer; Borrajo, Danielle; Bos, Isabelle; Bosco, Paolo; Bott, Nicholas; Rodrigues, Renato Botter Maio Lopes; Boughanmi, Amani; Bougias, Haralabos; Boulier, Thomas; Bourgeat, Pierrick; Bouyagoub, Samira; Bowes, Mike; Boyes, Richard; Bozoki, Andrea; Bradshaw, Tyler; Pereira, Joana Braga; Brahami, Yoann; Brambati, Simona Maria; Bras, Jose; Braskie, Meredith; Brecheisen, Ralph; Bregman, Noa; Brewer, James; Briassouli, Alexia; Brickman, Adam; Bridges, Robert; Brihmat, Nabila; Brinkmann, Benjamin; Britschgi, Markus; Broers, Thomas; Bron, Esther; Brown, Jesse; Brown, Matthew; Brown, Abel; Brown, Maria; Brunberg, James; Bu, Tao; Bubbico, Giovanna; Bubenik, Peter; Bubu, Omonigho; Buchanan, Daniel; Buchholz, Hans-Georg; Buchsbaum, Bradley; Buck, Katharina; Buckley, Rachel; Budgeon, Charley; Buhl, Derek; Sánchez, Manuel Buitrago; Bundela, Saurabh; Burciu, Irina; Burgos, Ninon; Burke, Shanna; Burn, Katherine; Burns, Jeffrey; Burns, Gully; Burzykowski, Tomasz; Bush, Sammie; Buss, Stephanie; Butcher, Bradley; Butt, Victoria; Buxbaum, Joseph; Sandeep, C. S.; Cabrera, Cristóbal; Cahyaningrum, Winda; Cai, Zhen-Nao; Cai, Siqi; Cai, Erik; Cajka, Tomas; Calamia, Matthew; Caligiuri, Maria Eugenia; Calixte, Christopher; Calon, Frederic; Cameron, Briana; Campbell, Roy; Lopez, Jose Antonio Campos; Cao, Hongliu; Cao, Jiguo; Cao, Guanqun; Cao, Bo; Capizzano, Aristides; Capon, Daniel; Carmasin, Jeremy; Carmichael, Owen; Carr, Sarah; Carrier, Jason; Carter, Greg; Carvalho, Luis; Carvalho, Janessa; Carvalho, Carolina; Casamitjana, Adrià; Casanova, Ramon; Casas, Josep R.; Cash, David; Castelluccio, Pete; Castiglioni, Isabella; Caswell, Carrie; Cattell, Liam; Cauda, Franco; Cepeda, Ileana; Çevik, Alper; Cha, Jungho; Chakrabarti, Shreya; Chakraborty, Shouvik; Chammam, Takwa; Chan, Christina; Chand, Ganesh; Chang, Catie; Chang, Yu-Ming; Chang, Rui; Chang, Hyunggi; Chang, Yu-Chuan; Chang, Ki Jung; Chang, Che-Wei; Chantrel, Steeve; Chao, Justin; Chao, Linda; Chapleau, Marianne; Charil, Arnaud; Chatterjee, Pratishtha; Chatterjee, Sambit; Chaudhry, Zainab; Chauhan, Harmanpreet; Chehade, Abdallah; Chekuri, Omkar; Cheloshkina, Kseniia; Chen, Jianhong; Chen, Gang; Chen, Geng; Chen, Ting-Huei; Chen, Yin Jie; Chen, Xi; Chen, Tzu-Chieh; Chen, Guojun; Chen, Shuzhong; Chen, Jerome; Chen, Fang; Chen, Kaifeng; Chen, Gennan; Chen, Jason; Chen, Guanhua; Chen, Ying-Hsiang; Chen, Ming-Hui; Chen, Chenbingyao; Chen, S. Y.; Chen, Hsu-Hsin; Chen, Xing; Chen, Kewei; Chen, Yuhan; Chen, Hugo; Chen, Rong; Chen, Ing-jou; Chen, Jun; Chen, Jean; Chen, Bo; Cheng, Danni; Cheng, Hewei; Cheng, Yong; Cheng, Yang; Cheng, Zhang; Cheng, Wai Ho; Chenhall, Tanya; Chepkoech, Joy-Loi; Cherukuri, Venkateswararao; Chhibber, Aparna; Chi, Haoyuan; Chi, Chih-Lin; Chiang, Gloria; Chiesa, Patrizia; Childress, Daniel Micah; Chilukuri, Yogitha; Fatt, Cherise Chin; Chincarini, Andrea; Ching, Christopher; Chiotis, Konstantinos; Cho, Soo Hyun; Cho, Yongrae; Cho, Sooyun; Choi, Jun-Sik; Choi, Hongyoon; Choi, Yeoreum; Choi, Sophia; Choi, Jaesik; Choi, Euna; Choo, I. L. Han; Chopra, Vishal; Chougrad, Hiba; Chouraki, Vincent; Christini, Amanda; Chu, Yufang; Chuang, Tzu-Chao; Chuanji, Luo; Chuanjian, Yu; Chun, Marvin; Chun, Sung; Chung, Ai; Chung, Yu-Min; Chung, Jung-Che; Chung, Ai Wern; Chung, Jaeeun; Chyzhyk, Darya; Ciarleglio, Adam; Cioli, Claudia; Cittanti, Corrado; Cives, Ana; Clark, Marissa; Clayton, David; Clement, Mark; Clifft, Daniel; Climer, Sharlee; Clouston, Sean; Clunie, David; Cohen, Phoebe; Cohen, Taco; Cole, Michael; Cole, James; Colletti, Patrick; Collingwood, Joanna; Comley, Robert; Conklin, Bryan; Conner, Lindsay; Conover, Joanne; Contardo-Berning, Ivona; Conway, Ronan; Copani, Agata; Coppola, Giovanni; Corbett, Syl; Corlier, Fabian; Correia, Rui; Cosman, Joshua; Costantino, Sebastian; Coubard, Olivier; Coulson, Elizabeth; Couser, Elizabeth; Cox, Kris; Coyle, Patrick; Cozzi, Brian; Craddock, Cameron; Crawford, Karen; Creese, Byron; Cribben, Ivor; Crisostomo-Wynne, Theodore; Crossley, Nicolas; Croteau, Etienne; Cruchaga, Carlos; Cuajungco, Math; Cui, Jing; Cui, Sue; Cullen, Nicholas; Cuneo, Daniel; Cutanda, Vicente; Cynader, Max; Binu, D.; D'Avossa, Giovanni; Dai, Tian; Dai, Peng; Dai, Hui; Davied Hong, Daivied Hong; Dakovic, Marko; Dalca, Adrian; Damiani, Stefano; Dammak, Mouna; Damoiseaux, Jessica; Dan, Zou; Dang, Xuan Hong; Dang, Shilpa; Daniel, Zinkert; Danjou, Fabrice; Darby, Eveleen; Darby, Ryan; Dardzinska, Agnieszka; Darst, Burcu; Darvesh, Sultan; Das, Kalyan; Das, Devsmita; Das, Sandhitsu; Das, Dulumani; Datta, Shounak; Dauvillier, Jérôme; Davatzikos, Christos; Davidson, Ian; de Boer, Renske; de Bruijne, Marleen; de Buhan, Maya; de Jager, Philip; de La Concha Vega, Nuño; de Lange, Siemon; de Luis Garcia, Rodrigo; de Marco, Matteo; de Sitter, Alexandra; Dean, Scott; Decarli, Charles; Decker, Summer; del Gaizo, John; Demir, Zeynep; Denby, Charles; Deng, Yanjia; Deng, Wanyu; Denisova, Kristina; Denney, William; Depue, Brendan; DeRamus, Thomas; Desikan, Rahul; Desplats, Paula; Desrosiers, Christian; Devadas, Vivek; Devanarayan, Viswanath; Devarajan, Sridharan; Devenyi, Gabriel; Dezhina, Zalina; Dhami, Devendra; Dharsee, Moyez; Dhillon, Permesh; Di, Xin; Di Mauro, Nicola; Diah, Kimberly; Diamond, Sara; Diaz-Asper, Catherine; Diciotti, Stefano; Dickerson, Bradford; Dickie, David Alexander; Dickinson, Philip; Dicks, Ellen; Diedrich, Karl; Dieumegarde, Louis; Dill, Vanderson; Dilliott, Allison; Ding, Zhaohua; Ding, Shanshan; Ding, Yanhui; Ding, Xiuhua; Ding, Xuemei; Dinov, Ivo; Dinu, Valentin; Diouf, Ibrahima; Dmitriev, Phillip; Dobromyslin, Vitaly; Dodge, Hiroko; Dolui, Sudipto; Dona, Olga; Dondelinger, Frank; Dong, Wen; Dong, Hao-Ming; Kehoe, Patricio Donnelly; Donohue, Michael; Dore, Vincent; Dougherty, Chase; Doughty, Mitchell; Dowling, N. Maritza; Doyle, Senan; Doyle, Andrew; Dragan, Matthew; Draganski, Bogdan; Draghici, Sorin; Dragomir, Andrei; Drake, Derek; Drake, Erin; Drd, Shilpa; Dronkers, Nina; Drozdowski, Madelyn; Du, Changde; Du, Yuhui; Du, Lei; Du, Guangwei; Du, Xingqi; Duan, Fang; Duan, Yuzhuo; Duan, Kuaikuai; Duchesne, Simon; Duggento, Andrea; Dukart, Juergen; Dumont, Matthieu; Dunn, Ruth; Duong, Vu; Duraisamy, Baskar; Duran, Tugce; Durrleman, Stanley; Dutta, Joyita; Dyrba, Martin; Dyvorne, Hadrien; R, Amulya E.; Eads, Jennifer; Eastman, Jennifer; Eaton, Susan; Edlund, Christopher; Edmonds, Emily; Edmondson, Mackenzie; Ehsan, Fatima; El-Gabalawy, Fady; Elander, Annie; Elango, Vidhya E.; Eldeeb, Ghaidaa; Elgamal, Fatmaelzahraa; Rodrigues, Yuri Elias; Elman, Jeremy; Elrakaiby, Nada; Emahazion, Tesfai; Emami, Behnaz; Embrechts, Jurriën; Emran Khan Emon, Mohammad Asif; Emrani, Saba; Emrani, Asieh; Emri, Miklós; Engelhardt, Barbara; Engle, Bob; Epstein, Noam; Er, Fusun; Erhardt, Erik; Eriksson, Oscar; Omay, Zeynep Erson; Escudero, Javier; Eshleman, Jason; Eskildsen, Simon; Espinosa, Luis; Essex, Ryan; Esteban, Oscar; Estrada, Karol; Ethell, Douglas; Ethridge, Kimberly; Ettehadi, Seyedrohollah; Eva, Bouguen; Evenden, Dave; Evtikheeve, Rina; Ewert, Siobhan; Fague, Scot; Fahmi, Rachid; Faizal, Sherin; Falahati, Farshad; Fan, Li; Fan, Zhen; Fan, Yong; Fan, Maohua; Fan, Yonghui; Fan, Sili; Fan, Ruzong; Fang, Chen; Fang, Xiaoling; Fanjul-Vélez, Félix; Fanti, Alessandro; Far, Bab; Farah, Martha; Farahani, Naemeh; Farahibozorg, Seyedehrezvan; Farahnak, Farhood; Farajpour, Maryam; Fardo, David; Farkhani, Sadaf; Farnsworth, Bryn; Farooq, Hamza; Farooq, Ammarah; Farouk, Yasmeen; Farrar, Danielle; Farrer, Lindsay; Fatemehh, Fatemeh; Fatemizadeh, Emad; Fatfat, Kim; Fatima, Shizza; Faux, Noel; Favan-Niven, Anne; Favary, Clélia; Fazlollahi, Amir; Fei, Gao; Feingold, Franklin; Feizi, Soheil; Félix, Eloy; Femminella, Grazia Daniela; Feng, Zijun; Feng, Ao; Feng, Brad; Feng, Xinyang; Feragen, Aasa; Fereidouni, Marzieh; Fernandes, Miguel; Fernández, Víctor; Ferrari, Ricardo; Ferraris, Sebastiano; Ferreira, Francisco; Ferreira, Luiz Kobuti; Ferreira, Hugo; Fiecas, Mark; Fieremans, Els; Fiford, Cassidy; Figurski, Michal; Filippi, Massimo; Filshtein, Teresa; Findley, Caleigh; Finger, Elizabeth; Firth, Nicholas; Fischer, Christopher; Fischer, Florian; Fitall, Simon; Fleet, Blair; Fleishman, Greg; Flokas, Lambros; Flores, Alberto; Focke, Niels; Fok, Wai Yan; Foldi, Nancy; Fôlego, Guilherme; Forero, Aura; Fornage, Myriam; Fos Guarinos, Belén; Founshtein, Gregory; Franc, Benjamin; Francois, Clement; Franke, Katja; Fraser, Mark; Frasier, Mark; Frederick, Blaise; Freitas, Fernandho; Escalin, Frency Jj; Freudenberg-Hua, Yun; Friedman, Brad; Friedmann, Theodore; Friedrich, Christoph M.; Frings, Lars; Frisoni, Giovanni; Fritzsche, Klaus; Frolov, Alexander; Frost, Robert; Fu, Ling; Fu, Zening; Fudao, Ke; Fuentes, Emmanuel; Fujishima, Motonobu; Fujiwara, Ken; Fukami, Tadanori; Funk, Cory; Furcila, Diana; Fuselier, Jessica; Nagarjuna Reddy, G.; Gaasterland, Terry; Gabelle, Audrey; Gahm, Jin; Gaiteri, Chris; Gajawelli, Niharika; Galantino, Alexis; Galarza Hernández, Javier; Galasko, Douglas; Galea, Liisa; Galisot, Gaetan; Sánchez, Antonio Javier Gallego; Gallins, Paul; Gamberger, Dragan; Gan, Hong Seng; Gan, Gavin; Ganapathi, Subha; Gancayco, Christina; Gangishetti, Umesh; Ganzetti, Marco; Gao, Fei; Gao, Jingjing; Gao, Linlin; Gao, Tianxiang; Gao, Yuanyuan; Gao, Xiaohong; Garani, Ranjini; Garbarino, Sara; Garcia, Ivan; Garcia, Xiadnai; Garcia, Jorge; Garcia, Tanya; Garcia Arias, Hernan Felipe; de La Garza, Angel Garcia; Gaig, Mireia Garcia; Novoa, Jorge Garcia; Valero, Mar Garcia; Garcia-Ojalvo, Jord; García-Polo, Pablo; Garg, Rahul; Garg, Gaurav; Garg, Divya; Garibotto, Valentina; Garvey, Matthew; Garza-Villarreal, Eduardo; Gaubert, Malo; Gauthier, Serge; Gavett, Brandon; Gavidia, Giovana; Gavtash, Barzin; Gawryluk, Jodie; Gbah, Messon; Ge, Tian; Geerts, Hugo; Geisser, Niklaus; Geng, Junxian; Gentili, Claudio; Gess, Felix; Ghaderi, Halleh; Ghahari, Shabnam; Ghanbari, Yaghoob; Ghazi-Saidi, Ladan; Ghodrati, Mojgan; Ghorbani, Behnaz; Ghoreishiamiri, Reyhaneh; Ghosal, Sayan; Ghosh, Sukanta; Ghosh, Saheb; Ghosh, Sreya; Ghoshal, Ankur; Giannicola, Galetta; Gibert, Karina; Gibson, Gary; Gieschke, Ronald; Gil Valencia, Jorge Mario; Gillen, Daniel; Giordani, Alessandro; Giraldo, Diana; Gispert, Juan D.; Gitelman, Darren; Giuffrida, Mario Valerio; Madhu, G. K.; Glass, Jesse; Glazier, Brad; Gleason, Carey; Glerean, Enrico; Glozman, Tanya; Godbey, Michael; Goettlich, Martin; Gogoi, Minakshi; Gola, Kelly; Golbabaei, Soroosh; Golden, Daniel; Goldstein, Felicia; Gomes, Carlos; de Olivera, Ramon Gomes Durães; Gomez, Isabel; Gomez Gonzalez, Juan Pablo; Gomez-Verdejo, Vanessa; Gong, Weikang; Gong, Enhao; Gong, Kuang; Gonneaud, Julie; Gonzalez, Clio; Gonzalez, Evelio; Gonzalez, Gerardo; Moreira, Eduardo Gonzalez; Goodman, James; Gopinath, Srinath; Gopu, Anusharani; Gordon, Brian; Gordon, David; Gordon, Mark; Gorriz, Juan Manuel; Gors, Dorothy; Göttler, Jens; Gounari, Xanthippi; Goyal, Devendra; Graf, John; Graff, Ariel; Graham, Leah; Graham, Jinko; Grajski, Kamil; Grami, Maziyar; Grand'Maison, Marilyn; Grant, Kiran; Grassi, Elena; Gray, Katherine; Grecchi, Elisabetta; Green, Robert; Green, Elaine; Greenberg, Jonathan; Greening, Steven; Greenwood, Bryson; Gregori, Johannes; Gregory, Michael; Greicius, Michael; Greve, Douglas; Griffin, Jason; Grill, Joshua; Grodner, Kelsey; Grolmusz, Vince; Groot, Perry; Groothuis, Irme; Gross, Alden; Grundstad, Arne; Grundy, Edward; Grzegorczyk, Tomasz; Nandith, G. S.; Gu, David; Gu, Jiena; Gu, Yun; Gu, Ginam; Guan, Sheng; Guan, Yuanfang; Guennel, Tobias; Guerin, Laurent; Guerrero, Ricardo; Guerrier, Laura; Guevara, Pamela; Guggari, Shankru; Roy, Abhijit Guha; Guidotti, Roberto; Guillon, Jérémy; Gulcher, Jeff; Gulia, Sarita; Gumedze, Freedom; Gunawardena, Nishan; Gunn, Roger; Guo, Michael; Guo, Xiao; Guo, Xingzhi; Guo, Yi; Kai, Zhang Guo; Zhao, Ma Guo; Gupta, Navin; Gupta, Anubha; Gupta, Ishaan; Guren, Onan; Gurnani, Ashita; Gurol, Mahmut Edip; Guzman, Gloria; Gyy, Gyy; Rajanna, Vanamala H.; Ha, Seongwook; Haacke, Ewart; Haaksma, Miriam; Habadi, Maryam; Habeck, Christian; Habes, Mohamad; Hackspiel Zarate, Maria Mercedes; Hadimani, Ravi; Hahn, William; Hahn, Tim; Haight, Thaddeus; Hair, Nicole; Haixing, Wang; Hajarolasvadi, Noushin; Hajjar, Ihab; Hajjo, Rima; Halchenko, Yaroslav; Hall, Anette; Hallock, Kevin; Hamdi, Shah Muhammad; Hameed, Farhan; Hamidian, Hajar; Han, Dong; Han, Yang; Han, Hio-Been; Han, Qingchang; Han, Beomsoo; Han, Duke; Han, Shizhong; Han, Xiaoxia; Han, Peipei; Han, Joo Yoon; Han, Dong-Sig; Handsaker, Robert; Hanna-Pladdy, Brenda; Hanseeuw, Bernard; Hansson, Björn; Hao, Yang; Hao, Jhon; Happ, Clara; Harischandra, Dilshan; Haritaoglu, Esin; Harris, Richard; Harris, Breanna; Hart, Brian; Hartzell, James; Harvey, Danielle; Hashimoto, Tsuyoshi; Hasooni, Hossein; Hassan, Moaied; Hassan, Mehdi; Hassanzadeh, Hamid Reza; Hassanzadeh, Oktie; Hatton, Sean; Hawchar, Jinan; Hayashi, Toshihiro; Hayashi, Norio; Hayes, Jasmeet; Hayete, Boris; Haynor, David; He, Linchen; He, Yan; He, Yao; He, Huiguang; Heegaard, Niels; Hefny, Mohamed; Heil, Julius; Heindel, William; Henderson, Samuel; Henf, Judith; Henriquez, Claudio; Herholz, Karl; Hermessi, Haithem; Hernandez, Monica; Herrera, Luis; Hibar, Derrek; Hidane, Moncef; Higuchi, Satomi; Hind, Jade; Hives, Florent; Hoang, Mimi; Hobel, Zachary; Hoffman, John; Hofmeister, Jeremy; Hohman, Timothy; Holder, Daniel; Holguin, Jess; Holmes, Robin; Hong, John; Hongliang, Zou; Hongyu, Guo; Hopkins, Paul; Hor, Soheil; Hornbeck, Russ; Horng, Andy; Horton, Wesley; Hosny, Khalid; Hosseini, Eghbal; Hosseini, Hadi; Hosseini, Zahra; Asl, Ehsan Hosseini; Hou, Beibei; Houghton, Richard; Houghton, Katherine; Householder, Erin; Howlett, James; Hsiao, John; Hsiao, Ing-Tsung; Hsu, Chih-Chin; Hu, Xixi; Hu, Lingjing; Hu, Nan; Hu, Kun; Hu, Tao; Hu, Li; Hu, Xiaolan; Hua, Fei; Huang, Marissa; Huang, Qi; Huang, Michelle; Huang, Chao; Huang, JunMing; Huang, Xingyuan; Huang, Yuhan; Huang, Sing-Hang; Huang, Shuai; Huang, Peiyu; Huang, Chun-Chao; Huang, Zhiyue; Huang, Meiyan; Huang, Zhiwen; Hubrich, Markus; Huestis, Michael; Huey, Edward; Hufton, Andrew; Huijbers, Willem; Huisman, Sjoerd; Hung, Joe; Hunsaker, Naomi; Hunt, Fostor; Huppertz, Hans-Jürgen; Huser, Vojtech; Hussain, Lal; Hutchison, R. Matthew; Hutton, Alexandre; Huyck, Els; Hwang, Jihye; Hyun, JungMoon; Iakovakis, Dimitris; Ibañez, Victoria; Ide, Kayoko; Igarashi, Takuma; Iglesias, Juan Eugenio; Muñoz, Laura Igual; Iidaka, Tetsuya; Ikeuchi, Takeshi; Ikhena, John; Ikuta, Toshikazu; Im, Hyung-Jun; Insausti, Ana; Insel, Philip; Invernizzi, Azzurra; Iosif, Ana-Maria; Ip, Nancy; Irizarry, Sierra; Irmak, Emrah; Irwin, David; Isaza, Mariano; Ishii, Makoto; Ishii, Kenji; Islam, Jyoti; Israel, Ariel; Isufi, Elvin; Ito, Kaori; Ito, Masato; Izquierdo, Walter; Alphin, J.; Akhila, J. A.; Jaberzadeh, Amir; Jackowiak, Edward; Jackson, Eric; Jackson, Chris; Jackson, Jonathan; Jacob, Samson; Jacobsen, Nina; Jacobsen, Jörn; Jacquemont, Thomas; Jacques, Nerline; Jaeger, Ralf; Jafari, Tahere; Jafari-Khouzani, Kourosh; Jagadish, Akshay Kumar; Jagtap, Priti; Jagust, William; Jahr, Joseph; Jain, Shubhankar; Jain, Shubham; Jaiswal, Ayush; Jaiswal, Akshay; Jait, Amine; Jakkoju, Chetan; Jakobsson, Andreas; James, Olga; James, Oliver; Jamlai, Maedeh; Jammeh, Emmanuel; Janardhana, Lajavanthi; Jang, Jinseong; Jang, Jae-Won; Jang, Jinhee; Jang, Hyesue; Janghel, Rekh Ram; Jawahar, Shasvat; Jean, Kharne; Jean-Baptiste, Schiratti; Jedynak, Bruno; Jefferson, Angela; Jennings, Danna; Jennings, Dominique; Jeon, Seun; Jeong, Yong; Jester, Charles; Jethwa, Ketan; Jha, Debesh; Ji, Gong-Jun; Ji, Chong; Ji, Jin; Jia, Bowen; Jiacheng, Lee; Jiajia, Guo; Jian, Weijian; Jiang, Shan; Jiang, Chunxiang; Jianhua, Gao; Jiao, Zhuqing; Jiao, Zeyu; Jiao, Du; Jimenez Alaniz, Juan Ramon; Gomez, Carolina Jimenez; Jiménez-Huete, Adolfo; Jimura, Koji; Jin, Yan; Jin, Zhu; Jogia, Jigar; Johansson, Per; John, Kimberley; Johnsen, Stian; Johnson, Leonard; Johnson, Sterling; Johnson, Kent; Johnston, Jane; Johnston, Stephen; Jomeiri, Alireza; Jonas, Katherine; Jones, Richard; Jones-Davis, Dorothy; Jönsson, Linus; Joseph, Jane; Joshi, Himanshu; Joshi, Shantanu; Joshi, Abhinay; Joyce, Katherine; Juengling, Freimut; Jung, Youngjin; Junker, Viv; Junwei, Ding; Jyothi, Singaraju; Jyotiyana, Monika; Sarthaj, K.; Kachouane, Mouloud; Kadian, Amit; Kaewaramsri, Yothin; Kaicheng, Li; Kaiser, Marcus; Kakinami, Lisa; Kalra, Sanjay; Kam, Hye Jin; Kamarudin, Nur Shazwani; Kaminker, Josh; Kandel, Benjamin; Kandiah, Nagaendran; Kaneko, Tomoki; Kang, Yun Seok; Kang, Ju Hee; Kang, Hakmook; Kang, Jian; Kansal, Anuraag; Kaouache, Mohammed; Kaplan, Adam; Kottaram, Akhil Karazhma; Karim, Faizan; Karimi-Mostowfi, Nicki; Karjoo, Mahboobe; Karlin, Daniel; Karp, Juliana; Karray, Chiheb; Kartsonis, Nick; Karu, Naama; Kasa, Jaya; Kasiri, Keyvan; Katako, Audrey; Kato, Ryo; Katsonis, Panagiotis; Katti, Hkkatti; Kaur, Prabhjot; Kauwe, John; Kawaguchi, Atsushi; Kazemi, Samaneh; Kazemi, Yosra; Rijan, K. C.; Kechin, Andrey; Kelkhoff, Douglas; Kelleher, Thomas; Kellner-Weldon, Frauke; Kennion, Oliver; Kerr, Daniel; Kesler, Shelli; Kesselman, Carl; Kessler, Daniel; Keuken, Max; Keyvanfard, Farzaneh; Khademi, April; Khajehnejad, Moein; Khan, Wasim; Khan, Tabrej; Khan, Hikmat; Khan, Anzalee; Khan, Samreen; Khanmohammadi, Sina; Khasanova, Tatiana; Khazaee, Ali; Khazan, Lenny; Kherif, Ferath; Khl, Aym; KHlif, Mohamed Salah; Khondoker, Mizanur; Khoo, Sok Kean; Khosrowabadi, Reza; Khurshid, Kiran; Kianfard, Reihaneh; Kida, Satoshi; Kiddle, Steven; Kikuchi, Masashi; Killiany, Ron; Kim, Jeongchul; Kim, Jong Hun; Kim, Hyunwoo; Kim, Jongin; Kim, Yeo Jin; Kim, Jung-Jae; Kim, Hang-Rai; Kim, Jaeyeol; Kim, Ki Hwan; Kim, Joseph; Kim, Younghoon; Kim, Mijung; Kim, Jeongsik; Kim, Bohyun; Kim, Taehyun; Kim, Heeyoung; Kim, Seonjik; Kim, Nakyoung; Kim, Byeongnam; Kim, ChanMi; Kim, Jeonghun; Kim, Seong Yoon; Kim, Sunhee; Kingery, Lisle; Kinnunen, Kirsi; Kinomes, Marie; Kirchner, Jan Hendrik; Caldwell, Jessica Kirkland; Kirwan, Brock; Kitamura, Chiemi; Kitty, Kitty; Kiviat, David; Kiyasova, Vera; Klein, Richard; Klein, Alison; Klein, Gregory; Klein, Jan; Kleinman, Aaron; Kling, Mitchel; Klinger, Joern; Klinger, Rebecca; Klink, Katharina; Kocaturk, Mustafa; Koch, Philipp Johannes; Kochova, Elena; Koenig, Loren; Koh, Natalie; Köhler, Jens Erik; Koikkalainen, Juha; Koini, Marisa; Kolachalama, Vijaya; Koncz, Rebecca; Kong, Xiang-Zhen; Kong, Vincent; Kong, Xiangzhen; Kong, Dehan; Kong, Linglong; Konukoglu, Ender; Kopeinigg, Daniel; Kopera, Krzysztof; Koppers, Simon; Korb, Matheus; Korfiatis, Panagiotis; Korolev, Igor; Korolev, Sergey; Korostyshevskiy, Valeriy; Koshiya, Heena; Kost, James; Kotari, Vikas; Koutra, Danai; Koychev, Ivan; Kruthika, K. R.; Krahnke, Tillmann; Krause, Matthew; Kraybill, Matt; Kriebel, Martin; Hari Krishna, M.; Krohn, Stephan; Kruggel, Frithjof; Kuceyeski, Amy; Kuhl, Donald; Kulshreshtha, Devang; Kumar, Santosh; Kumar, Sambath; Kumar, Kuldeep; Kumar, Anil; Kumar, Abhishek; Kumar, A.; Kumar, Saurabh; Kumar, Ashwani; Kumar, Ambar; Kumar, Dinesh; Kumar, Rishab; Kumarasinghe, Janaka; Kundu, Suprateek; Kung, Te-Han; Kuo, Li-Wei; Kuo, Phillip; Channappa, Usha Kuppe; Kuriakose, Elmy; Kurian, P.; Kwan, Kenneth; Kwasigroch, Arkadiusz; Kwon, Young Hye; Kyeong, Sunghyon; Fleur, Claire La; Wungo, Supriyadi La; Labbe, Tomas; Lacombe, Daniel; Lad, Meher; Lahoti, Geet; Lai, Ying Liang; Lai, Catherine; Lai, Dongbing; Laird, Dillon; Lakatos, Anita; Lam, Alice; Lama, Ramesh; Lambert, Christian; Landau, Susan; Landman, Bennett; Landre, Victor; Lane, Elizabeth; Lange, Catharina; Langenieux, Alexandre; Lareau, Caleb; Larson, Katelyn; Latif, Ghazanfar; Lauber, Ross; Lawliet, Z. H.; Lawrence, Emma; Lazar, Anca; Le, Ngan; Le, Thi Khuyen; Le, Matthieu; Guen, Yann Le; Scouiller, Stephanie Le; Leandrou, Stephanos; Leatherday, Christopher; Leavitt, Mackenzie; Ledbetter, Christina; Lee, Hyekyoung; Lee, Wook; Lee, Annie; Lee, Jaehong; Lee, Dongyoung; Lee, Joel; Lee, Song-Ting; Lee, Kuo-Jung; Lee, Subin; Lee, Jaeho; Lee, Catherine; Lee, Gyungtae; Lee, Suzee; Lee, Erik; Lee, Yunseong; Lee, Sang-Gil; Lee, Seonjoo; Lee, Peng Jung; Lee, Hyunna; Lee, Cheng-Hsien; Lee, Hengtong; Lee, Mi Ri; Lee, Ilgu; Lee, Qixiang; Lefterov, Iliya; Leger, Charlie; Lehallier, Benoit; Lei, B.; Lei, Shi; Lei, Hongxing; Lei, Haoyun; Leong, Tze Yun; Leong, Sharlene; Leoutsakos, Jeannie-Marie; Lepore, Natasha; Lerch, Ondrej; Leung, Yip Sang; Leung, Yuk Yee; Leung, Shuyu; Leung, Hoi-Chung; Leung, Ming-Ying; Levakov, Gidon; Levine, Abraham; Li, Chawn; Li, Miranda; Li, Huijie; Li, Junning; Li, Xiaofeng; Li, Yi; Li, Jinchao; Li, Tianhong; Li, Yongming; Li, Xiangrui; Li, Tieqiang; Li, Yan; Li, Fuhai; Li, Feijiang; Li, Shuyang; Li, Zhi; Li, Xing; Li, Rongjian; Li, Rui; Li, Y. U.; Li, Kang; Li, Zhenzhen; Li, Qingqin; Li, Wenjun; Li, Yang; Li, Jialu; Li, Guangyu; Li, Michelle; Li, Yibai; Li, Yupeng; Li, Tao; Li, Zhujun; Li, Yafen; Li, Muwei; Li, Xuan; Li, Yi-Ju; Li, Cen Sing; Li, X. W.; Li, Yingjie; Li, Lin; Li, Yihan Jessie; Li, Yaqing; Li, Xiantao; Li, Xingfeng; Li, Chenxi; Li, Chao; Li, Jicong; Li, Jiewei; Li, Tengfei; Li, Wei; Li, Xinzhong; Li, Nannan; Li, Chunfei; Li, Yeshu; Liang, Chen; Liang, Nanying; Liang, Jingjing; Liang, Shengxiang; Liang, Xiaoyun; Liang, Xia; Liang, Ying; Liberman, Sofia; Libon, David; Liébana, Sergio; Liedes, Hilkka; Lim, Wee Keong; Lim, Yen Ying; Lin, Yenching; Lin, Katherine; Lin, Ming; Lin, Ai-Ling; Lin, Ching-Heng; Lin, Bing; Lin, Lin; Lin, Jyh-Miin; Lin, W. M.; Lin, Chien-Tong; Lin, Liyan; Lin, Jing; Lindberg, Olof; Linesch, Paul; Linn, Kristin; Lippert, Christoph; Litovka, Nikita; Little, Graham; Liu, Man-Yun; Liu, Jin; Liu, Chin-Fu; Liu, Zhaowen; Liu, Eulanca; Liu, Weixiang; Liu, K. E.; Liu, Hao Chen; Liu, Jia; Liu, Richann; Liu, Dongbo; Liu, Victor; Liu, Wenjie; Liu, Tao; Liu, Xiaoli; Liu, Yong; Liu, Lin; Liu, Dan; Liu, Xiuwen; Liu, Mengmeng; Liu, Chia-Shang; Liu, Ying; Liu, Yan; Liu, Xueqing; Liu, Han; Liu, Chien-Liang; Liu, Sidong; Liu, Jundong; Liu, Yang; Liu, Tianming; Liu, Tingshan; Liu, Ning; Liu, Lan; Liuyu, Liuyu; Lizarraga, Gabriel; Llido, Jerome; Lobach, Iryna; Lockhart, Samuel; Loft, Henrik; Lohr, Kelly; Lon, Hoi Kei; Lone, Kashif Javed; Long, Ziyi; Long, Xiaojing; Longo, Frank; Alves, Isadora Lopes; Lopez, Guadalupe; Lorenzi, Marco; Lotan, Eyal; Louie, Gregory; Louis, Maxime; Loukas, Andreas; Love, Seth; Lowe, Deborah; Lu, Bin; Lu, Chia-Feng; Lu, Zixiang; Lu, Lijun; Lu, Pascal; Lu, Shen; Lu, Qing; Lu, Zheshen; Lu, Chuan; Lu, Patty; Lu, Hangquan; Lu, Bo; Luktuke, Yadnyesh; Luo, Wei; Luo, Suhuai; Luo, Sheng; Luo, Shaojun; Luo, Peggy; Luo, Shan; Luo, Weidong; Luo, Liao; Luo, Xiao; Lupton, Michelle; Lutz, Michael; Lv, Eric; Lyu, Juan; Angshul, M.; Radha, M. R.; Dinesh, M. S.; Ma, Xiangyu; Ma, Chao; Ma, Li; Ma, Yu; Ma, Qianli; MacArthur, Daniel; Macey, Paul; Mach, Eric; MacPhee, Imola; Madadi, Mahboubeh; Madan, Christopher; Madan, Bharat; Madero, Giovanny; Madhavan, Radhika; Madhyastha, Tara; Maeno, Nobuhisa; Magsood, Hamzah; Mah, Linda; Mahdavi, Shirin; Mahdavi, Asef; Mahmoud, Abeer; Mahmoud, Hentati; Mahmoud, Kariman; Mahmoudi, Ahmad; Dehkordi, Siamak Mahmoudian; Mahor, Monika; Mahseredjian, Taleen; Mai, Cha; Maia, Rui; Maiti, Taps; Maj, Carlo; Maji, Pradipta; Majidpour, Jafar; Makhlouf, Laouchedi; Makino, Satoshi; Makrievski, Stefan; Makse, Hernan; Malagi, Archana; Malakhova, Katerina; Malamon, John; Malashenkova, Irina; Malchano, Zach; Maleki-Balajoo, Somayeh; Malik, Sadia; Malik, Tamoor; Mallik, Abhirup; Malm, Tarja; Malpas, Charles; Malpica, Norberto; Malviya, Meenakshi; Mamandi, A.; Manandhar, Abinash; Mandal, Pravat; Mandali, Alekhya; Mane, Prajakta; Manning, Emily; Manoufali, Mohamed; Manser, Paul; Mantini, Dante; Mantri, Ninad; Manyakov, Nikolay; Manzak, Dİlek; Mao, Shuai; Maoyu, Tian; Maple Grødem, Jodi; Maravilla, Kenneth; Marco, Simonetti; Marcus, Daniel; Margetis, John; Margolin, Richard; Mariano, Laura; Marinescu, Razvan Valentin; Markett, Sebastian; Markiewicz, Pawel; Marnane, Michael; Maroof, Asif; Marple, Laura; Marques, Cristiane; Marrakchi, Linda; Marshall, Gad; Märtens, Kaspar; Mårtensson, Gustav; Marti, Cristian; Martin, Harold; Martinaud, Olivier; Martinez, Victor; Martinez, Oliver; Martinez, Jesus; Martinez, Carlos; Abadías, Neus Martinez; Torteya, Antonio Martinez; Martini, Jean-Baptiste; Martins, Samuel; Masciotra, Viviane; Masmoudi, Ahmed; Masny, Aliaksandr; Shah, Pir Masoom; Massaro, Tyler; Masumoto, Jun; Matan, Cristy; Mate, Karen; Mateus, Pedro; Mather, Mara; Mather, Karen; Mathew, Jesia; Mathias, Samuel; Mathiyalagan, Tamilalaghan; Matloff, Will; Matsubara, Keisuke; Matsubara, Takashi; Matsuda, Yukihisa; Matthews, Dawn; Mattis, Paul; May, Patrick; Mayburd, Anatoly; Mayo, Chantel; Mayordomo, Elvira; Mbuyi, Gaylord; McCallum, Colleen; McCann, Bryony; McCollough, Todd; McCormick, Shannon; McCurdy, Sean; McDonald, Carrie; McEligot, Archana; McEvoy, Linda; McGeown, William; McGinnis, Scott; McHugh, Thomas; McIntosh, Elissa; McIntosh, Randy; McKenzie, Andrew; McLaren, Donald; McMillan, Corey; McMillan, Alan; McPherson, Brent; McRae-McKee, Kevin; Zaini, Muhammad Hafiz Md; Meadowcroft, Mark; Mecca, Adam; Meda, Shashwath; Medikonda, Venkata Srinu; Meeker, Karin; Megherbi, Thinhinane; Mehmood, Anum; Mehrtash, Alireza; Meiberth, Dix; Meier, Dominik; Meijerman, Antoine; Mejia, Jose; Mekkayil, Lasitha; Meles, Sanne; Melie-Garcia, Lester; Melo, Hans; Melrose, Rebecca; Melzer, Corina; Mendes, Aline; Leon, Ricardo Antonio Mendoza; Gonzalez, Manuel Menendez; Meng, Dewen; Meng, Xianglai; Meng, Guilin; Mengel, David; Menon, Ramesh; Menon, Ravi; Mercado, Flavio; Messick, Viviana; Meyer, Pierre-Francois; Meyer, Carsten; Mezher, Adam; Mi, Liang; Miao, Hongyu; Michailovich, Oleg; Michels, Lars; Mickael, Guedj; Mikhail, Mark; Mikhno, Arthur; Milana, Diletta; Miller, Rachel; Miller, Brendan; Millikin, Colleen; Min, Byung Wook; Minadakis, George; Minghui, Hu; Chinh, Truong Minh; Minkova, Lora; Miranda, Michelle; Misevic, Dusan; Mishra, Amit; Mishra, Chetan; Mishra, Shiwangi; Mishra, Ashutosh; Mishra, Krishna; Misquitta, Karen; Mitchell, Brian; Mithawala, Keyur; Mitnitski, Arnold; Mitra, Sinjini; Mittal, Gaurav; Mittner, Matthias; Miyapuram, Krishna Prasad; Mlalazi, Rebaone; Mo, Daojun; Moghekar, Abhay; Moguilner, Sebastian; Moh, Heba; Mohabir, Mark; Mohajer, Bahram; Mohamed, Moataz; Mohammadi, Sadeq; Mohammadi-Nejad, Ali-Reza; Mohammady, Saed; Taqi, Arwa Mohammed; Mohan, Kishore Kumar; Mohy-Ud-Din, Hassan; Moitra, Dipanjan; Mojaradi, Mehdi; Mojtabavi, Alireza; Molina, Helena; Mollon, Jennifer; Molteni, Erika; Montajabi, Mohaddeseh; Montal, Victor; Montazami, Aram; Monté-Rubio, Gemma; Montembeault, Maxime; Montero-Odasso, Manuel; Montillo, Albert; Moon, Byung-Seung; Moon, Chan; Moon, Chooza; Moore, Archer; Morabito, Francesco C.; Moradi, Masoud; Moraes, Renato; Ballesteros, Orlando Morales; Morales-Henriquez, Daniela; Moratal, David; Moreno, Herman; Morihara, Ryuta; Mormino, Elizabeth; Morris, Jeffrey; Mortamet, Bénédicte; Morton, John; Moscato, Pablo; Rial, Alexis Moscoso; Mossa, Abdela Ahmed; Mottaghi, Setare; Mouelhi, Aymen; Moussavi, Arezou; Moustafa, Ahmed; Mowrey, Wenzhu; Mtetwa, Lungile; Muehlboeck, Sebastian; Mueller, Susanne; Mueller-Sarnowski, Felix; Mufidah, Ratna; Mukherjee, Rik; Mukherjee, Shubhabrata; Müller, Christian; Müller, Hans-Peter; Mullins, Paul; Mullins, Roger; Muncy, Nathan; Munir, Akhtar; Munirathinam, Ramesh; Munoz, David; Munro, Catherine; Muranevici, Gabriela; Rendon, Santiago Murillo; Murilo, Robson; Murphy, Sonya; Muscio, Cristina; Musso, Gabriel; Mustafa, Yasser; Myall, Daniel; Gayathri, N.; Nabavi, Shahab; Nabeel, Eman; Nagele, Robert; Naghshbandi, Hane; Naik, Shruti; Najmitabrizi, Neda; Nakawah, Mohammad Obadah; Nalls, Mike; Namboori, Krishnan; Nancy, Annie; Napolitano, Giulio; Narayan, Manjari; Narkhede, Atul; Naseri, Mahsa; Nasrallah, Ilya; Nasrallah, Fatima; Nassif, Rana; Nath, Sruthi R.; Nathoo, Farouk; Nation, Daniel; Naughton, Brian; Nault, Larry; Nautiyal, Deeksha; Nayak, Deepak Ranjan; Naz, Mufassra; Nazemian, Shayan; Nazeri, Arash; Neckoska, Emilija; Neelamegam, Malinee; Nehary, Ebrahim; Nelson, Peter; Nelson, Linda; Nematzadeh, Hosein; Nerur, Shubha; Nesteruk, Thomas; Neu, Scott; Ng, Yen-Bee; Nguyen, Tin; Nguyen, Thanh; Nguyen, Harrison; Nguyen, Nghi; Trung, Hieu Nguyen; Ni, Lucy; Nian, Yongjian; Nichols, Thomas; Nicodemus, Kristin; Nie, Yunlong; Nielsen, Casper; Nikolov, Robert; Nila, Jessica; Nishioka, Christopher; Njeh, Ines; Njie, Emalick; Nobakht, Samaneh; Noble, Andrew; Noda, Art; Noroozi, Ali; Norton, Derek; Nosarti, Chiara; Nosheny, Rachel; Notsu, Akifumi; Novak, Gerald; Nozadi, Seyed Hossein; Nu, Fen; Nudelman, Kelly; Nunes, Adonay; Nunes, Ana; Núñez, Christian; Nuno, Michelle; Nuriel, Tal; Nygaard, Haakon; Nyquist, Paul; O'Bott, Jacob; O'Charoen, Sirimon; O'Neill, William; O'Rawe, Jonathan; Obrzut, Grzegorz; Och, Ganzorig; Odaibo, David; Odry, Benjamin; Oehmichen, Axel; Ofori, Edward; Ogunsanmi, Abdulfatai; Oguz, Kaya; Oh, Jungsu; Oh, Minyoung; Oh, Hwamee; Ohigashi, Hironori; Oishi, Kenichi; Oishi, Naoya; Okhravi, Hamid; Okonkwo, Ozioma; Okyay, Savaş; Oliveira, Cyrill; Oliveira, João; Oliveira, Francisco; Oliver, Ruth; Olmos, Salvador; Olszowy, Wiktor; Oltra-Cucarella, Javier; Önen, Zehra; Ong, Rowena; Onoda, Keiichi; Onyike, Chiadi; Operto, Grégory; Oppedal, Ketil; Orejuela, Juan; Orhon, Atila; Orozco, Max; Ortuño, Juan; Osadebey, Michael; Osborn, Joseph; Osoba, Osonde; Ostadrahimi, Hamid; Ostovari, Parisa; Otis, Sarah; Overgaard, Shauna; Owen, Catrin Elin; Oxtoby, Neil; Öziç, Muhammet Üsame; Ozkaya, Gorkem; Okur, Ozlem Ozmen; Ozsolak, Fatih; Ozyildirim, Melis; Pa, Judy; Pacheco, Joe; Pack, Gary; Padilla, Daniel; Cerezo, Berizohar Padilla; Padovese, Bruno; Pae, Chongwon; Pagano, Gennaro; Pahuja, Gunjan; Pai, Shraddha; Pajavand, Shahryar; Pajula, Juha; Pak, Kyoungjune; Pakzad, Ashkan; Palaniappan, Mathiyalagan; Palanisamy, Sindhu; Palmqvist, Sebastian; Palsson, Frosti; Pan, Dan; Pan, Tiffany; Pan, Yuqing; Pan, Wei; Pan, Sun; Pan, Hongliang; Pan, Xiaoxi; Pandey, Lokesh; Pang, Qiaoyu; Pangilinan, Erin; Pannetier, Nicolas; Panpan, Xu; Panyavaraporn, Jantana; Pardini, Matteo; Paredes, José; Parikh, Jignesh; Park, Seongbeom; Park, Young Ho; Park, Min Tae; Park, Hyunjin; Park, Sejin; Park, JongSeong; Park, DooHyun; Park, Ji Eun; Park, Yuhyun; Park, Jiyong; Parker, Jason; Parker, Richard; Parodi, Alice; Bautista, Yohn Jairo Parra; Parrish, Marcus; Parthiban, Preethy; Pascariello, Guido; Pascual, Belen; Paskov, Hristo; Pasquini, Lorenzo; Tantaleán, Julio Sergio Eduardo Pastor; Pastur, Lucas; Patel, Raihaan; Patel, Sejal; Paterson, Ross; Paton, Bryan; Patriarche, Julia; Patriat, Rémi; Pattichis, Constantinos; Paul, Debashis; Pawar, Kuldeep; Pawlak, Mikolaj; Paz, Rotem; Pedroto, Maria; Pelekanos, Matthew; Péléraux, Annick; Peng, Dan; Peng, Jing; Pengfei, Tian; Perani, Daniela; Peraza, Luis; Pereira, Fabricio; Pereira, Francisco; Perkins, Diana; Perneczky, Robert; Persad, Umesh; Peter, Jessica; Peters, Mette; Peters, Ruth; Pether, Mark; Petrella, Jeffrey; Petrenko, Roman; Petrone, Paula; Petrov, Dmitry; Pezzatini, Daniele; Pfenning, Andreas; Pham, Chi-Tuan; Philipson, Pete; Phillips, Jeffrey; Phillips, Nicole; Phophalia, Ashish; Phuah, Chia-Ling; Pichai, Shanthi; Pichardo, Cesar; Binette, Alexa Pichet; Pietras, Olga; Pietrzyk, Mariusz; Pike, Kerryn; Pillai, Jagan; Piludu, Francesca; Pineda, Joanna; Ping, He; Pirraglia, Elizabeth; Pither, Richard; Piyush, Ranjan; Pizzi, Nick; Gonzalez, Luis Fernando Planella; Plassard, Andrew; Platero, Carlos; Plocharski, Maciej; Podhorski, Adam; Poggiali, Davide; Poghosyan, Mher; Pohl, Kilian; Poirier, Judes; Polakow, Jean Jacques; Politis, Marios; Poljak, Anne; Poloni, Katia Maria; Poole, Victoria; Poppenk, Jordan; Porsteinsson, Anton; Portelius, Erik; Posta, Filippo; Posthuma, Danielle; Potashman, Michele; Poulin, Stephane; Pourmennati, Bahar; Prahlad, Tejas; Pranav, Lee; Prasanth, Isaac; Prashar, Ajay; Prescott, Jeff; Prevedello, Luciano; Previtali, Fabio; Pricer, James; Prichard, James; Prince, Jerry; Prins, Samantha; Pritchard, Christopher; Priya, Priya; Priya, Anandh; Priyanka, Ahana; Properzi, Michael; Prosser, Angus; Proust-Lima, Cécile; Pruessner, Jens; Pu, Jian; Punjabi, Arjun; Punugu, Venkatapavani Pallavi; Puri, Dilip; Renjini, Anurenjan Purushothaman; Pyeon, DoYeong; Qader, Abu; Qi, Zeyao; Qi, Baihong; Qian, Xiaoning; Qian, Long; Qiao, Ju; Qiao, Jocelin; Qiaoli, Zhang; Qin, Hongsen; Qin, Wang; Qin, Tian; Qin, Yuanyuan; Qin, Qinxiaotie; Qin, Qiao; Qing, Zhao; Qiongling, Li; Qiu, Yu; Qiu, Wendy; Qiu, Deqiang; Qiu, Yingwei; Quadrelli, Scott; Qualls, Jake; Quan, Li; Quarg, Peter; Qureshi, Adnan; Anand, R.; Chitra, R.; Balaji, R.; Madhusudhan, R. N.; Raamana, Pradeep Reddy; Rabbia, Michael; Rabin, Laura; Radke, David; Pc, Muhammed Raees; Rafeiean, Mahsa; Raha, Oindrila; Rahimi, Amir; Arashloo, Shervin Rahimzadeh; Rai, Vipin; Rajamanickam, Karunanithi; Rajan, Surya; Rajapakse, Jagath; Rajaram, Sampath; Rajendran, Rajeswari; Rakovski, Cyril; Ramalhosa, Ivo; Raman, Fabio; Ramasamy, Ellankavi; Ramasangu, Hariharan; Ramirez, Alfredo; Ramos Pérez, Ana Victoria; Rana, Rahul; Rane, Swati; Rao, Anil; Rao, Vikram; Rashidi, Arash; Rasoanaivo, Oly; Rassem, Taha; Rastgoo, Hossein; Rath, Daniel; Ratnarajah, Nagulan; Ravikirthi, Prabhasa; Ravipati, Kaushik; RaviPrakash, Harish; Rawdha, Bousseta; Ray, Meredith; Ray, Debashree; Ray, Nilanjan; Ray, Dipankar; Ray, Soumi; Rebbah, Sana; Redding, Morgan; Regnerus, Bouke; Rehn, Patrick; Rehouma, Rokaya; Reid, Robert; Reimer, Alyssa; Reiss, Philip; Reitz, Christiane; Rekabi, Maryam; Rekik, Islem; Ren, Xuhua; Ren, Fujia; Ren, Xiaowei; Ren, Weijie; Renehan, William; Rennert, Lior; Rey, Samuel; Reyes, Pablo; Reza, Rifat; Rezaee, Khosro; Rhinn, Herve; Lorenzo, Pablo Ribalta; Ribeiro, Adèle Helena; Richards, John; Richards, Burt; Richards, Todd; Richardson, Hamish; Richiardi, Jonas; Richter, Nils; Ridge, Perry; Ridgway, Gerard; Ridha, Basil; Ried, Janina; Riedel, Brandalyn; Riphagen, Joost; Ritter, Kerstin; Rivaz, Hassan; Rivers-Auty, Jack; Allah, Mina Rizk; Rizzi, Massimo; Roalf, David; Robb, Catherine; Roberson, Erik; Robieson, Weining; Rocca-Serra, Philippe; Rodrigues, Marcos Antonio; Rodriguez, Alain; Aguiar, Güise Lorenzo Rodríguez; Rodriguez-Sanchez, Antonio; Rodriguez-Vieitez, Elena; Roes, Meighen; Rogalski, Emily; Rogers, James; Rogers, Baxter; Rohani, Hosna; Rollins, Carin; Rollo, Jenny; Romanillos, Adrian; Romero, Marcelo; Romero, Klaus; Rominger, Axel; Rondina, Jane; Ronquillo, Jeremiah; Roohparvar, Sanaz; Rosand, Jonathan; Rose, Gregory; Roshchupkin, Gennady; Rosoce, Jeremy; Ross, David; Ross, Joel; Ross, Owen; Rossi, Stephanie; Roussarie, Jean-Pierre; Roy, Arkaprava; Roy, Snehashis; Ruble, Cara; Rubright, Jonathan; Rudovic, Ognjen; Ruggiero, Denise; Rui, Qiao; Ruiz, Pablo; Rullmann, Michael; Rusmevichientong, Pimbucha; Russell, Rolf; Rutten, Julie; Saadatmand-Tarzjan, Mahdi; Saba, Valiallah; Sabuncu, Mert; Sacuiu, Simona; Sampathkumar, Srihari Sadhu; Sadikhov, Shamil; Saeedi, Sarah; Saf, Naz; Safapur, Alireza; Safi, Asad; Saint-Aubert, Laure; Saito, Noboru; Saito, Naomi; Sakata, Muneyuki; Frigerio, Carlo Sala; Sala-Llonch, Roser; Salah, Zainab; Salamanca, Luis; Salat, David; Salehzade, Mahdi; Salter, Hugh; Samatova, Nagiza; Sampat, Mehul; Gonzalez, Jorge Samper; Samtani, Mahesh; Samuel, Pearl; Bohorquez, Sandra Sanabria; Sanbao, Cheng; Sanchez, Iñigo; Sánchez, Irina; Sandella, Nick; Sanderlin, Ashley Hannah; Sanders, Elizabeth; Sankar, Tejas; Sanroma, Gerard; Sanson, Horacio; Santamaria, Mar; de Lourdes, Daniella; de Andrade, Luna Santana; Santhanam, Prasanna; Ribeiro, Andre Santos; Sardi, Pablo; Sardina, Davide; Saremi, Arvin; Sarica, Alessia; Sarnowski, Chloé; Sarraf, Saman; Saslow, Adam; Sato, Takayuki; Sato, Joao; Sattler, Sophia; Savic, Milos; Saxon, Jillian; Saya, Boson; Saykin, Andrew; Sbeiti, Elia; Scarapicchia, Vanessa; Scelsi, Marzia Antonella; Schaerer, Joel; Scharre, Douglas; Scherr, Martin; Schevenels, Klara; Schibler, Tony; Schiller, Florian; Schirmer, Markus; Schmansky, Nick; Schmidt, Marco; Schmidt, Paul; Schmitz, Taylor; Schmuker, Michael; Schneider, Anja; Schneider, Reinhard; Schoemaker, Dorothee; Schöll, Michael; Schouten, Tijn; Schramm, Hauke; Schreiber, Frank; Schultz, Timothy; Schultz, Aaron; Schürmann, Heike; Schwab, Patrick; Schwartz, Pamela; Schwarz, Adam; Schwarz, Christopher; Schwarzbauer, Christian; Scott, Julia; Scott, F. Jeffrey; Scott, David; Scussel, Artur; Seale, William; Seamons, John; Seemiller, Joseph; Sekine, Tetsuro; Selnes, Per; Sembritzki, Klaus; Senanayake, Vijitha; Seneca, Nicholas; Senjem, Matthew; Filho, Antonio Carlos Senra; Sensi, Stefano; Seo, Eun Hyun; Seo, Kangwon; Seong, Sibaek; Sepeta, Leigh; Seraji-Bozorgzad, Navid; Serra-Cayuela, Arnau; Seshadri, Sudha; Sgouros, Nicholas; Sha, Miao; Shackman, Alexander; Shafee, Rebecca; Shah, Rupali; Shah, Hitul; Shahid, Mohammad; Shahparian, Nastaran; Shakeri, Mahsa; Shams, Sara; Shams, Ali; Baboli, Aref Shams; Shamul, Naomi; Shan, Guogen; Shang, Yuan; Shao, Rui; Shao, Hanyu; Shao, Xiaozhe; Shaoxun, Yuan; Noghabi, Hossein Sharifi; Sharlene, Newman; Sharma, Avinash; Sharma, Ankita; Sharma, Aman; Shaw, Leslie; Shaw, Saurabh; Shcherbinin, Sergey; Sheline, Yvette; Shen, Li; Shen, Yanhe; Shen, Qian; Sherriff, Ian; Shi, Xin; Shi, Lei; Shi, Yonggang; Shi, Yue; Shi, Yupan; Shi, Jie; Shi, Feng; Shiban, Nisreen; Shields, Trevor; Shiiba, Takuro; Shiino, Akihiko; 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Taswell, Koby; Taswell, Carl; Tatsuoka, Curtis; Taylan, Pakize; Taylor, Jonathan; Taylor, Brad; Tayubi, Iftikhar; Tchistiakova, Ekaterina; tee, Yee Kai; Teipel, Stefan; Temizer, Leyla; Kate, Mara Ten; Tenbergen, Carlijn; Tenenbaum, Jessica; Teng, Zi; Teng, Yuan-Ching; Teng, Edmond; Termenon, Maite; Terry, Eloise; Thaker, Ashesh; Theobald, Chuck; Thiel, Taylor; Thiele, Ines; Thiele, Frank; Thierry, Jean Pierre; Thirunavu, Vineeth; Thomas, Chris; Thomas, Kelsey; Thomas, Anoop Jacob; Thomas, Benjamin; Thomas, Ronald; Thomas, Adam; Thomopoulos, Sophia; Thompson, Gerard; Thompson, Jeff; Thompson, Will; Thompson, Paul; Thung, Kimhan; Tian, Sijia; Tierney, Mary; Tilquin, Florian; Tingay, Karen; Tirrell, Lee; Tirumalai, Sindhuja; Tobis, Jonathan; Todkari, Suhasini; Tohka, Jussi; Tokuda, Takahiko; Toledo, Juan B.; Toledo, Jon; Tolonen, Antti; Tombari, Federico; Tomiyama, Tetsuro; Tomola, Lauren; Tong, Yunjie; Tong, Liz; Tong, Li; Tong, Xiaoran; Torgerson, Carinna; Toro, Roberto; Torok, Levente; Toschi, Nicola; Tosto, Giuseppe; Tosun, Duygu; Tourandaz, Morteza; Toussaint, Paule; Towhidi, Sasan Maximilian; Towler, Stephen; Toyama, Teruhide; Tractenberg, Rochelle E.; Tran, Thao; Tran, Daniel; Trapani, Benjamin; Tremolizzo, Lucio; Tripathi, Shashi; Trittschuh, Emily; Trivedi, Ashish; Trojacanec, Katarina; Truong, Dennis; Tsanas, Athanasios; Tse, Kai-Hei; Tsoy, Elena; Tu, Yanshuai; Tubeleviciute-Aydin, Agne; Tubi, Meral; Tucholka, Alan; Tufail, Ahsan; Tumati, Shankar; Tuo, Shouheng; Tuovinen, Timo; Tustison, Nicholas; Tutunji, Rayyan; Tward, Daniel; Tyagi, Gaurav; Tzioras, Nikolaos; Raghavendra, U.; Uberti, Daniela; Uchiyama, Yoshikazu; Ueki, Masao; Ulug, Aziz; Umek, Robert; University, Northwestern; de Almeida, Sofia Urioste Y. Nunes; Urrutia, Leandro; Usama, Ahmed; Ustun, Ali Alp; Uus, Alena; Uyar, Muharrem Umit; Visalatchi, V.; Rajinikanth, V.; Vafaei, Amin; Vairre, Darlene; Vaishnavi, Sanjeev; Vaithinathan, Krishnakumar; Vakorin, Vasily; Hernández, Maria Valdés; van Bokhoven, Pieter; Deerlin, Vivianna Van; van der Brug, Marcel; Dijk, Koene Van; van Duijn, Cornelia; van Erp, Theo; van Hooren, Roy; Leemput, Koen Van; van Loenhoud, Anita; Schependom, Jeroen Van; van Velden, Floris; van Westen, Danielle; Vandekar, Simon; Vandijck, Manu; Vanhoutte, Matthieu; Vannini, Patrizia; Vansteenkiste, Elias; Varatharajah, Yogatheesan; Vardarajan, Badri; Varey, Stephen; Vargas, Hernan; Varkey, Julia; Varma, Susheel; Varma, Vijay; Varma, Sudhr; Vasanthakumar, Aparna; Vashi, Tejal; Vasilchuk, Kseniia; Vassileva, Albena; Vatsalan, Dinusha; Vb, Nastaran; Veeramacheneni, Teja; Veeranah, Darvesh; Vejdani, Kaveh; Veldsman, Michele; Velgos, Stefanie; Veloso, Adriano; Vemuri, Prashanthi; Venero, Cesar; Venkataraman, Ashwin; Venkatasubramanian, Palamadai; Venkatraghavan, Vikram; Venugopal, Vinisha; Venugopalan, Janani; Verbeeck, Rudi; Verbel, David; Verbist, Bie; Verdoliva, Luisa; Verma, Ajay Kumar; Verma, Tarun; Verma, Ishan; Veronese, Mattia; Grabovetsky, Alejandro Vicente; Victor, Jonathan; Vieira, Domingos; Vijayaraj, Vinesh Raja; Vikas, Vinutha; Vilaplana, Veronica; Vilaplana, Eduard; Villar, José Ramón; Vincent, Fabrice; Vinkler, Mojmir; Viswanath, Satish; Viswanathan, Srikrishnan; Vitek, Michael; Viti, Mario; Vladutu, Liviu; Vlock, Daniel; Voineskos, Aristotle; Vora, Anvi; Vos, Stephanie; Voyle, Nicola; Vrenken, Hugo; Vu, Tien Duong; Vucetic, Zivjena; Vuksanovic, Vesna; Wachinger, Christian; Wada, Masataka; Wade, Sara; Wagstyl, Konrad; Wahba, Grace; Waldorf, Johannes; Walker, Douglas; Moore, Kim Poki Walker; Walsh, Dominic; Wan, Lin; Wang, Di; Wang, Jane-Ling; Wang, Yongmao; Wang, Huaming; Wang, Miao; Wang, Zi-Rui; Wang, Zheyu; Wang, Z. E.; Wang, Lucy; Wang, Bin; Wang, Lei; Wang, Jason; Wang, Cathy; Wang, Jing; Wang, Xiuyuan; Wang, Dai; Wang, Lingyu; Wang, Jianjia; Wang, Yuan; Wang, Yujiang; Wang, Ming-Liang; Wang, De; Wang, Ling; Wang, Liangliang; Wang, Jianxin; Wang, Zhanyu; Wang, William Shi-Yuan; Wang, HuiFu; Wang, Weixin; Wang, Zhenxun; Wang, Wei; Wang, Junwen; Wang, Yipei; Wang, Shanshan; Wang, Yinying; Wang, Chengjia; Wang, Yuanjia; Wang, Kerry; Wang, Li-San; Wang, Kangcheng; Wang, Rui; Wang, Kai; Wang, Qian; Wang, Xinying; Wang, Xinglong; Wang, Jeff; Wang, Tianyi; Wang, Honglang; Wang, Xuekuan; Wang, Yongxiang; Wang, Hong; Wang, Silun; Waring, Stephen; Warren, David; Wasule, Vijay; Watanabe, Yoshiyuki; Wearn, Alfie; Wee, Chong-Yaw; Wegmayr, Viktor; Wehenkel, Marie; Wei, Rizhen; Wei, Zheng; Wei, Penghu; Wei, Yongbin; Wei, Guohui; Wei, Changshuai; Weichart, Emily; Weiler, Marina; Weise, Christopher; Weisong, Zhong; Weisshuhn, Philip; Weizheng, Yan; Wen, Canhong; Wen, Junhao; Wen, Wei; Wen, Zhenfu; Wen, Hao; Wenzel, Fabian; Werhane, Madeleine; Westaway, Shawn; Westlye, Lars T.; Westman, Eric; Whardana, Adithya; Whitcher, Brandon; Whittington, Alexander; Wicks, Stephen; Wiens, Jenna; Wildsmith, Kristin; Wilhelmsen, Kirk; Wilkinson, Andrea; Willette, Auriel; Williams, Kristin; Williams, Robert; Williams, Rebecca; Wilman, Alan; Wilmot, Beth; Wilson, Lorraine; Win, Juliet; Windpass, F. C.; Wink, Alle Meije; Winter, Nils; Winzeck, Stefan; Wirth, Miranka; Wishart, Heather; Wisniewski, Gary; Wiste, Heather; Wolpe, Noham; Wolz, Robin; Wong, Stephen; Wong, Swee Seong; Wong, Tak-Lam; Woo, Jongwook; Woo, Taekang; Woo, Young; Wood, Levi; Worth, Andrew; Wrenn, Jesse; Wright, Paul; Wu, Guorong; Wu, Lynn; Wu, Shawn; Wu, Menglin; Wu, Ruige; Wu, Shaoju; Wu, Chong; Wu, Juhao; Wu, Liyun; Wu, Yu-Te; Wu, Yuankai; Wu, Helen; Xia, Weiming; Xiang, Xu; Xiangmao, Kong; Xiao, Yiming; Xiao, Jie; Xiao, Y. U.; Xiaoxi, Ji; Xiaoya, Zhu; Xiaoying, Qi; Xie, Yuchen; Xie, Zhiyong; Xie, Lei; Xie, Xiancheng; Xin, Huang; Xingyi, Huang; Xiong, Yuanpeng; Xiong, Momiao; Xu, Yongchao; Xu, XiaoYing; Xu, Qiqi; Xu, Lijun; Xu, Hewen; Xu, Yunlong; Xu, Zhilei; Xu, Ziliang; Xu, Jiayuan; Xu, Yadong; Xu, Lu; Xu, Shuoyu; Xue, Fei; Xuesong, Yang; Xz, Zarric; Yadav, Rishi; Yaish, Aviv; Yakushev, Igor; Yamada, Shigeki; Yamamoto, Utako; Yamashita, Alexandre; Yamashita, Fumio; Yan, Li; Yan, Yu; Yan, Jianhua; Yan, Shiju; Yan, Chao-Gan; Yan, Qingyu; Yan, Jingwen; Yan, Chen; Yan, Meng; Yang, Meng; Yang, Bin; Yang, Jiarui; Yang, Zhi; Yang, Xianfeng; Yang, Sli; Yang, Liang; Yang, Robert; Yang, Aleex; Yang, Hyungjeong; Yang, ChengHao; Yang, Haiwei; Yang, Jhih-Ying; Yang, Xu; Yangyang, Xia; Yao, Xufeng; Yaping, Wang; Yaqiong, Bi; Yared, Surafael; Yashin, Anatoliy; Yassine, Hussein; Yau, Tat; Yavorsky, Christian; Ye, Chang; Ye, Byoung Seok; Ye, Joy; Ye, Yongkai; Ye, Yuting; Ye, Wu; Yelampalli, Praveen Kumar Reddy; Thomas Yeo, B. T.; Yi, Zhao; Yi, Wang; Yi, Yuan; Yijing, Ruan; Yilmaz, Zeynep; Yin, Baocai; Yin, Tang-Kai; Ying, Li; Yingjiang, Wu; Yiyun, Yu; Yoichiro, Sato; Yokoyama, Jennifer; Yong, Zhang; Yonghong, Shi; Yonghu, Guo; Yongqi, Huang; Yoo, Inwan; Yoon, So Hoon; Yoon, Jee Seok; Yoon, Seung-Yong; Yoshida, Hisako; Yoshio, Kiyofumi; You, Jia; You, You; You, Xiaozhen; Young, Alexandra; Yu, Peng; Yu, Jaemin; Yu, Lin; Yu, Sui; Yu, Philip S.; Yu, Guan; Yu, Fengli; Yu, Jiaxin; Yu, Shaode; Yu, Suizhi; Yu, Donghyeon; Yuan, Yue; Yuan, Shaofeng; Yuan, Shuai; Yuanyuan, Chen; Yue, Ye; Yue, Cynthia; Yunaiyama, Daisuke; YushaoChen, YushaoChen; Yushkevich, Paul; Yx, W.; Zafeiris, Dimitrios; Zagorchev, Lyubomir; Zalocusky, Kelly; Zamorano, Francisco; Zandifar, Azar; Zanella, Laura; Zang, Yufeng; Zanke, Brent; Zaranek, Alexander Wait; Zawaideh, Mazen; Zawawi, Nour; Zee, Jarcy; Zeighami, Yashar; Zeitzer, Jamie; Zemla, Jeffrey; Zeng, Qi; Zeng, Fan; Zeng, Donglin; Zeng, Wei; Zeng, Yingying; Ženko, Bernard; Zereshki, Ehsan; Zeskind, Benjamin; Zhan, Justin; Zhang, Chenghui; Zhang, Yixuan; Zhang, Xiong; Zhang, Li; Zhang, Zhi; Zhang, Jianlun; Zhang, Jing; Zhang, Jianwei; Zhang, Yufei; Zhang, Sai; Zhang, Shan; Zhang, Xiaoling; Zhang, Changle; Zhang, Qingtian; Zhang, Fan; Zhang, Xiangliang; Zhang, Linda; Zhang, Yingteng; Zhang, Jianhua; Zhang, Xiaoqun; Zhang, Ziwei; Zhang, Ping; Zhang, Tuo; Zhang, Bin; Zhang, Hong; Zhang, Yuping; Zhang, Zhan; Zhang, Yu; Zhang, Jie; Zhang, Lijun; Zhang, ChengZhi; Zhang, Jian; Zhang, Peng; Zhang, Zhengjun; Zhang, Wen; Zhang, Guishan; Zhang, Xixue; Zhang, Tianhao; Zhangyi, Zhangyi; Zhao, Wenting; Zhao, Xuewu; Zhao, Peng; Zhao, Yifei; Zhao, Xing-Ming; Zhao, Di; Zhao, Qian; Zhao, Yang; Zhao, Lu; Zheng, Lijuan; Zheng, Kaiping; Zheng, Weihao; Zheng, Du; Zheng, Muhua; Zheng, Qiang; Zheng, Bichen; Zheng, Lihong; Zhong, Wenxuan; Zhong, Yujia; Zhou, Tian; Zhou, Jiayin; Zhou, Zhen; Zhou, Yongxia; Zhou, Lixin; Zhou, Bowei; Zhou, Juan; Zhou, Qixin; Zhou, Levi; Zhou, Fengfeng; Zhou, Jiayu; Zhou, Luping; Zhou, Yun; Zhou, Yingjie; Zhou, Ying; Zhou, Frankie; Zhu, Zonghai; Zhu, Xiaoya; Zhu, Xiaolu; Zhu, Shanfeng; Zhu, David; Zhu, Hongxiao; Zhu, Lida; Zhu, Xiaofeng; Zhuxin, Jin; Zigon, Robert; Zille, Pascal; Zimmer, Eduardo; Zimmer, Jennifer; Zimmerman, Earl; Zimmerman, Karl; Zimmermann, Joelle; Zipperer, Erin; Zito, Giancarlo; Zou, Yang; Zuo, Maria; Zywiec, Andrew

    2017-01-01

    Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions,

  3. Introduction to the feature section on functional imaging of the pelvic floor.

    Maccioni, Francesca

    2013-10-01

    This is the introduction to the feature section of functional imaging of the pelvic floor, which includes 6 articles, two focused on clinical issues, while four on radiological aspects, mostly on dynamic pelvic floor MRI.

  4. Imaging Features of Pediatric Pentastomiasis Infection: a Case Report

    Lai, Can; Wang, Xi Qun; Lin, Long; Gao, De Chun; Zhang, Hong Xi; Zhang, Yi Ying; Zhou, Yin Bao [Zhejiang University School of Medicine, Zhejiang (China)

    2010-08-15

    We report here a case of pentastomiasis infection in a 3-year-old girl who had high fever, abdominal pain, abdominal tension and anemia. Ultrasound scanning of the abdomen revealed disseminated hyperechoic nodules in the liver and a small amount of ascites. Abdominal MRI showed marked hepatomegaly with disseminated miliary nodules of high signal intensity throughout the hepatic parenchyma on T2-weighted images; retroperitoneal lymphadenopathy and disseminated miliary nodules on the peritoneum were also noted. Chest CT showed scattered small hyperdense nodules on both sides of the lungs. The laparoscopy demonstrated diffuse white nodules on the liver surface and the peritoneum. After the small intestinal wall and peritoneal biopsy, histological examination revealed parenchymal tubercles containing several larvae of pentastomids and a large amount of inflammatory cell infiltration around them. The pathological diagnosis was parasitic granuloma from pentastomiasis infection

  5. Imaging Features of Pediatric Pentastomiasis Infection: a Case Report

    Lai, Can; Wang, Xi Qun; Lin, Long; Gao, De Chun; Zhang, Hong Xi; Zhang, Yi Ying; Zhou, Yin Bao

    2010-01-01

    We report here a case of pentastomiasis infection in a 3-year-old girl who had high fever, abdominal pain, abdominal tension and anemia. Ultrasound scanning of the abdomen revealed disseminated hyperechoic nodules in the liver and a small amount of ascites. Abdominal MRI showed marked hepatomegaly with disseminated miliary nodules of high signal intensity throughout the hepatic parenchyma on T2-weighted images; retroperitoneal lymphadenopathy and disseminated miliary nodules on the peritoneum were also noted. Chest CT showed scattered small hyperdense nodules on both sides of the lungs. The laparoscopy demonstrated diffuse white nodules on the liver surface and the peritoneum. After the small intestinal wall and peritoneal biopsy, histological examination revealed parenchymal tubercles containing several larvae of pentastomids and a large amount of inflammatory cell infiltration around them. The pathological diagnosis was parasitic granuloma from pentastomiasis infection

  6. Imaging and Clinical Features of Thyroid Cancer in Children and Adolescents

    Lee, Kang Young; Hong, HyunSook; Lee, Eun Hye; Yi, Beom Ha; Lee, Hae Kyung; Lee, Yong Hwa; Koh, Eun Suk

    2011-01-01

    To evaluate clinical and imaging features of pediatric thyroid cancer, including BRAF'V 600E mutation status in papillary thyroid cancer (PTC). We evaluated clinical findings including BRAF''6 00E status, ultrasound (US), and CT features of 13 pediatric patients with thyroid cancer. US findings were retrospectively analyzed for location, presence of a nodule, echotexture, echogenicity, calcifications, margin, shape, intranodular vascularity and abnormal lymph nodes. CT characteristics of the lesions, including attenuation, calcification, and measured degree of enhancement, were assessed. The patients included three boys and ten girls with a mean age of 15.5 years (range 6-18 years). No patient was exposed to radiation. Palpable neck mass was the most common presentation. Eleven of 13 patients (84.6%) were diagnosed with PTC, and two (15.4%) had follicular thyroid cancer (FTC). Nine of 13 (69.2%) had high T-staging. BRAF V600E mutations were detected in 30.0% of PTC patients. A diffusely enlarged thyroid with calcifications (n = 2) or nodules (n = 7) was detected on US. All PTC nodules showed malignant US findings and one FTC displayed on indeterminate nodule. Nodules generally showed low attenuation on enhanced CT (n = 11/12). US demonstrated enlarged glands with calcifications or nodules. Diffusely enlarged thyroids with microcalcifications should be evaluated using fine-needle aspiration. A low attenuation nodule was a common finding on enhanced CT.

  7. Eccrine Porocarcinoma: Patient Characteristics, Clinical and Histopathologic Features, and Treatment in 7 Cases.

    Gómez-Zubiaur, A; Medina-Montalvo, S; Vélez-Velázquez, M D; Polo-Rodríguez, I

    2017-05-01

    Eccrine porocarcinoma is a rare, malignant cutaneous adnexal tumor that arises from the ducts of sweat glands. Found mainly in patients of advanced age, this tumor has diverse clinical presentations. Histology confirms the diagnosis, detects features relevant to prognosis, and guides treatment. Growth is slow, but the prognosis is poor if the tumor metastasizes to lymph nodes or visceral organs. We report 7 cases of eccrine porocarcinoma, describing patient characteristics, the clinical and histopathologic features of the tumors, and treatments used. Our observations were similar to those of other published case series. Given the lack of therapeutic algorithms or protocols for this carcinoma, we propose a decision-making schema based on our review of the literature and our experience with this case series. The algorithm centers on sentinel lymph node biopsy and histologic features. Copyright © 2016 AEDV. Publicado por Elsevier España, S.L.U. All rights reserved.

  8. Classification of radiolarian images with hand-crafted and deep features

    Keçeli, Ali Seydi; Kaya, Aydın; Keçeli, Seda Uzunçimen

    2017-12-01

    Radiolarians are planktonic protozoa and are important biostratigraphic and paleoenvironmental indicators for paleogeographic reconstructions. Radiolarian paleontology still remains as a low cost and the one of the most convenient way to obtain dating of deep ocean sediments. Traditional methods for identifying radiolarians are time-consuming and cannot scale to the granularity or scope necessary for large-scale studies. Automated image classification will allow making these analyses promptly. In this study, a method for automatic radiolarian image classification is proposed on Scanning Electron Microscope (SEM) images of radiolarians to ease species identification of fossilized radiolarians. The proposed method uses both hand-crafted features like invariant moments, wavelet moments, Gabor features, basic morphological features and deep features obtained from a pre-trained Convolutional Neural Network (CNN). Feature selection is applied over deep features to reduce high dimensionality. Classification outcomes are analyzed to compare hand-crafted features, deep features, and their combinations. Results show that the deep features obtained from a pre-trained CNN are more discriminative comparing to hand-crafted ones. Additionally, feature selection utilizes to the computational cost of classification algorithms and have no negative effect on classification accuracy.

  9. A Feature Subtraction Method for Image Based Kinship Verification under Uncontrolled Environments

    Duan, Xiaodong; Tan, Zheng-Hua

    2015-01-01

    The most fundamental problem of local feature based kinship verification methods is that a local feature can capture the variations of environmental conditions and the differences between two persons having a kin relation, which can significantly decrease the performance. To address this problem...... the feature distance between face image pairs with kinship and maximize the distance between non-kinship pairs. Based on the subtracted feature, the verification is realized through a simple Gaussian based distance comparison method. Experiments on two public databases show that the feature subtraction method...

  10. Edge enhancement and noise suppression for infrared image based on feature analysis

    Jiang, Meng

    2018-06-01

    Infrared images are often suffering from background noise, blurred edges, few details and low signal-to-noise ratios. To improve infrared image quality, it is essential to suppress noise and enhance edges simultaneously. To realize it in this paper, we propose a novel algorithm based on feature analysis in shearlet domain. Firstly, as one of multi-scale geometric analysis (MGA), we introduce the theory and superiority of shearlet transform. Secondly, after analyzing the defects of traditional thresholding technique to suppress noise, we propose a novel feature extraction distinguishing image structures from noise well and use it to improve the traditional thresholding technique. Thirdly, with computing the correlations between neighboring shearlet coefficients, the feature attribute maps identifying the weak detail and strong edges are completed to improve the generalized unsharped masking (GUM). At last, experiment results with infrared images captured in different scenes demonstrate that the proposed algorithm suppresses noise efficiently and enhances image edges adaptively.

  11. Feature and Contrast Enhancement of Mammographic Image Based on Multiscale Analysis and Morphology

    Shibin Wu

    2013-01-01

    Full Text Available A new algorithm for feature and contrast enhancement of mammographic images is proposed in this paper. The approach bases on multiscale transform and mathematical morphology. First of all, the Laplacian Gaussian pyramid operator is applied to transform the mammography into different scale subband images. In addition, the detail or high frequency subimages are equalized by contrast limited adaptive histogram equalization (CLAHE and low-pass subimages are processed by mathematical morphology. Finally, the enhanced image of feature and contrast is reconstructed from the Laplacian Gaussian pyramid coefficients modified at one or more levels by contrast limited adaptive histogram equalization and mathematical morphology, respectively. The enhanced image is processed by global nonlinear operator. The experimental results show that the presented algorithm is effective for feature and contrast enhancement of mammogram. The performance evaluation of the proposed algorithm is measured by contrast evaluation criterion for image, signal-noise-ratio (SNR, and contrast improvement index (CII.

  12. Imaging characteristics of pilomyxoid astrocytomas in comparison with pilocytic astrocytomas

    Lee, In Ho; Kim, Ji Hye; Suh, Yeon-Lim; Eo, Hong; Shin, Hyung Jin; Yoo, So-Young; Lee, Kyung Soo

    2011-01-01

    Purpose: Pilomyxoid astrocytoma (PMA) is a recently described astrocytic tumor that has been previously diagnosed as pilocytic astrocytoma (PA). The purpose of this study was to describe the imaging features of PMAs in comparison with PAs. Materials and methods: We retrospectively reviewed CT/MR images and medical records of 10 patients with PMA and 38 patients with PA. The mean ages of patients with PMA and PA were 10 and 15 years, respectively. Imaging features including location, composition, enhancement pattern, presence of calcification, hemorrhage, and leptomeningeal dissemination were compared in patients with two tumor types. Results: Six PMAs (60%) occurred at the suprasellar area and the cerebellum was the most common (45%) site of PA. Solid component was dominant in eight PMAs (80%) and in 19 PAs (50%). All of the PMAs containing solid mass (n = 8) included non-enhancing portion while 12/37 (32%) PAs included non-enhancing solid portion (p < 0.05). Leptomeningeal dissemination was noted in five PMAs (50%) and one PA (3%) (p < 0.05). Other imaging findings were not significantly different. Conclusion: A younger age, more frequent occurrence at the suprasellar area, mainly solid mass containing non-enhancing portion, and more frequent leptomeningeal dissemination are helpful differential features of PMAs as compared to PAs.

  13. Rotation-invariant features for multi-oriented text detection in natural images.

    Cong Yao

    Full Text Available Texts in natural scenes carry rich semantic information, which can be used to assist a wide range of applications, such as object recognition, image/video retrieval, mapping/navigation, and human computer interaction. However, most existing systems are designed to detect and recognize horizontal (or near-horizontal texts. Due to the increasing popularity of mobile-computing devices and applications, detecting texts of varying orientations from natural images under less controlled conditions has become an important but challenging task. In this paper, we propose a new algorithm to detect texts of varying orientations. Our algorithm is based on a two-level classification scheme and two sets of features specially designed for capturing the intrinsic characteristics of texts. To better evaluate the proposed method and compare it with the competing algorithms, we generate a comprehensive dataset with various types of texts in diverse real-world scenes. We also propose a new evaluation protocol, which is more suitable for benchmarking algorithms for detecting texts in varying orientations. Experiments on benchmark datasets demonstrate that our system compares favorably with the state-of-the-art algorithms when handling horizontal texts and achieves significantly enhanced performance on variant texts in complex natural scenes.

  14. Instructional Quality Features in Videotaped Biology Lessons: Content-Independent Description of Characteristics

    Dorfner, Tobias; Förtsch, Christian; Boone, William; Neuhaus, Birgit J.

    2017-09-01

    A number of studies on single instructional quality features have been reported for mathematics and science instruction. For summarizing single instructional quality features, researchers have created a model of three basic dimensions (classroom management, supportive climate, and cognitive activation) of instructional quality mainly through observing mathematics instruction. Considering this model as valid for all subjects and as usable for describing instruction, we used it in this study which aimed to analyze characteristics of instructional quality in biology lessons of high-achieving and low-achieving classes, independently of content. Therefore, we used the data of three different previous video studies of biology instruction conducted in Germany. From each video study, we selected three high-achieving and three low-achieving classes (N = 18 teachers; 35 videos) for our multiple-case study, in which conspicuous characteristics of instructional quality features were qualitatively identified and qualitatively analyzed. The amount of these characteristics was counted in a quantitative way in all the videos. The characteristics we found could be categorized using the model of three basic dimensions of instructional quality despite some subject-specific differences for biology instruction. Our results revealed that many more characteristics were observable in high-achieving classes than in low-achieving classes. Thus, we believe that this model could be used to describe biology instruction independently of the content. We also make the claims about the qualities for biology instruction—working with concentration in a content-structured environment, getting challenged in higher order thinking, and getting praised for performance—that could have positive influence on students' achievement.

  15. Automated prostate cancer detection via comprehensive multi-parametric magnetic resonance imaging texture feature models

    Khalvati, Farzad; Wong, Alexander; Haider, Masoom A.

    2015-01-01

    Prostate cancer is the most common form of cancer and the second leading cause of cancer death in North America. Auto-detection of prostate cancer can play a major role in early detection of prostate cancer, which has a significant impact on patient survival rates. While multi-parametric magnetic resonance imaging (MP-MRI) has shown promise in diagnosis of prostate cancer, the existing auto-detection algorithms do not take advantage of abundance of data available in MP-MRI to improve detection accuracy. The goal of this research was to design a radiomics-based auto-detection method for prostate cancer via utilizing MP-MRI data. In this work, we present new MP-MRI texture feature models for radiomics-driven detection of prostate cancer. In addition to commonly used non-invasive imaging sequences in conventional MP-MRI, namely T2-weighted MRI (T2w) and diffusion-weighted imaging (DWI), our proposed MP-MRI texture feature models incorporate computed high-b DWI (CHB-DWI) and a new diffusion imaging modality called correlated diffusion imaging (CDI). Moreover, the proposed texture feature models incorporate features from individual b-value images. A comprehensive set of texture features was calculated for both the conventional MP-MRI and new MP-MRI texture feature models. We performed feature selection analysis for each individual modality and then combined best features from each modality to construct the optimized texture feature models. The performance of the proposed MP-MRI texture feature models was evaluated via leave-one-patient-out cross-validation using a support vector machine (SVM) classifier trained on 40,975 cancerous and healthy tissue samples obtained from real clinical MP-MRI datasets. The proposed MP-MRI texture feature models outperformed the conventional model (i.e., T2w+DWI) with regard to cancer detection accuracy. Comprehensive texture feature models were developed for improved radiomics-driven detection of prostate cancer using MP-MRI. Using a

  16. UNLABELED SELECTED SAMPLES IN FEATURE EXTRACTION FOR CLASSIFICATION OF HYPERSPECTRAL IMAGES WITH LIMITED TRAINING SAMPLES

    A. Kianisarkaleh

    2015-12-01

    Full Text Available Feature extraction plays a key role in hyperspectral images classification. Using unlabeled samples, often unlimitedly available, unsupervised and semisupervised feature extraction methods show better performance when limited number of training samples exists. This paper illustrates the importance of selecting appropriate unlabeled samples that used in feature extraction methods. Also proposes a new method for unlabeled samples selection using spectral and spatial information. The proposed method has four parts including: PCA, prior classification, posterior classification and sample selection. As hyperspectral image passes these parts, selected unlabeled samples can be used in arbitrary feature extraction methods. The effectiveness of the proposed unlabeled selected samples in unsupervised and semisupervised feature extraction is demonstrated using two real hyperspectral datasets. Results show that through selecting appropriate unlabeled samples, the proposed method can improve the performance of feature extraction methods and increase classification accuracy.

  17. Performance characteristics of proximity focused ultraviolet image converters

    Williams, J. T.; Feibelman, W. A.

    1973-01-01

    Performance characteristics of Bendix type BX 8025-4522 proximity focused image tubes for UV to visible light conversion are presented. Quantum efficiency, resolution, background, geometric distortion, and environmental test results are discussed. The converters use magnesium fluoride input windows with Cs-Te photocathodes and P-11 phosphors on fiber optic output windows.

  18. Variability of textural features in FDG PET images due to different acquisition modes and reconstruction parameters.

    Galavis, Paulina E; Hollensen, Christian; Jallow, Ngoneh; Paliwal, Bhudatt; Jeraj, Robert

    2010-10-01

    Characterization of textural features (spatial distributions of image intensity levels) has been considered as a tool for automatic tumor segmentation. The purpose of this work is to study the variability of the textural features in PET images due to different acquisition modes and reconstruction parameters. Twenty patients with solid tumors underwent PET/CT scans on a GE Discovery VCT scanner, 45-60 minutes post-injection of 10 mCi of [(18)F]FDG. Scans were acquired in both 2D and 3D modes. For each acquisition the raw PET data was reconstructed using five different reconstruction parameters. Lesions were segmented on a default image using the threshold of 40% of maximum SUV. Fifty different texture features were calculated inside the tumors. The range of variations of the features were calculated with respect to the average value. Fifty textural features were classified based on the range of variation in three categories: small, intermediate and large variability. Features with small variability (range ≤ 5%) were entropy-first order, energy, maximal correlation coefficient (second order feature) and low-gray level run emphasis (high-order feature). The features with intermediate variability (10% ≤ range ≤ 25%) were entropy-GLCM, sum entropy, high gray level run emphsis, gray level non-uniformity, small number emphasis, and entropy-NGL. Forty remaining features presented large variations (range > 30%). Textural features such as entropy-first order, energy, maximal correlation coefficient, and low-gray level run emphasis exhibited small variations due to different acquisition modes and reconstruction parameters. Features with low level of variations are better candidates for reproducible tumor segmentation. Even though features such as contrast-NGTD, coarseness, homogeneity, and busyness have been previously used, our data indicated that these features presented large variations, therefore they could not be considered as a good candidates for tumor

  19. Variability of textural features in FDG PET images due to different acquisition modes and reconstruction parameters

    Galavis, Paulina E.; Jallow, Ngoneh; Paliwal, Bhudatt; Jeraj, Robert; Hollensen, Christian

    2010-01-01

    Background. Characterization of textural features (spatial distributions of image intensity levels) has been considered as a tool for automatic tumor segmentation. The purpose of this work is to study the variability of the textural features in PET images due to different acquisition modes and reconstruction parameters. Material and methods. Twenty patients with solid tumors underwent PET/CT scans on a GE Discovery VCT scanner, 45-60 minutes post-injection of 10 mCi of [ 18 F]FDG. Scans were acquired in both 2D and 3D modes. For each acquisition the raw PET data was reconstructed using five different reconstruction parameters. Lesions were segmented on a default image using the threshold of 40% of maximum SUV. Fifty different texture features were calculated inside the tumors. The range of variations of the features were calculated with respect to the average value. Results. Fifty textural features were classified based on the range of variation in three categories: small, intermediate and large variability. Features with small variability (range = 5%) were entropy-first order, energy, maximal correlation coefficient (second order feature) and low-gray level run emphasis (high-order feature). The features with intermediate variability (10% = range = 25%) were entropy-GLCM, sum entropy, high gray level run emphasis, gray level non-uniformity, small number emphasis, and entropy-NGL. Forty remaining features presented large variations (range > 30%). Conclusion. Textural features such as entropy-first order, energy, maximal correlation coefficient, and low-gray level run emphasis exhibited small variations due to different acquisition modes and reconstruction parameters. Features with low level of variations are better candidates for reproducible tumor segmentation. Even though features such as contrast-NGTD, coarseness, homogeneity, and busyness have been previously used, our data indicated that these features presented large variations, therefore they could not be

  20. Improved medical image modality classification using a combination of visual and textual features.

    Dimitrovski, Ivica; Kocev, Dragi; Kitanovski, Ivan; Loskovska, Suzana; Džeroski, Sašo

    2015-01-01

    In this paper, we present the approach that we applied to the medical modality classification tasks at the ImageCLEF evaluation forum. More specifically, we used the modality classification databases from the ImageCLEF competitions in 2011, 2012 and 2013, described by four visual and one textual types of features, and combinations thereof. We used local binary patterns, color and edge directivity descriptors, fuzzy color and texture histogram and scale-invariant feature transform (and its variant opponentSIFT) as visual features and the standard bag-of-words textual representation coupled with TF-IDF weighting. The results from the extensive experimental evaluation identify the SIFT and opponentSIFT features as the best performing features for modality classification. Next, the low-level fusion of the visual features improves the predictive performance of the classifiers. This is because the different features are able to capture different aspects of an image, their combination offering a more complete representation of the visual content in an image. Moreover, adding textual features further increases the predictive performance. Finally, the results obtained with our approach are the best results reported on these databases so far. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. Extended feature-fusion guidelines to improve image-based multi-modal biometrics

    Brown, Dane

    2016-09-01

    Full Text Available The feature-level, unlike the match score-level, lacks multi-modal fusion guidelines. This work demonstrates a practical approach for improved image-based biometric feature-fusion. The approach extracts and combines the face, fingerprint...

  2. Profiles of US and CT imaging features with a high probability of appendicitis

    van Randen, A.; Laméris, W.; van Es, H.W.; ten Hove, W.; Bouma, W.H.; van Leeuwen, M.S.; van Keulen, E.M.; van der Hulst, V.P.M.; Henneman, O.D.; Bossuyt, P.M.; Boermeester, M.A.; Stoker, J.

    2010-01-01

    To identify and evaluate profiles of US and CT features associated with acute appendicitis. Consecutive patients presenting with acute abdominal pain at the emergency department were invited to participate in this study. All patients underwent US and CT. Imaging features known to be associated with

  3. Schnitzler's syndrome: an unusual cause of bone pain with suggestive nuclear imaging features

    Raedt, N. de; Mortelmans, L.

    2009-01-01

    Schnitzler's syndrome is a rare inflammatory disorder characterised by chronic urticarial rash and monoclonal IgM gammopathy accompanied by at least two of the following features: fever, arthralgia or arthritis, bone pain, lymphadenopathy, hepato- or splenomegaly, leucocytosis and elevated sedimentation. The association of these clinical and biological features with radiographic and bone scan findings are suggestive of the disease. The case of a 37-year-old man presenting with Schnitzler's syndrome, emphasizing nuclear imaging features is reported here. (N.C.)

  4. Imaging features of tuberculous mastitis : Comparison with non-tuberculous mastitis

    Won, Mi Sook; Chung, Soo Young; Yang, Ik; Lee, Yul; Kim, Young Mook; Lee, Myung Hwan [College of Medicine, Hallym Univ., Seoul (Korea, Republic of); Kim, Hak Hee [College of Medicine, Catholic Univ., Seoul (Korea, Republic of); Im, Jung Gi [College of Medicine, Seoul National Univ., Seoul (Korea, Republic of)

    1996-12-01

    The purpose of this report is to evaluate the characteristic findings of tuberculosis of the breast on mammogram, sonogram, and CT and to compare the results with the imaging feature of non-tuberculous mastitis. Using mammograms and sonograms, nine cases of tuberculosis of the breast were evaluated, and for four cases, CT was used. Aspects evaluated were contour, shape and size of the lesion, homogeneity of internal content, and extension of the lesion from/to the adjacent organs. Diagnosis was based on aspiration, surgery, and pathologic findings including acid-fast bacillus (AFB) staining. Mammograms and sonograms of 19 patients with non-tuberculous mastitis of the breast were reviewed. No cases of tuberculous mastitis presented clinical evidence of acute inflammation such as fever, swelling or skin redness. Nine cases of tuberculous mastitis were seen as a distinct mass on mammogram and sonogram. Four of nine cases (44.4%) showed a relatively smooth peripheral margin on mammogram and a cold abscess form on sonogram and CT. There were other foci of tuberculosis in the chest wall, anterior mediastinum, pleural cavity or lung. Five cases demonstrated as a nodular type on US. In the non-tuberculous mastitis group, and abscess with distinct margin or direct contiguity between a breast lesion and the adjacent organ was observed neither on mammogram nor on sonogram. In an afebrile patient, relative homogeneous density with distinct margin in the breast on mammogram and a fistulous connection or direct continuity between breat abscess form with the adjacent organ on sonogram or CT is a characteristic feature of the tuberculous mastitis. The cold abscess type is a frequent subtypes of this entity, and must also be included.

  5. Imaging features of tuberculous mastitis : Comparison with non-tuberculous mastitis

    Won, Mi Sook; Chung, Soo Young; Yang, Ik; Lee, Yul; Kim, Young Mook; Lee, Myung Hwan; Kim, Hak Hee; Im, Jung Gi

    1996-01-01

    The purpose of this report is to evaluate the characteristic findings of tuberculosis of the breast on mammogram, sonogram, and CT and to compare the results with the imaging feature of non-tuberculous mastitis. Using mammograms and sonograms, nine cases of tuberculosis of the breast were evaluated, and for four cases, CT was used. Aspects evaluated were contour, shape and size of the lesion, homogeneity of internal content, and extension of the lesion from/to the adjacent organs. Diagnosis was based on aspiration, surgery, and pathologic findings including acid-fast bacillus (AFB) staining. Mammograms and sonograms of 19 patients with non-tuberculous mastitis of the breast were reviewed. No cases of tuberculous mastitis presented clinical evidence of acute inflammation such as fever, swelling or skin redness. Nine cases of tuberculous mastitis were seen as a distinct mass on mammogram and sonogram. Four of nine cases (44.4%) showed a relatively smooth peripheral margin on mammogram and a cold abscess form on sonogram and CT. There were other foci of tuberculosis in the chest wall, anterior mediastinum, pleural cavity or lung. Five cases demonstrated as a nodular type on US. In the non-tuberculous mastitis group, and abscess with distinct margin or direct contiguity between a breast lesion and the adjacent organ was observed neither on mammogram nor on sonogram. In an afebrile patient, relative homogeneous density with distinct margin in the breast on mammogram and a fistulous connection or direct continuity between breat abscess form with the adjacent organ on sonogram or CT is a characteristic feature of the tuberculous mastitis. The cold abscess type is a frequent subtypes of this entity, and must also be included

  6. Characteristics of Tau and Its Ligands in PET Imaging

    Ryuichi Harada

    2016-01-01

    Full Text Available Tau deposition is one of the neuropathological hallmarks in Alzheimer’s disease as well as in other neurodegenerative disorders called tauopathies. Recent efforts to develop selective tau radiopharmaceuticals have allowed the visualization of tau deposits in vivo. In vivo tau imaging allows the assessment of the regional distribution of tau deposits in a single human subject over time for determining the pathophysiology of tau accumulation in aging and neurodegenerative conditions as well as for application in drug discovery of anti-dementia drugs as surrogate markers. However, tau deposits show complicated characteristics because of different isoform composition, histopathology, and ultrastructure in various neurodegenerative conditions. In addition, since tau radiopharmaceuticals possess different chemotype classes, they may show different binding characteristics with heterogeneous tau deposits. In this review, we describe the characteristics of tau deposits and their ligands that have β-sheet binding properties, and the status of tau imaging in clinical studies.

  7. The Feature Extraction Based on Texture Image Information for Emotion Sensing in Speech

    Kun-Ching Wang

    2014-09-01

    Full Text Available In this paper, we present a novel texture image feature for Emotion Sensing in Speech (ESS. This idea is based on the fact that the texture images carry emotion-related information. The feature extraction is derived from time-frequency representation of spectrogram images. First, we transform the spectrogram as a recognizable image. Next, we use a cubic curve to enhance the image contrast. Then, the texture image information (TII derived from the spectrogram image can be extracted by using Laws’ masks to characterize emotional state. In order to evaluate the effectiveness of the proposed emotion recognition in different languages, we use two open emotional databases including the Berlin Emotional Speech Database (EMO-DB and eNTERFACE corpus and one self-recorded database (KHUSC-EmoDB, to evaluate the performance cross-corpora. The results of the proposed ESS system are presented using support vector machine (SVM as a classifier. Experimental results show that the proposed TII-based feature extraction inspired by visual perception can provide significant classification for ESS systems. The two-dimensional (2-D TII feature can provide the discrimination between different emotions in visual expressions except for the conveyance pitch and formant tracks. In addition, the de-noising in 2-D images can be more easily completed than de-noising in 1-D speech.

  8. Learning effective color features for content based image retrieval in dermatology

    Bunte, Kerstin; Biehl, Michael; Jonkman, Marcel F.; Petkov, Nicolai

    We investigate the extraction of effective color features for a content-based image retrieval (CBIR) application in dermatology. Effectiveness is measured by the rate of correct retrieval of images from four color classes of skin lesions. We employ and compare two different methods to learn

  9. Comparison of clustering methods for tracking features in RGB-D images

    Pancham, Ardhisha

    2016-10-01

    Full Text Available difficult to track individually over an image sequence. Clustering techniques have been recommended and used to cluster image features to improve tracking results. New and affordable RGB-D cameras, provide both color and depth information. This paper...

  10. Multi-example feature-constrained back-projection method for image super-resolution

    Junlei Zhang; Dianguang Gai; Xin Zhang; Xuemei Li

    2017-01-01

    Example-based super-resolution algorithms,which predict unknown high-resolution image information using a relationship model learnt from known high- and low-resolution image pairs, have attracted considerable interest in the field of image processing. In this paper, we propose a multi-example feature-constrained back-projection method for image super-resolution. Firstly, we take advantage of a feature-constrained polynomial interpolation method to enlarge the low-resolution image. Next, we consider low-frequency images of different resolutions to provide an example pair. Then, we use adaptive k NN search to find similar patches in the low-resolution image for every image patch in the high-resolution low-frequency image, leading to a regression model between similar patches to be learnt. The learnt model is applied to the low-resolution high-frequency image to produce high-resolution high-frequency information. An iterative back-projection algorithm is used as the final step to determine the final high-resolution image.Experimental results demonstrate that our method improves the visual quality of the high-resolution image.

  11. Features and limitations of mobile tablet devices for viewing radiological images.

    Grunert, J H

    2015-03-01

    Mobile radiological image display systems are becoming increasingly common, necessitating a comparison of the features of these systems, specifically the operating system employed, connection to stationary PACS, data security and rang of image display and image analysis functions. In the fall of 2013, a total of 17 PACS suppliers were surveyed regarding the technical features of 18 mobile radiological image display systems using a standardized questionnaire. The study also examined to what extent the technical specifications of the mobile image display systems satisfy the provisions of the Germany Medical Devices Act as well as the provisions of the German X-ray ordinance (RöV). There are clear differences in terms of how the mobile systems connected to the stationary PACS. Web-based solutions allow the mobile image display systems to function independently of their operating systems. The examined systems differed very little in terms of image display and image analysis functions. Mobile image display systems complement stationary PACS and can be used to view images. The impacts of the new quality assurance guidelines (QS-RL) as well as the upcoming new standard DIN 6868 - 157 on the acceptance testing of mobile image display units for the purpose of image evaluation are discussed. © Georg Thieme Verlag KG Stuttgart · New York.

  12. A blur-invariant local feature for motion blurred image matching

    Tong, Qiang; Aoki, Terumasa

    2017-07-01

    Image matching between a blurred (caused by camera motion, out of focus, etc.) image and a non-blurred image is a critical task for many image/video applications. However, most of the existing local feature schemes fail to achieve this work. This paper presents a blur-invariant descriptor and a novel local feature scheme including the descriptor and the interest point detector based on moment symmetry - the authors' previous work. The descriptor is based on a new concept - center peak moment-like element (CPME) which is robust to blur and boundary effect. Then by constructing CPMEs, the descriptor is also distinctive and suitable for image matching. Experimental results show our scheme outperforms state of the art methods for blurred image matching

  13. Extending the MEDAS Feature Dictionary to Support Access to Radiological Images

    Kaufman, Bryan L.; Naeymi-Rad, Frank; Charletta, Dale A.; Kepic, Anna; Trace, David A.; Naeymirad, Shon; Carmony, Lowell; Spigos, Dimitrios; Evens, Martha

    1989-01-01

    This paper discusses a method of adding a library of radiological images to MEDAS (the Medical Emergency Decision Assistance System). This library is interfaced with the MEDAS Feature Dictionary [1, 2], a dictionary containing terminology for MEDAS knowledge bases. The connections between the radiological images and the terms in the dictionary are used in two ways: 1) To retrieve the images with free text queries. 2) To help in the evaluation of radiological findings during the diagnostic cyc...

  14. [Localized Scleroderma of Lower Extremities:Clinical and Magnetic Resonance Imaging Features].

    Wang, Feng-dan; Wang, Hong-wei; Wu, Zhi-hong; Hou, Bo; Jiang, Bo; Zhang, Yan; Feng, Feng; Jin, Zheng-yu; Yuan, Xie

    2015-08-01

    To evaluate the clinical and musculoskeletal characteristics of localized scleroderma with lower extremities affected. All the localized scleroderma patients,who received magnetic resonance (MR ) examinations of affected lower extremities at Peking Union Medical College Hospital from April 2013 to June 2014,were retrospectively reviewed. Their clinical data and laboratory results of antinuclear antibody,anti-double stranded-DNA antibody, and anti-extractable nuclear antigen antibody were collected and analyzed. All the MR examinations were non-contrast imaging using Siemens Skyra 3.0T MR scanner. There were 16 localized scleroderma patients with lower extremities affected, 11 of whom were linear scleroderma, 4 generalized morphea, and 1 deep morphea. Female to male ratio was 1:2.2. The mean age was 22.5 years. The mean time span was 7.4 years. Four of the 14 patients (28.6%) who received antinuclear antibody test were positive. All the 10 patients who received anti-double stranded-DNA antibody test and the 7 patients who received anti-extractable nuclear antigen antibody test were negative. The most common musculoskeletal MR features were subcutaneous septal thickening (16/16) and fascial thickening (11/16). The thickened speta and fascia could either be hypointenstiy or hyperintensity on turbo inversion recovery magnitude/proton density weighted imaging. Other MR manifestations were intramuscular speta thickening (3/16), muscular abnormal signals (1/16), and bone marrow abnormal signals (2/16). Musculoskeletal manifestations of the lower extremities with localized scleroderma can be well revealed using MR imaging.

  15. Profiles of US and CT imaging features with a high probability of appendicitis

    Randen, A. van; Lameris, W.; Es, H.W. van; Hove, W. ten; Bouma, W.H.; Leeuwen, M.S. van; Keulen, E.M. van; Hulst, V.P.M. van der; Henneman, O.D.; Bossuyt, P.M.; Boermeester, M.A.; Stoker, J.

    2010-01-01

    To identify and evaluate profiles of US and CT features associated with acute appendicitis. Consecutive patients presenting with acute abdominal pain at the emergency department were invited to participate in this study. All patients underwent US and CT. Imaging features known to be associated with appendicitis, and an imaging diagnosis were prospectively recorded by two independent radiologists. A final diagnosis was assigned after 6 months. Associations between appendiceal imaging features and a final diagnosis of appendicitis were evaluated with logistic regression analysis. Appendicitis was assigned to 284 of 942 evaluated patients (30%). All evaluated features were associated with appendicitis. Imaging profiles were created after multivariable logistic regression analysis. Of 147 patients with a thickened appendix, local transducer tenderness and peri-appendiceal fat infiltration on US, 139 (95%) had appendicitis. On CT, 119 patients in whom the appendix was completely visualised, thickened, with peri-appendiceal fat infiltration and appendiceal enhancement, 114 had a final diagnosis of appendicitis (96%). When at least two of these essential features were present on US or CT, sensitivity was 92% (95% CI 89-96%) and 96% (95% CI 93-98%), respectively. Most patients with appendicitis can be categorised within a few imaging profiles on US and CT. When two of the essential features are present the diagnosis of appendicitis can be made accurately. (orig.)

  16. Profiles of US and CT imaging features with a high probability of appendicitis

    Randen, A. van; Lameris, W. [University of Amsterdam, Department of Radiology, Academic Medical Center, Amsterdam (Netherlands); University of Amsterdam, Department of Surgery, Academic Medical Center, Amsterdam (Netherlands); Es, H.W. van [St Antonius Hospital, Department of Radiology, Nieuwegein (Netherlands); Hove, W. ten; Bouma, W.H. [Gelre Hospitals, Department of Surgery, Apeldoorn (Netherlands); Leeuwen, M.S. van [University Medical Centre, Department of Radiology, Utrecht (Netherlands); Keulen, E.M. van [Tergooi Hospitals, Department of Radiology, Hilversum (Netherlands); Hulst, V.P.M. van der [Onze Lieve Vrouwe Gasthuis, Department of Radiology, Amsterdam (Netherlands); Henneman, O.D. [Bronovo Hospital, Department of Radiology, The Hague (Netherlands); Bossuyt, P.M. [University of Amsterdam, Department of Clinical Epidemiology, Biostatistics, and Bioinformatics, Academic Medical Center, Amsterdam (Netherlands); Boermeester, M.A. [University of Amsterdam, Department of Surgery, Academic Medical Center, Amsterdam (Netherlands); Stoker, J. [University of Amsterdam, Department of Radiology, Academic Medical Center, Amsterdam (Netherlands)

    2010-07-15

    To identify and evaluate profiles of US and CT features associated with acute appendicitis. Consecutive patients presenting with acute abdominal pain at the emergency department were invited to participate in this study. All patients underwent US and CT. Imaging features known to be associated with appendicitis, and an imaging diagnosis were prospectively recorded by two independent radiologists. A final diagnosis was assigned after 6 months. Associations between appendiceal imaging features and a final diagnosis of appendicitis were evaluated with logistic regression analysis. Appendicitis was assigned to 284 of 942 evaluated patients (30%). All evaluated features were associated with appendicitis. Imaging profiles were created after multivariable logistic regression analysis. Of 147 patients with a thickened appendix, local transducer tenderness and peri-appendiceal fat infiltration on US, 139 (95%) had appendicitis. On CT, 119 patients in whom the appendix was completely visualised, thickened, with peri-appendiceal fat infiltration and appendiceal enhancement, 114 had a final diagnosis of appendicitis (96%). When at least two of these essential features were present on US or CT, sensitivity was 92% (95% CI 89-96%) and 96% (95% CI 93-98%), respectively. Most patients with appendicitis can be categorised within a few imaging profiles on US and CT. When two of the essential features are present the diagnosis of appendicitis can be made accurately. (orig.)

  17. Disaster damage detection through synergistic use of deep learning and 3D point cloud features derived from very high resolution oblique aerial images, and multiple-kernel-learning

    Vetrivel, Anand; Gerke, Markus; Kerle, Norman; Nex, Francesco; Vosselman, George

    2018-06-01

    Oblique aerial images offer views of both building roofs and façades, and thus have been recognized as a potential source to detect severe building damages caused by destructive disaster events such as earthquakes. Therefore, they represent an important source of information for first responders or other stakeholders involved in the post-disaster response process. Several automated methods based on supervised learning have already been demonstrated for damage detection using oblique airborne images. However, they often do not generalize well when data from new unseen sites need to be processed, hampering their practical use. Reasons for this limitation include image and scene characteristics, though the most prominent one relates to the image features being used for training the classifier. Recently features based on deep learning approaches, such as convolutional neural networks (CNNs), have been shown to be more effective than conventional hand-crafted features, and have become the state-of-the-art in many domains, including remote sensing. Moreover, often oblique images are captured with high block overlap, facilitating the generation of dense 3D point clouds - an ideal source to derive geometric characteristics. We hypothesized that the use of CNN features, either independently or in combination with 3D point cloud features, would yield improved performance in damage detection. To this end we used CNN and 3D features, both independently and in combination, using images from manned and unmanned aerial platforms over several geographic locations that vary significantly in terms of image and scene characteristics. A multiple-kernel-learning framework, an effective way for integrating features from different modalities, was used for combining the two sets of features for classification. The results are encouraging: while CNN features produced an average classification accuracy of about 91%, the integration of 3D point cloud features led to an additional

  18. Some distinguishing characteristics of contour and texture phenomena in images

    Jobson, Daniel J.

    1992-01-01

    The development of generalized contour/texture discrimination techniques is a central element necessary for machine vision recognition and interpretation of arbitrary images. Here, the visual perception of texture, selected studies of texture analysis in machine vision, and diverse small samples of contour and texture are all used to provide insights into the fundamental characteristics of contour and texture. From these, an experimental discrimination scheme is developed and tested on a battery of natural images. The visual perception of texture defined fine texture as a subclass which is interpreted as shading and is distinct from coarse figural similarity textures. Also, perception defined the smallest scale for contour/texture discrimination as eight to nine visual acuity units. Three contour/texture discrimination parameters were found to be moderately successful for this scale discrimination: (1) lightness change in a blurred version of the image, (2) change in lightness change in the original image, and (3) percent change in edge counts relative to local maximum.

  19. Automatic detection of solar features in HSOS full-disk solar images using guided filter

    Yuan, Fei; Lin, Jiaben; Guo, Jingjing; Wang, Gang; Tong, Liyue; Zhang, Xinwei; Wang, Bingxiang

    2018-02-01

    A procedure is introduced for the automatic detection of solar features using full-disk solar images from Huairou Solar Observing Station (HSOS), National Astronomical Observatories of China. In image preprocessing, median filter is applied to remove the noises. Guided filter is adopted to enhance the edges of solar features and restrain the solar limb darkening, which is first introduced into the astronomical target detection. Then specific features are detected by Otsu algorithm and further threshold processing technique. Compared with other automatic detection procedures, our procedure has some advantages such as real time and reliability as well as no need of local threshold. Also, it reduces the amount of computation largely, which is benefited from the efficient guided filter algorithm. The procedure has been tested on one month sequences (December 2013) of HSOS full-disk solar images and the result shows that the number of features detected by our procedure is well consistent with the manual one.

  20. 3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes.

    Zhong, Zichun; Guo, Xiaohu; Cai, Yiqi; Yang, Yin; Wang, Jing; Jia, Xun; Mao, Weihua

    2016-01-01

    By using prior information of planning CT images and feature-based nonuniform meshes, this paper demonstrates that volumetric images can be efficiently registered with a very small portion of 2D projection images of a Cone-Beam Computed Tomography (CBCT) scan. After a density field is computed based on the extracted feature edges from planning CT images, nonuniform tetrahedral meshes will be automatically generated to better characterize the image features according to the density field; that is, finer meshes are generated for features. The displacement vector fields (DVFs) are specified at the mesh vertices to drive the deformation of original CT images. Digitally reconstructed radiographs (DRRs) of the deformed anatomy are generated and compared with corresponding 2D projections. DVFs are optimized to minimize the objective function including differences between DRRs and projections and the regularity. To further accelerate the above 3D-2D registration, a procedure to obtain good initial deformations by deforming the volume surface to match 2D body boundary on projections has been developed. This complete method is evaluated quantitatively by using several digital phantoms and data from head and neck cancer patients. The feature-based nonuniform meshing method leads to better results than either uniform orthogonal grid or uniform tetrahedral meshes.

  1. 3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes

    Zichun Zhong

    2016-01-01

    Full Text Available By using prior information of planning CT images and feature-based nonuniform meshes, this paper demonstrates that volumetric images can be efficiently registered with a very small portion of 2D projection images of a Cone-Beam Computed Tomography (CBCT scan. After a density field is computed based on the extracted feature edges from planning CT images, nonuniform tetrahedral meshes will be automatically generated to better characterize the image features according to the density field; that is, finer meshes are generated for features. The displacement vector fields (DVFs are specified at the mesh vertices to drive the deformation of original CT images. Digitally reconstructed radiographs (DRRs of the deformed anatomy are generated and compared with corresponding 2D projections. DVFs are optimized to minimize the objective function including differences between DRRs and projections and the regularity. To further accelerate the above 3D-2D registration, a procedure to obtain good initial deformations by deforming the volume surface to match 2D body boundary on projections has been developed. This complete method is evaluated quantitatively by using several digital phantoms and data from head and neck cancer patients. The feature-based nonuniform meshing method leads to better results than either uniform orthogonal grid or uniform tetrahedral meshes.

  2. Segmentation of Clinical Endoscopic Images Based on the Classification of Topological Vector Features

    O. A. Dunaeva

    2013-01-01

    Full Text Available In this work, we describe a prototype of an automatic segmentation system and annotation of endoscopy images. The used algorithm is based on the classification of vectors of the topological features of the original image. We use the image processing scheme which includes image preprocessing, calculation of vector descriptors defined for every point of the source image and the subsequent classification of descriptors. Image preprocessing includes finding and selecting artifacts and equalizating the image brightness. In this work, we give the detailed algorithm of the construction of topological descriptors and the classifier creating procedure based on mutual sharing the AdaBoost scheme and a naive Bayes classifier. In the final section, we show the results of the classification of real endoscopic images.

  3. A unified framework of image latent feature learning on Sina microblog

    Wei, Jinjin; Jin, Zhigang; Zhou, Yuan; Zhang, Rui

    2015-10-01

    Large-scale user-contributed images with texts are rapidly increasing on the social media websites, such as Sina microblog. However, the noise and incomplete correspondence between the images and the texts give rise to the difficulty in precise image retrieval and ranking. In this paper, a hypergraph-based learning framework is proposed for image ranking, which simultaneously utilizes visual feature, textual content and social link information to estimate the relevance between images. Representing each image as a vertex in the hypergraph, complex relationship between images can be reflected exactly. Then updating the weight of hyperedges throughout the hypergraph learning process, the effect of different edges can be adaptively modulated in the constructed hypergraph. Furthermore, the popularity degree of the image is employed to re-rank the retrieval results. Comparative experiments on a large-scale Sina microblog data-set demonstrate the effectiveness of the proposed approach.

  4. Computed Tomography and Magnetic Resonance Imaging Features of the Temporomandibular Joint in Two Normal Camels

    Alberto Arencibia

    2012-01-01

    Full Text Available Computed tomography (CT and magnetic resonance (MR image features of the temporomandibular joint (TMJ and associated structures in two mature dromedary camels were obtained with a third-generation equipment CT and a superconducting magnet RM at 1.5 Tesla. Images were acquired in sagittal and transverse planes. Medical imaging processing with imaging software was applied to obtain postprocessing CT and MR images. Relevant anatomic structures were identified and labelled. The resulting images provided