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Sample records for differential imaging features

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

    International Nuclear Information System (INIS)

    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

  2. Differential diagnostic features of the radionuclide scrotal image

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    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. Differential diagnostic features of the radionuclide scrotal image

    International Nuclear Information System (INIS)

    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

  4. Sclerosing cholangitis: Clinicopathologic features, imaging spectrum, and systemic approach to differential diagnosis

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    Seo, Ni Eun [Dept. of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul (Korea, Republic of); Kim, So Yeon; Lee, Seung Soo; Byun, Jae Ho; Kim, Hyoung Jung; Kim, Jin Hee; Lee, Moon Gyu [Dept. of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul (Korea, Republic of)

    2016-02-15

    Sclerosing cholangitis is a spectrum of chronic progressive cholestatic liver disease characterized by inflammation, fibrosis, and stricture of the bile ducts, which can be classified as primary and secondary sclerosing cholangitis. Primary sclerosing cholangitis is a chronic progressive liver disease of unknown cause. On the other hand, secondary sclerosing cholangitis has identifiable causes that include immunoglobulin G4-related sclerosing disease, recurrent pyogenic cholangitis, ischemic cholangitis, acquired immunodeficiency syndrome-related cholangitis, and eosinophilic cholangitis. In this review, we suggest a systemic approach to the differential diagnosis of sclerosing cholangitis based on the clinical and laboratory findings, as well as the typical imaging features on computed tomography and magnetic resonance (MR) imaging with MR cholangiography. Familiarity with various etiologies of sclerosing cholangitis and awareness of their typical clinical and imaging findings are essential for an accurate diagnosis and appropriate management.

  5. Sclerosing Cholangitis: Clinicopathologic Features, Imaging Spectrum, and Systemic Approach to Differential Diagnosis.

    Science.gov (United States)

    Seo, Nieun; Kim, So Yeon; Lee, Seung Soo; Byun, Jae Ho; Kim, Jin Hee; Kim, Hyoung Jung; Lee, Moon-Gyu

    2016-01-01

    Sclerosing cholangitis is a spectrum of chronic progressive cholestatic liver disease characterized by inflammation, fibrosis, and stricture of the bile ducts, which can be classified as primary and secondary sclerosing cholangitis. Primary sclerosing cholangitis is a chronic progressive liver disease of unknown cause. On the other hand, secondary sclerosing cholangitis has identifiable causes that include immunoglobulin G4-related sclerosing disease, recurrent pyogenic cholangitis, ischemic cholangitis, acquired immunodeficiency syndrome-related cholangitis, and eosinophilic cholangitis. In this review, we suggest a systemic approach to the differential diagnosis of sclerosing cholangitis based on the clinical and laboratory findings, as well as the typical imaging features on computed tomography and magnetic resonance (MR) imaging with MR cholangiography. Familiarity with various etiologies of sclerosing cholangitis and awareness of their typical clinical and imaging findings are essential for an accurate diagnosis and appropriate management.

  6. Differentiating benign from malignant bone tumors using fluid-fluid level features on magnetic resonance imaging

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    Yu, Hong; Cui, Jian Ling; Cui, Sheng Jie; Sun, Ying Cal; Cui, Feng Zhen [Dept. of Radiology, The Third Hospital of Hebei Medical University, Hebei Province Biomechanical Key Laborary of Orthopedics, Shijiazhuang, Hebei (China)

    2014-12-15

    To analyze different fluid-fluid level features between benign and malignant bone tumors on magnetic resonance imaging (MRI). This study was approved by the hospital ethics committee. We retrospectively analyzed 47 patients diagnosed with benign (n = 29) or malignant (n = 18) bone tumors demonstrated by biopsy/surgical resection and who showed the intratumoral fluid-fluid level on pre-surgical MRI. The maximum length of the largest fluid-fluid level and the ratio of the maximum length of the largest fluid-fluid level to the maximum length of a bone tumor in the sagittal plane were investigated for use in distinguishing benign from malignant tumors using the Mann-Whitney U-test and a receiver operating characteristic (ROC) analysis. Fluid-fluid level was categorized by quantity (multiple vs. single fluid-fluid level) and by T1-weighted image signal pattern (high/low, low/high, and undifferentiated), and the findings were compared between the benign and malignant groups using the chi2 test. The ratio of the maximum length of the largest fluid-fluid level to the maximum length of bone tumors in the sagittal plane that allowed statistically significant differentiation between benign and malignant bone tumors had an area under the ROC curve of 0.758 (95% confidence interval, 0.616-0.899). A cutoff value of 41.5% (higher value suggests a benign tumor) had sensitivity of 73% and specificity of 83%. The ratio of the maximum length of the largest fluid-fluid level to the maximum length of a bone tumor in the sagittal plane may be useful to differentiate benign from malignant bone tumors.

  7. Differentiating benign from malignant bone tumors using fluid-fluid level features on magnetic resonance imaging

    International Nuclear Information System (INIS)

    Yu, Hong; Cui, Jian Ling; Cui, Sheng Jie; Sun, Ying Cal; Cui, Feng Zhen

    2014-01-01

    To analyze different fluid-fluid level features between benign and malignant bone tumors on magnetic resonance imaging (MRI). This study was approved by the hospital ethics committee. We retrospectively analyzed 47 patients diagnosed with benign (n = 29) or malignant (n = 18) bone tumors demonstrated by biopsy/surgical resection and who showed the intratumoral fluid-fluid level on pre-surgical MRI. The maximum length of the largest fluid-fluid level and the ratio of the maximum length of the largest fluid-fluid level to the maximum length of a bone tumor in the sagittal plane were investigated for use in distinguishing benign from malignant tumors using the Mann-Whitney U-test and a receiver operating characteristic (ROC) analysis. Fluid-fluid level was categorized by quantity (multiple vs. single fluid-fluid level) and by T1-weighted image signal pattern (high/low, low/high, and undifferentiated), and the findings were compared between the benign and malignant groups using the chi2 test. The ratio of the maximum length of the largest fluid-fluid level to the maximum length of bone tumors in the sagittal plane that allowed statistically significant differentiation between benign and malignant bone tumors had an area under the ROC curve of 0.758 (95% confidence interval, 0.616-0.899). A cutoff value of 41.5% (higher value suggests a benign tumor) had sensitivity of 73% and specificity of 83%. The ratio of the maximum length of the largest fluid-fluid level to the maximum length of a bone tumor in the sagittal plane may be useful to differentiate benign from malignant bone tumors.

  8. Differentiation of Uterine Leiomyosarcoma from Atypical Leiomyoma: Diagnostic Accuracy of Qualitative MR Imaging Features and Feasibility of Texture Analysis.

    Science.gov (United States)

    Lakhman, Yulia; Veeraraghavan, Harini; Chaim, Joshua; Feier, Diana; Goldman, Debra A; Moskowitz, Chaya S; Nougaret, Stephanie; Sosa, Ramon E; Vargas, Hebert Alberto; Soslow, Robert A; Abu-Rustum, Nadeem R; Hricak, Hedvig; Sala, Evis

    2017-07-01

    To investigate whether qualitative magnetic resonance (MR) features can distinguish leiomyosarcoma (LMS) from atypical leiomyoma (ALM) and assess the feasibility of texture analysis (TA). This retrospective study included 41 women (ALM = 22, LMS = 19) imaged with MRI prior to surgery. Two readers (R1, R2) evaluated each lesion for qualitative MR features. Associations between MR features and LMS were evaluated with Fisher's exact test. Accuracy measures were calculated for the four most significant features. TA was performed for 24 patients (ALM = 14, LMS = 10) with uniform imaging following lesion segmentation on axial T2-weighted images. Texture features were pre-selected using Wilcoxon signed-rank test with Bonferroni correction and analyzed with unsupervised clustering to separate LMS from ALM. Four qualitative MR features most strongly associated with LMS were nodular borders, haemorrhage, "T2 dark" area(s), and central unenhanced area(s) (p ≤ 0.0001 each feature/reader). The highest sensitivity [1.00 (95%CI:0.82-1.00)/0.95 (95%CI: 0.74-1.00)] and specificity [0.95 (95%CI:0.77-1.00)/1.00 (95%CI:0.85-1.00)] were achieved for R1/R2, respectively, when a lesion had ≥3 of these four features. Sixteen texture features differed significantly between LMS and ALM (p-values: feasible. • Four qualitative MR features demonstrated the strongest statistical association with LMS. • Combination of ≥3 these features could accurately differentiate LMS from ALM. • Texture analysis was a feasible semi-automated approach for lesion categorization.

  9. Differential Diagnosis of Cystic Lymphangioma of the Pancreas Based on Imaging Features

    Directory of Open Access Journals (Sweden)

    Ting-Kai Leung

    2006-01-01

    Full Text Available Lymphangioma is a benign tumor, which is a consequence of lymphatic malformation with blockage of lymphatic flow. Most lymphangiomas occur in the neck and axillary region, and < 1% occur in the mesentery or retroperitoneum. Lymphangiomas arising from the pancreas are extremely rare. We report the case of a 34-year-old woman with cystic lymphangioma of the pancreas without major symptoms or signs. A 6 × 6 cm intra-abdominal cystic mass was incidentally revealed by sonography during a health examination. It is always a challenge to differentiate the lesion from other possible cystic-like pancreatic neoplasms. Differential diagnosis of cystic lymphangioma from other cystic-like tumors of the pancreas can be performed based on their imaging characteristics, including presence of septa, cystic or wall calcification, soft tissue, wall thickness, single or multiple loculation, and dilatation of the pancreatic duct. Post-gadolinium magnetic resonance imaging is excellent in defining the origin of intra-abdominal cystic mass and intracystic septa.

  10. SU-D-BRA-04: Computerized Framework for Marker-Less Localization of Anatomical Feature Points in Range Images Based On Differential Geometry Features for Image-Guided Radiation Therapy

    International Nuclear Information System (INIS)

    Soufi, M; Arimura, H; Toyofuku, F; Nakamura, K; Hirose, T; Umezu, Y; Shioyama, Y

    2016-01-01

    Purpose: To propose a computerized framework for localization of anatomical feature points on the patient surface in infrared-ray based range images by using differential geometry (curvature) features. Methods: The general concept was to reconstruct the patient surface by using a mathematical modeling technique for the computation of differential geometry features that characterize the local shapes of the patient surfaces. A region of interest (ROI) was firstly extracted based on a template matching technique applied on amplitude (grayscale) images. The extracted ROI was preprocessed for reducing temporal and spatial noises by using Kalman and bilateral filters, respectively. Next, a smooth patient surface was reconstructed by using a non-uniform rational basis spline (NURBS) model. Finally, differential geometry features, i.e. the shape index and curvedness features were computed for localizing the anatomical feature points. The proposed framework was trained for optimizing shape index and curvedness thresholds and tested on range images of an anthropomorphic head phantom. The range images were acquired by an infrared ray-based time-of-flight (TOF) camera. The localization accuracy was evaluated by measuring the mean of minimum Euclidean distances (MMED) between reference (ground truth) points and the feature points localized by the proposed framework. The evaluation was performed for points localized on convex regions (e.g. apex of nose) and concave regions (e.g. nasofacial sulcus). Results: The proposed framework has localized anatomical feature points on convex and concave anatomical landmarks with MMEDs of 1.91±0.50 mm and 3.70±0.92 mm, respectively. A statistically significant difference was obtained between the feature points on the convex and concave regions (P<0.001). Conclusion: Our study has shown the feasibility of differential geometry features for localization of anatomical feature points on the patient surface in range images. The proposed

  11. SU-D-BRA-04: Computerized Framework for Marker-Less Localization of Anatomical Feature Points in Range Images Based On Differential Geometry Features for Image-Guided Radiation Therapy

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    Soufi, M; Arimura, H; Toyofuku, F [Kyushu University, Fukuoka, Fukuoka (Japan); Nakamura, K [Hamamatsu University School of Medicine, Hamamatsu, Shizuoka (Japan); Hirose, T; Umezu, Y [Kyushu University Hospital, Fukuoka, Fukuoka (Japan); Shioyama, Y [Saga Heavy Ion Medical Accelerator in Tosu, Tosu, Saga (Japan)

    2016-06-15

    Purpose: To propose a computerized framework for localization of anatomical feature points on the patient surface in infrared-ray based range images by using differential geometry (curvature) features. Methods: The general concept was to reconstruct the patient surface by using a mathematical modeling technique for the computation of differential geometry features that characterize the local shapes of the patient surfaces. A region of interest (ROI) was firstly extracted based on a template matching technique applied on amplitude (grayscale) images. The extracted ROI was preprocessed for reducing temporal and spatial noises by using Kalman and bilateral filters, respectively. Next, a smooth patient surface was reconstructed by using a non-uniform rational basis spline (NURBS) model. Finally, differential geometry features, i.e. the shape index and curvedness features were computed for localizing the anatomical feature points. The proposed framework was trained for optimizing shape index and curvedness thresholds and tested on range images of an anthropomorphic head phantom. The range images were acquired by an infrared ray-based time-of-flight (TOF) camera. The localization accuracy was evaluated by measuring the mean of minimum Euclidean distances (MMED) between reference (ground truth) points and the feature points localized by the proposed framework. The evaluation was performed for points localized on convex regions (e.g. apex of nose) and concave regions (e.g. nasofacial sulcus). Results: The proposed framework has localized anatomical feature points on convex and concave anatomical landmarks with MMEDs of 1.91±0.50 mm and 3.70±0.92 mm, respectively. A statistically significant difference was obtained between the feature points on the convex and concave regions (P<0.001). Conclusion: Our study has shown the feasibility of differential geometry features for localization of anatomical feature points on the patient surface in range images. The proposed

  12. Educational effect of a lecture on differential imaging features comparing ameloblastomas and keratocystic odontogenic tumors of the mandible presented to dental students

    International Nuclear Information System (INIS)

    Morita, Mitsuko; Ariji, Yoshiko; Kise, Yoshitaka; Goto, Masakazu; Izumi, Masahiro; Naitoh, Munetaka; Ariji, Eiichiro; Katsumata, Akitoshi

    2011-01-01

    The objective of this study was to clarify the educational effect of a lecture on differential imaging features comparing ameloblastomas and keratocystic odontogenic tumors of the mandibles presented to dental students. Panoramic and CT images of 10 ameloblastomas and 10 keratocystic odontogenic tumors were randomly presented 114 dental students. Test scores, correct answer ratios, identification index, and understanding of the imaging features contributing to a correct diagnosis were serially evaluated before and after the lecture on the differential imaging features comparing the two types of tumors. The mean and standard deviation of the scoring ratios of dental students diagnosing these lesions on panoramic and CT images were 48.8±10.8% and 52.5±12.9%, respectively. After the lecture on the differential imaging features comparing the two tumors, the scoring ratios improved significantly. After the lecture, both the numbers of patients whose images were correctly diagnosed and the identification indices increased. The lecture also increased the number of imaging features recognized as contributing to the correct diagnosis. A lecture on the differential imaging features comparing ameloblastomas and keratocystic odontogenic tumors of the mandibles contributed to the improvement of imaging diagnosis skills among dental students. (author)

  13. Abdominal tuberculosis: Imaging features

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    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.

  14. Abdominal tuberculosis: Imaging features

    International Nuclear Information System (INIS)

    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

  15. Differentiation of ductal carcinoma in situ versus fibrocystic changes by magnetic resonance imaging: are there pathognomonic imaging features?

    Science.gov (United States)

    Dietzel, Matthias; Kaiser, Clemens G; Wenkel, Evelyn; Clauser, Paola; Uder, Michael; Schulz-Wendtland, Rüdiger; Baltzer, Pascal At

    2017-10-01

    Background In breast magnetic resonance imaging (MRI), the diagnosis of ductal carcinoma in situ (DCIS) remains controversial; the most challenging cause of false-positive DCIS diagnosis is fibrocystic changes (FC). Purpose To search for typical and pathognomonic patterns of DCIS and FC using a standard clinical MRI protocol. Material and Methods Consecutive patients scheduled for breast MRI (standardized protocols @ 1.5T: dynamic-T1-GRE before/after Gd-DTPA [0.1 mmol/kg body weight (BW)]; T1-TSE), with subsequent pathological sampling, were investigated. Sixteen MRI descriptors were prospectively assessed by two experienced radiologists in consensus (blinded to pathology) and explored in patients with DCIS (n = 77) or FC (n = 219). Univariate and multivariate statistics were performed to identify the accuracy of descriptors (alone, combined). Furthermore, pathognomonic descriptor-combinations with an accuracy of 100% were explored (χ 2 statistics; decision trees). Results Six breast MRI descriptors significantly differentiated DCIS from FC ( P corrected  breast MRI and hence might help to decrease the number of unnecessary biopsies in this clinically challenging subgroup.

  16. Multispectral Image Feature Points

    Directory of Open Access Journals (Sweden)

    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.

  17. Imaging features of musculoskeletal tuberculosis

    International Nuclear Information System (INIS)

    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.)

  18. Localized scleroderma: imaging features

    International Nuclear Information System (INIS)

    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.)

  19. Localized scleroderma: imaging features

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    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.)

  20. Differentiation between malignant and benign thyroid nodules and stratification of papillary thyroid cancer with aggressive histological features: Whole-lesion diffusion-weighted imaging histogram analysis.

    Science.gov (United States)

    Hao, Yonghong; Pan, Chu; Chen, WeiWei; Li, Tao; Zhu, WenZhen; Qi, JianPin

    2016-12-01

    To explore the usefulness of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) derived from reduced field-of-view (r-FOV) diffusion-weighted imaging (DWI) in differentiating malignant and benign thyroid nodules and stratifying papillary thyroid cancer (PTC) with aggressive histological features. This Institutional Review Board-approved, retrospective study included 93 patients with 101 pathologically proven thyroid nodules. All patients underwent preoperative r-FOV DWI at 3T. The whole-lesion ADC assessments were performed for each patient. Histogram-derived ADC parameters between different subgroups (pathologic type, extrathyroidal extension, lymph node metastasis) were compared. Receiver operating characteristic curve analysis was used to determine optimal histogram parameters in differentiating benign and malignant nodules and predicting aggressiveness of PTC. Mean ADC, median ADC, 5 th percentile ADC, 25 th percentile ADC, 75 th percentile ADC, 95 th percentile ADC (all P histogram analysis might help to differentiate malignant nodules from benign ones and show the PTCs with extrathyroidal extension. J. Magn. Reson. Imaging 2016;44:1546-1555. © 2016 International Society for Magnetic Resonance in Medicine.

  1. Featured Image | Galaxy of Images

    Science.gov (United States)

    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

  2. Classification of breast masses in ultrasound images using self-adaptive differential evolution extreme learning machine and rough set feature selection.

    Science.gov (United States)

    Prabusankarlal, Kadayanallur Mahadevan; Thirumoorthy, Palanisamy; Manavalan, Radhakrishnan

    2017-04-01

    A method using rough set feature selection and extreme learning machine (ELM) whose learning strategy and hidden node parameters are optimized by self-adaptive differential evolution (SaDE) algorithm for classification of breast masses is investigated. A pathologically proven database of 140 breast ultrasound images, including 80 benign and 60 malignant, is used for this study. A fast nonlocal means algorithm is applied for speckle noise removal, and multiresolution analysis of undecimated discrete wavelet transform is used for accurate segmentation of breast lesions. A total of 34 features, including 29 textural and five morphological, are applied to a [Formula: see text]-fold cross-validation scheme, in which more relevant features are selected by quick-reduct algorithm, and the breast masses are discriminated into benign or malignant using SaDE-ELM classifier. The diagnosis accuracy of the system is assessed using parameters, such as accuracy (Ac), sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV), Matthew's correlation coefficient (MCC), and area ([Formula: see text]) under receiver operating characteristics curve. The performance of the proposed system is also compared with other classifiers, such as support vector machine and ELM. The results indicated that the proposed SaDE algorithm has superior performance with [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] compared to other classifiers.

  3. Imaging features of thalassemia

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    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.)

  4. Imaging features of thalassemia

    International Nuclear Information System (INIS)

    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.)

  5. Pulmonary vasculitis: imaging features

    International Nuclear Information System (INIS)

    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

  6. Imaging features of aggressive angiomyxoma

    International Nuclear Information System (INIS)

    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

  7. Renal angiomyoadenomatous tumour: Imaging features

    Science.gov (United States)

    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

  8. Imaging features of kaposiform lymphangiomatosis

    International Nuclear Information System (INIS)

    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.)

  9. Textural features for image classification

    Science.gov (United States)

    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.

  10. Differential magnetic force microscope imaging.

    Science.gov (United States)

    Wang, Ying; Wang, Zuobin; Liu, Jinyun; Hou, Liwei

    2015-01-01

    This paper presents a method for differential magnetic force microscope imaging based on a two-pass scanning procedure to extract differential magnetic forces and eliminate or significantly reduce background forces with reversed tip magnetization. In the work, the difference of two scanned images with reversed tip magnetization was used to express the local magnetic forces. The magnetic sample was first scanned with a low lift distance between the MFM tip and the sample surface, and the magnetization direction of the probe was then changed after the first scan to perform the second scan. The differential magnetic force image was obtained through the subtraction of the two images from the two scans. The theoretical and experimental results have shown that the proposed method for differential magnetic force microscope imaging is able to reduce the effect of background or environment interference forces, and offers an improved image contrast and signal to noise ratio (SNR). © Wiley Periodicals, Inc.

  11. Intramural hemorrhage of the thoracic aorta - imaging features and differential diagnosis; Das intramurale Haematom der thorakalen Aorta: Bildgebende Diagnostik und Differentialdiagnose

    Energy Technology Data Exchange (ETDEWEB)

    Sommer, T. [Bonn Univ. (Germany) Radiologische Klinik; Abu-Ramadan, D. [Bonn Univ. (Germany). Klinik fuer Herz- und Gefaesschirurgie; Busch, M. [Bonn Univ. (Germany) Radiologische Klinik; Bierhoff, E. [Bonn Univ. (Germany). Pathologische Inst.; Kreft, B. [Bonn Univ. (Germany) Radiologische Klinik; Kuhl, C. [Bonn Univ. (Germany) Radiologische Klinik; Lutterbey, G. [Bonn Univ. (Germany) Radiologische Klinik; Keller, E. [Bonn Univ. (Germany) Radiologische Klinik; Schild, H. [Bonn Univ. (Germany) Radiologische Klinik

    1996-09-01

    Purpose: Aortic wall thickening due to intramural hemorrhage may be the only sign of aortic dissection. The aim of this study was to evaluate the incidence, imaging features and differential diagnoses of intramural hemorrhage (IMH) of the thoracic aorta. Methods: 98 patients with clinically suspected aortic dissection were investigated via Spiral-CT and MRT. Diagnosis of IMH based on the presence of smooth crescentic or concentric wall thickening over a longer segment of the thoracic aorta without flow visualization and without compression or distortion of the aortic lumen. Results: 69 patients had classic aortic dissections and 7 patients were diagnosed to have IMH of the thoracic aorta. One patient with IMH of the ascending aorta died of aortic rupture and subsequent pericardial tamponade 12 hours after onset of symptoms. In one patient with IMH of the descending aorta on initial examination, there was a progression of overt aortic dissection at follow-up after three weeks. In two patients with IMH of the descending aorta, wall thickening decreased in size at follow-up (10-15 weeks), whereas in one patient it remained unchanged. Conclusion: IMH of the aorta should be considered a precursor of aortic dissection. At follow-up IMH may decrease in size, rupture or progress to overt aortic dissection. (orig.) [Deutsch] Ziel: Eine aortale Wandverdichtung als Ausdruck eines intramuralen Haematoms kann die einzige Manifestation einer Aortendissektion sein. Ziel dieser Arbeit war die Evaluierung der Inzidenz, bildgebenden Aspekte und Differentialdiagnosen dieses in der deutschsprachigen Literatur wenig bekannten Krankheitsbildes. Methode: 98 Patienten mit klinischem Verdacht auf eine Aortendissektion wurden MR- und computertomographisch untersucht. Kriterium fuer das Vorliegen eines intramuralen Haematoms war der Nachweis einer laengerstreckigen aortalen Wandverdickung ohne Flussnachweis sowie ohne Konfigurationsaenderung des aortalen Lumens. Ergebnisse: 69 Patienten

  12. Textural features for radar image analysis

    Science.gov (United States)

    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.

  13. Average Gait Differential Image Based Human Recognition

    Directory of Open Access Journals (Sweden)

    Jinyan Chen

    2014-01-01

    Full Text Available The difference between adjacent frames of human walking contains useful information for human gait identification. Based on the previous idea a silhouettes difference based human gait recognition method named as average gait differential image (AGDI is proposed in this paper. The AGDI is generated by the accumulation of the silhouettes difference between adjacent frames. The advantage of this method lies in that as a feature image it can preserve both the kinetic and static information of walking. Comparing to gait energy image (GEI, AGDI is more fit to representation the variation of silhouettes during walking. Two-dimensional principal component analysis (2DPCA is used to extract features from the AGDI. Experiments on CASIA dataset show that AGDI has better identification and verification performance than GEI. Comparing to PCA, 2DPCA is a more efficient and less memory storage consumption feature extraction method in gait based recognition.

  14. Perinatal clinical and imaging features of CLOVES syndrome

    Energy Technology Data Exchange (ETDEWEB)

    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.)

  15. Imaging features of cardiac myxoma

    International Nuclear Information System (INIS)

    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)

  16. Differential morphology and image processing.

    Science.gov (United States)

    Maragos, P

    1996-01-01

    Image processing via mathematical morphology has traditionally used geometry to intuitively understand morphological signal operators and set or lattice algebra to analyze them in the space domain. We provide a unified view and analytic tools for morphological image processing that is based on ideas from differential calculus and dynamical systems. This includes ideas on using partial differential or difference equations (PDEs) to model distance propagation or nonlinear multiscale processes in images. We briefly review some nonlinear difference equations that implement discrete distance transforms and relate them to numerical solutions of the eikonal equation of optics. We also review some nonlinear PDEs that model the evolution of multiscale morphological operators and use morphological derivatives. Among the new ideas presented, we develop some general 2-D max/min-sum difference equations that model the space dynamics of 2-D morphological systems (including the distance computations) and some nonlinear signal transforms, called slope transforms, that can analyze these systems in a transform domain in ways conceptually similar to the application of Fourier transforms to linear systems. Thus, distance transforms are shown to be bandpass slope filters. We view the analysis of the multiscale morphological PDEs and of the eikonal PDE solved via weighted distance transforms as a unified area in nonlinear image processing, which we call differential morphology, and briefly discuss its potential applications to image processing and computer vision.

  17. Magnetic Resonance Imaging Features of Neuromyelitis Optica

    Energy Technology Data Exchange (ETDEWEB)

    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.

  18. Magnetic Resonance Imaging Features of Neuromyelitis Optica

    International Nuclear Information System (INIS)

    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.

  19. Identifying Image Manipulation Software from Image Features

    Science.gov (United States)

    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

  20. Hypothesis testing for differentially correlated features.

    Science.gov (United States)

    Sheng, Elisa; Witten, Daniela; Zhou, Xiao-Hua

    2016-10-01

    In a multivariate setting, we consider the task of identifying features whose correlations with the other features differ across conditions. Such correlation shifts may occur independently of mean shifts, or differences in the means of the individual features across conditions. Previous approaches for detecting correlation shifts consider features simultaneously, by computing a correlation-based test statistic for each feature. However, since correlations involve two features, such approaches do not lend themselves to identifying which feature is the culprit. In this article, we instead consider a serial testing approach, by comparing columns of the sample correlation matrix across two conditions, and removing one feature at a time. Our method provides a novel perspective and favorable empirical results compared with competing approaches. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  1. Solving jigsaw puzzles using image features

    DEFF Research Database (Denmark)

    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...

  2. Wilson’s disease: Atypical imaging features

    Directory of Open Access Journals (Sweden)

    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.

  3. Image fusion using sparse overcomplete feature dictionaries

    Science.gov (United States)

    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.

  4. Infrared image enhancement with learned features

    Science.gov (United States)

    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.

  5. Imaging features of iliopsoas bursitis

    Energy Technology Data Exchange (ETDEWEB)

    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.)

  6. Imaging features of iliopsoas bursitis

    International Nuclear Information System (INIS)

    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.)

  7. Feature hashing for fast image retrieval

    Science.gov (United States)

    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.

  8. Featured Image: Simulating Planetary Gaps

    Science.gov (United States)

    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

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

    Science.gov (United States)

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

    Science.gov (United States)

    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.

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

    African Journals Online (AJOL)

    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 ...

  12. MR imaging features of hydrocephalus

    International Nuclear Information System (INIS)

    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

  13. Saliency image of feature building for image quality assessment

    Science.gov (United States)

    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.

  14. Primary Neuroendocrine Tumor of the Breast: Imaging Features

    International Nuclear Information System (INIS)

    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

  15. MR imaging features of craniodiaphyseal dysplasia

    Energy Technology Data Exchange (ETDEWEB)

    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.)

  16. Feature Detector and Descriptor for Medical Images

    Science.gov (United States)

    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.

  17. Field application of feature-enhanced imaging

    International Nuclear Information System (INIS)

    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

  18. [Differential features of DRG 541 readmitting patients].

    Science.gov (United States)

    López Pérez, J; López Álvarez, J; Montero Ruiz, E

    2015-01-01

    Hospital readmission is considered an adverse outcome, and the hospital readmission ratio is an indicator of health care quality. Published studies show a wide variability and heterogeneity, with large groups of patients with different diagnoses and prognoses. The aim of the study was to analyse the differences between patients readmitted and those who were not, in patients grouped into the diagnosis related group (DRG) 541. A retrospective observational study was conducted on DRG 541 patients discharged in 2010. Readmission is defined as any admission into any hospital department, and for any reason at ≤30 days from discharge. An analysis was performed that included age, sex, day of discharge, month of discharge, number of diagnoses and drugs at discharge, respiratory depressant drugs, length of stay, requests for consultations/referrals, Charlson comorbidity index, feeding method, hospitalisations in the previous 6 months, albumin and haemoglobin levels and medical examinations within 30 days after discharge. Of the 985 patients included in the study, 189 were readmitted. On multivariate analysis, significant variables were: Haemoglobin -0.6g/dl (95% confidence interval [95%CI] -0.9 to -0.3), gastrostomy feeding odds ratio (OR) 5.6 (95%CI: 1.5 to 21.6), hospitalisations in previous 6 months OR 1.9 (95%CI: 1.3 to 2.8), visits to emergency department OR 17.4 (95%CI: 11.3 to 26.8), medical checks after discharge OR 0.4 (95%CI: 0.2 to 0.8). DRG 541 readmitting patients have some distinctive features that could allow early detection and prevent hospital readmission. Copyright © 2015 SECA. Published by Elsevier Espana. All rights reserved.

  19. Hemorrhage detection in MRI brain images using images features

    Science.gov (United States)

    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.

  20. Imaging features of benign adrenal cysts

    International Nuclear Information System (INIS)

    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

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  2. Remote Sensing Image Registration Using Multiple Image Features

    Directory of Open Access Journals (Sweden)

    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.

  3. Autoimmune Thyroiditis: Clinical Course Features and Principles of Differential Therapy

    Directory of Open Access Journals (Sweden)

    L.Ye. Bobyryova

    2014-02-01

    Full Text Available Constant increase in the incidence of autoimmune thyroiditis (AIT in different regions of Ukraine puts this problem in actual number that determines the need to identify features of the clinical course of AIT, the principles of differentiated treatment depending on the nature of the metabolic changes and taking into account regional differences in thyroid pathology, particularly AIT. The paper presents data on the study of features of clinical course and complex treatment of AIT.

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

    LENUS (Irish Health Repository)

    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.

  5. Featured Image: Diamonds in a Meteorite

    Science.gov (United States)

    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

  6. Special feature on imaging systems and techniques

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  8. Imaging features of juxtacortical chondroma in children

    International Nuclear Information System (INIS)

    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.)

  9. Imaging features of juxtacortical chondroma in children

    Energy Technology Data Exchange (ETDEWEB)

    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.)

  10. Determination of the Image Complexity Feature in Pattern Recognition

    Directory of Open Access Journals (Sweden)

    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.

  11. Imaging differential polarization microscope with electronic readout

    International Nuclear Information System (INIS)

    Mickols, W.; Tinoco, I.; Katz, J.E.; Maestre, M.F.; Bustamante, C.

    1985-01-01

    A differential polarization microscope forms two images: one of the transmitted intensity and the other due to the change in intensity between images formed when different polarizations of light are used. The interpretation of these images for linear dichroism and circular dichroism are described. The design constraints on the data acquisition systems and the polarization modulation are described. The advantage of imaging several biological systems which contain optically anisotropic structures are described

  12. MR imaging features of hemispherical spondylosclerosis

    Energy Technology Data Exchange (ETDEWEB)

    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.)

  13. Mass-like extramedullary hematopoiesis: imaging features

    Energy Technology Data Exchange (ETDEWEB)

    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.)

  14. Molecular biological features of male germ cell differentiation

    Science.gov (United States)

    HIROSE, MIKA; TOKUHIRO, KEIZO; TAINAKA, HITOSHI; MIYAGAWA, YASUSHI; TSUJIMURA, AKIRA; OKUYAMA, AKIHIKO; NISHIMUNE, YOSHITAKE

    2007-01-01

    Somatic cell differentiation is required throughout the life of a multicellular organism to maintain homeostasis. In contrast, germ cells have only one specific function; to preserve the species by conveying the parental genes to the next generation. Recent studies of the development and molecular biology of the male germ cell have identified many genes, or isoforms, that are specifically expressed in the male germ cell. In the present review, we consider the unique features of male germ cell differentiation. (Reprod Med Biol 2007; 6: 1–9) PMID:29699260

  15. Imaging features of foot osteoid osteoma

    Energy Technology Data Exchange (ETDEWEB)

    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.)

  16. Feature extraction & image processing for computer vision

    CERN Document Server

    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

  17. Hybridizing Differential Evolution with a Genetic Algorithm for Color Image Segmentation

    Directory of Open Access Journals (Sweden)

    R. V. V. Krishna

    2016-10-01

    Full Text Available This paper proposes a hybrid of differential evolution and genetic algorithms to solve the color image segmentation problem. Clustering based color image segmentation algorithms segment an image by clustering the features of color and texture, thereby obtaining accurate prototype cluster centers. In the proposed algorithm, the color features are obtained using the homogeneity model. A new texture feature named Power Law Descriptor (PLD which is a modification of Weber Local Descriptor (WLD is proposed and further used as a texture feature for clustering. Genetic algorithms are competent in handling binary variables, while differential evolution on the other hand is more efficient in handling real parameters. The obtained texture feature is binary in nature and the color feature is a real value, which suits very well the hybrid cluster center optimization problem in image segmentation. Thus in the proposed algorithm, the optimum texture feature centers are evolved using genetic algorithms, whereas the optimum color feature centers are evolved using differential evolution.

  18. Imaging features of intracranial solitary fibrous tumors

    International Nuclear Information System (INIS)

    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)

  19. Unsupervised feature learning for autonomous rock image classification

    Science.gov (United States)

    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.

  20. MR imaging features of the congenital uterine anomalies

    International Nuclear Information System (INIS)

    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

  1. Imaging features of breast echinococcus granulosus

    International Nuclear Information System (INIS)

    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)

  2. Featured Image: Bright Dots in a Sunspot

    Science.gov (United States)

    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

  3. Imaging features of colovesical fistulae on MRI.

    Science.gov (United States)

    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.

  4. MR imaging features of spindle cell lipoma

    Energy Technology Data Exchange (ETDEWEB)

    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

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

    Institute of Scientific and Technical Information of China (English)

    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.

  6. Differentiation of Solid Renal Tumors with Multiparametric MR Imaging.

    Science.gov (United States)

    Lopes Vendrami, Camila; Parada Villavicencio, Carolina; DeJulio, Todd J; Chatterjee, Argha; Casalino, David D; Horowitz, Jeanne M; Oberlin, Daniel T; Yang, Guang-Yu; Nikolaidis, Paul; Miller, Frank H

    2017-01-01

    Characterization of renal tumors is critical to determine the best therapeutic approach and improve overall patient survival. Because of increased use of high-resolution cross-sectional imaging in clinical practice, renal masses are being discovered with increased frequency. As a result, accurate imaging characterization of these lesions is more important than ever. However, because of the wide array of imaging features encountered as well as overlapping characteristics, identifying reliable imaging criteria for differentiating malignant from benign renal masses remains a challenge. Multiparametric magnetic resonance (MR) imaging based on various anatomic and functional parameters has an important role and adds diagnostic value in detection and characterization of renal masses. MR imaging may allow distinction of benign solid renal masses from several renal cell carcinoma (RCC) subtypes, potentially suggest the histologic grade of a neoplasm, and play an important role in ensuring appropriate patient management to avoid unnecessary surgery or other interventions. It is also a useful noninvasive imaging tool for patients who undergo active surveillance of renal masses and for follow-up after treatment of a renal mass. The purpose of this article is to review the characteristic MR imaging features of RCC and common benign renal masses and propose a diagnostic imaging approach to evaluation of solid renal masses using multiparametric MR imaging. © RSNA, 2017.

  7. Can magnetic resonance imaging differentiate undifferentiated arthritis?

    DEFF Research Database (Denmark)

    Østergaard, Mikkel; Duer, Anne; Hørslev-Petersen, K

    2005-01-01

    A high sensitivity for the detection of inflammatory and destructive changes in inflammatory joint diseases makes magnetic resonance imaging potentially useful for assigning specific diagnoses, such as rheumatoid arthritis and psoriatic arthritis in arthritides, that remain undifferentiated after...... conventional clinical, biochemical and radiographic examinations. With recent data as the starting point, the present paper describes the current knowledge on magnetic resonance imaging in the differential diagnosis of undifferentiated arthritis....

  8. Systematic Review and Meta-Analysis of CT Features for Differentiating Complicated and Uncomplicated Appendicitis.

    Science.gov (United States)

    Kim, Hae Young; Park, Ji Hoon; Lee, Yoon Jin; Lee, Sung Soo; Jeon, Jong-June; Lee, Kyoung Ho

    2018-04-01

    Purpose To perform a systematic review and meta-analysis to identify computed tomographic (CT) features for differentiating complicated appendicitis in patients suspected of having appendicitis and to summarize their diagnostic accuracy. Materials and Methods Studies on diagnostic accuracy of CT features for differentiating complicated appendicitis (perforated or gangrenous appendicitis) in patients suspected of having appendicitis were searched in Ovid-MEDLINE, EMBASE, and the Cochrane Library. Overlapping descriptors used in different studies to denote the same image finding were subsumed under a single CT feature. Pooled diagnostic accuracy of the CT features was calculated by using a bivariate random effects model. CT features with pooled diagnostic odds ratios with 95% confidence intervals not including 1 were considered as informative. Results Twenty-three studies were included, and 184 overlapping descriptors for various CT findings were subsumed under 14 features. Of these, 10 features were informative for complicated appendicitis. There was a general tendency for these features to show relatively high specificity but low sensitivity. Extraluminal appendicolith, abscess, appendiceal wall enhancement defect, extraluminal air, ileus, periappendiceal fluid collection, ascites, intraluminal air, and intraluminal appendicolith showed pooled specificity greater than 70% (range, 74%-100%), but sensitivity was limited (range, 14%-59%). Periappendiceal fat stranding was the only feature that showed high sensitivity (94%; 95% confidence interval: 86%, 98%) but low specificity (40%; 95% confidence interval, 23%, 60%). Conclusion Ten informative CT features for differentiating complicated appendicitis were identified in this study, nine of which showed high specificity, but low sensitivity. © RSNA, 2017 Online supplemental material is available for this article.

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

    Directory of Open Access Journals (Sweden)

    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.

  10. Imaging strategy in differentiated thyroid cancer

    NARCIS (Netherlands)

    Phan, Thi Thanh Ha

    2007-01-01

    This thesis focuses on clinical dilemmas, which the clinician faces in the management of patients with differentiated thyroid cancer (DTC) with a specific emphasis on the role of current and new diagnostic imaging. Thyroid cancer is a rare disease, but it is the most common endocrine malignancy of

  11. Fingerprint image enhancement by differential hysteresis processing.

    Science.gov (United States)

    Blotta, Eduardo; Moler, Emilce

    2004-05-10

    A new method to enhance defective fingerprints images through image digital processing tools is presented in this work. When the fingerprints have been taken without any care, blurred and in some cases mostly illegible, as in the case presented here, their classification and comparison becomes nearly impossible. A combination of spatial domain filters, including a technique called differential hysteresis processing (DHP), is applied to improve these kind of images. This set of filtering methods proved to be satisfactory in a wide range of cases by uncovering hidden details that helped to identify persons. Dactyloscopy experts from Policia Federal Argentina and the EAAF have validated these results.

  12. An Effective Combined Feature For Web Based Image Retrieval

    Directory of Open Access Journals (Sweden)

    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

  13. Image feature detectors and descriptors foundations and applications

    CERN Document Server

    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. .

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  16. Differentiation of Glioblastoma and Lymphoma Using Feature Extraction and Support Vector Machine.

    Science.gov (United States)

    Yang, Zhangjing; Feng, Piaopiao; Wen, Tian; Wan, Minghua; Hong, Xunning

    2017-01-01

    Differentiation of glioblastoma multiformes (GBMs) and lymphomas using multi-sequence magnetic resonance imaging (MRI) is an important task that is valuable for treatment planning. However, this task is a challenge because GBMs and lymphomas may have a similar appearance in MRI images. This similarity may lead to misclassification and could affect the treatment results. In this paper, we propose a semi-automatic method based on multi-sequence MRI to differentiate these two types of brain tumors. Our method consists of three steps: 1) the key slice is selected from 3D MRIs and region of interests (ROIs) are drawn around the tumor region; 2) different features are extracted based on prior clinical knowledge and validated using a t-test; and 3) features that are helpful for classification are used to build an original feature vector and a support vector machine is applied to perform classification. In total, 58 GBM cases and 37 lymphoma cases are used to validate our method. A leave-one-out crossvalidation strategy is adopted in our experiments. The global accuracy of our method was determined as 96.84%, which indicates that our method is effective for the differentiation of GBM and lymphoma and can be applied in clinical diagnosis. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  17. Feature coding for image representation and recognition

    CERN Document Server

    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

  18. HLA-G Haplotypes Are Differentially Associated with Asthmatic Features

    Directory of Open Access Journals (Sweden)

    Camille Ribeyre

    2018-02-01

    Full Text Available Human leukocyte antigen (HLA-G, a HLA class Ib molecule, interacts with receptors on lymphocytes such as T cells, B cells, and natural killer cells to influence immune responses. Unlike classical HLA molecules, HLA-G expression is not found on all somatic cells, but restricted to tissue sites, including human bronchial epithelium cells (HBEC. Individual variation in HLA-G expression is linked to its genetic polymorphism and has been associated with many pathological situations such as asthma, which is characterized by epithelium abnormalities and inflammatory cell activation. Studies reported both higher and equivalent soluble HLA-G (sHLA-G expression in different cohorts of asthmatic patients. In particular, we recently described impaired local expression of HLA-G and abnormal profiles for alternatively spliced isoforms in HBEC from asthmatic patients. sHLA-G dosage is challenging because of its many levels of polymorphism (dimerization, association with β2-microglobulin, and alternative splicing, thus many clinical studies focused on HLA-G single-nucleotide polymorphisms as predictive biomarkers, but few analyzed HLA-G haplotypes. Here, we aimed to characterize HLA-G haplotypes and describe their association with asthmatic clinical features and sHLA-G peripheral expression and to describe variations in transcription factor (TF binding sites and alternative splicing sites. HLA-G haplotypes were differentially distributed in 330 healthy and 580 asthmatic individuals. Furthermore, HLA-G haplotypes were associated with asthmatic clinical features showed. However, we did not confirm an association between sHLA-G and genetic, biological, or clinical parameters. HLA-G haplotypes were phylogenetically split into distinct groups, with each group displaying particular variations in TF binding or RNA splicing sites that could reflect differential HLA-G qualitative or quantitative expression, with tissue-dependent specificities. Our results, based on a

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

    International Nuclear Information System (INIS)

    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.)

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

    International Nuclear Information System (INIS)

    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.)

  1. MRI features in differentiation borderline from benign mucinous ovarian cystadenoma

    International Nuclear Information System (INIS)

    Zhao Shuhui; Qiang Jinwei; Zhang Guofu; Qiu Haiying; Wang Xuezhen; Wang Li

    2012-01-01

    Objective: To investigate MRI features for differentiating borderline from benign mucinous cystadenoma (MC) of the ovary. Methods: Twenty three patients with 23 benign MCs and 19 patients with 20 borderline mucinous cystadenomas (BMC)proven by surgery and pathology underwent MRI, with 23 benign MCs and 20 BMC. MRI features of tumor were evaluated and compared between two groups including location, shape, size, loculation, signal intensity of the fluid, thickness of septa and wall, and vegetations. The findings were correlated with those of pathology. The loculation, the signal intensity of the intracystic content, the thickness of the septation and the wall, and the vegetations between the benign MCs and the BMCs were compared using the Chi-square test.Results Homogenous low signal on T 1 WI and homogenous high signal on T 2 WI were the main signal patterns of benign MC seen more commonly in benign MC (18/23 and 17/23, respectively) than in BMC (5/20 and 8/20, respectively) (χ 2 =12.1979, 5.0553; P<0.05). The honeycomb loculi, high signal on T 1 WI, low signal on T 2 WI, thickened septa or wall (≥5 mm), and vegetations (≥5 mm) were significantly more common in BMC (10/20, 9/20, 8/20, 10/20 and 14/20, respectively) than in benign MC(4/23, 3/23, 1/23, 1/23 and 1/23, respectively) (χ 2 =5.1804, 5.4300, 8.2163, 11.7113 and 20.2990, P<0.05), with the sensitivity and specificity for characterizing BMC of 50.0% and 82.6%, 45.0% and 87.0%, 40.0% and 95.7%, 50.0% and 95.7%, and 70.0% and 95.7%, respectively. When one of honeycomb loculi with low signal on T 2 WI, thickened septa or wall (≥5 mm), and vegetations (≥5 mm) were found, the sensitivity, specificity and accuracy for characterizing BMC were 90.0%, 91.3% and 90.7% respectively. Conclusion: MRI is accurate for demonstrating morphological features of ovarian MC which well correlated to pathological characteristics, and for differentiating BMC from benign MC, thus helpful for making surgery strategy. (authors)

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

    Energy Technology Data Exchange (ETDEWEB)

    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.)

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

    International Nuclear Information System (INIS)

    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.)

  4. Featured Image: Revealing Hidden Objects with Color

    Science.gov (United States)

    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. Superpixel-Based Feature for Aerial Image Scene Recognition

    Directory of Open Access Journals (Sweden)

    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.

  6. Imaging features of diffuse pulmonary hemorrhage

    International Nuclear Information System (INIS)

    Schmit, M.; Vogel, W.; Horger, M.

    2006-01-01

    There are diverse etiologies of diffuse pulmonary hemorrhage, so specific diagnosis may be difficult. Conventional radiography tends to be misleading as hemoptysis may lacking in patients with hemorrhagic anemia. Diffuse pulmonary hemorrhage should be differentiated from focal pulmonary hemorrhage resulting from chronic bronchitis, bronchiectasis, active infection (tuberculosis) neoplasia, trauma, or embolism. (orig.)

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

    International Nuclear Information System (INIS)

    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

  8. Iris recognition based on key image feature extraction.

    Science.gov (United States)

    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.

  9. Multimodality imaging features of hereditary multiple exostoses

    OpenAIRE

    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...

  10. What are the differentiating clinical and MRI-features of enchondromas from low-grade chondrosarcomas?

    Energy Technology Data Exchange (ETDEWEB)

    Douis, Hassan [Royal Orthopaedic Hospital, Department of Radiology, Birmingham (United Kingdom); University Hospital Birmingham, Department of Radiology, Birmingham (United Kingdom); Parry, M. [Royal Orthopaedic Hospital, Department of Orthopaedic Oncology, Birmingham (United Kingdom); Vaiyapuri, S. [Royal Orthopaedic Hospital, Department of Musculoskeletal Pathology, Birmingham (United Kingdom); Davies, A.M. [Royal Orthopaedic Hospital, Department of Radiology, Birmingham (United Kingdom)

    2018-01-15

    To evaluate the role of clinical assessment, conventional and dynamic contrast-enhanced MRI in differentiating enchondromas from chondrosarcomas of long bone. The following clinical and MRI findings were assessed: age, gender, pain, pain attributable to lesion, tumour location, tumour length, presence, depth of endosteal scalloping, bone marrow oedema, soft tissue oedema, cortical destruction, periosteal reaction, bone expansion, macroscopic fat, calcification, soft tissue mass, haemorrhage, dynamic contrast-enhanced MRI. Clinical and MRI findings were compared with histopathological grading. Sixty patients with central chondroid tumours were included (27 enchondromas, 10 cartilaginous lesions of unknown malignant potential, 15 grade 1 chondrosarcomas, 8 high-grade chondrosarcomas). Pain attributed to lesion, tumour length, endosteal scalloping > 2/3, cortical destruction, bone expansion and soft tissue mass were differentiating features between enchondromas and grade 1 chondrosarcomas. Dynamic contrast-enhanced MRI could not differentiate enchondromas from grade 1 chondrosarcomas. Previously reported imaging signs of chondrosarcomas are useful in the diagnosis of grade 1 lesions but have lower sensitivity than in higher grade lesions. Deep endosteal scalloping is the most sensitive imaging sign of grade 1 chondrosarcomas. Pain due to the lesion is an important clinical sign of grade 1 chondrosarcomas. Dynamic contrast-enhanced MRI is not useful in differentiating enchondromas from grade 1 chondrosarcomas. (orig.)

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

    Science.gov (United States)

    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

  12. Prototype Theory Based Feature Representation for PolSAR Images

    OpenAIRE

    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...

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  15. Adapting Local Features for Face Detection in Thermal Image

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  17. Rosai-Dorfman Disease with Epidural and Spinal Bone Marrow Involvement: Magnetic Resonance Imaging and Diffusion-Weighted Imaging Features

    International Nuclear Information System (INIS)

    Oner, A.Y.; Akpek, S.; Tali, T.

    2007-01-01

    Sinus histiocytosis with massive lymphadenopathy (SHML), or Rosai-Dorfman disease, is a rare histiocytic disorder that typically presents with chronic, self-limiting cervical lymphadenopathy. Although this disease mainly affects histiocytes, there are a few reports of bone marrow infiltration. Diffusion-weighted imaging (DWI) is a promising technology in differentiating between various bone marrow pathologies. We here present conventional magnetic resonance imaging and DWI features of a patient with SHML and bone marrow involvement

  18. Rosai-Dorfman Disease with Epidural and Spinal Bone Marrow Involvement: Magnetic Resonance Imaging and Diffusion-Weighted Imaging Features

    Energy Technology Data Exchange (ETDEWEB)

    Oner, A.Y.; Akpek, S.; Tali, T. [Dept. of Radiology, Gazi Univ. School of Medicine. Besevler-Ankara (Turkey)

    2007-04-15

    Sinus histiocytosis with massive lymphadenopathy (SHML), or Rosai-Dorfman disease, is a rare histiocytic disorder that typically presents with chronic, self-limiting cervical lymphadenopathy. Although this disease mainly affects histiocytes, there are a few reports of bone marrow infiltration. Diffusion-weighted imaging (DWI) is a promising technology in differentiating between various bone marrow pathologies. We here present conventional magnetic resonance imaging and DWI features of a patient with SHML and bone marrow involvement.

  19. [Feature extraction for breast cancer data based on geometric algebra theory and feature selection using differential evolution].

    Science.gov (United States)

    Li, Jing; Hong, Wenxue

    2014-12-01

    The feature extraction and feature selection are the important issues in pattern recognition. Based on the geometric algebra representation of vector, a new feature extraction method using blade coefficient of geometric algebra was proposed in this study. At the same time, an improved differential evolution (DE) feature selection method was proposed to solve the elevated high dimension issue. The simple linear discriminant analysis was used as the classifier. The result of the 10-fold cross-validation (10 CV) classification of public breast cancer biomedical dataset was more than 96% and proved superior to that of the original features and traditional feature extraction method.

  20. Learning Hierarchical Feature Extractors for Image Recognition

    Science.gov (United States)

    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

  1. Ewing sarcoma versus osteomyelitis: differential diagnosis with magnetic resonance imaging

    International Nuclear Information System (INIS)

    Henninger, B.; Glodny, B.; Rudisch, A.; Trieb, T.; Loizides, A.; Judmaier, W.; Schocke, M.F.; Putzer, D.

    2013-01-01

    To find and evaluate characteristic magnetic resonance imaging (MRI) patterns for the differentiation between Ewing sarcoma and osteomyelitis. We identified 28 consecutive patients referred to our department for MRI (1.5 T) of an unclear bone lesion with clinical symptoms suggestive of Ewing sarcoma or osteomyelitis. MRI scans were re-evaluated by two experienced radiologists, typical MR imaging features were documented and a diagnostic decision between Ewing sarcoma and osteomyelitis was made. Statistical significance of the association between MRI features and the biopsy-based diagnosis was assessed using Fisher's exact test. The most clear-cut pattern for determining the correct diagnosis was the presence of a sharp and defined margin of the bone lesion, which was found in all patients with Ewing sarcoma, but in none of the patients with osteomyelitis (P < 0.0001). Contrast enhancing soft tissue was present in all cases with Ewing sarcoma and absent in 4 patients with osteomyelitis (P = 0.0103). Cortical destruction was found in all patients with Ewing sarcoma, 4 patients with osteomyelitis did not present any cortical reaction (P = 0.0103). Cystic or necrotic areas were identified in 13 patients with Ewing sarcoma and in 1 patient with osteomyelitis (P = 0.004). Interobserver reliability was very good (kappa = 1) in Ewing sarcoma and moderate (kappa = 0.6) in patients with osteomyelitis. A sharp and defined margin, optimally visualized on T1-weighted images in comparison to short tau inversion recovery (STIR) images, is the most significant feature of Ewing sarcoma in differentiating from osteomyelitis. (orig.)

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

    International Nuclear Information System (INIS)

    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

  3. An efficient approach for differentiating Alzheimer's disease from normal elderly based on multicenter MRI using gray-level invariant features.

    Directory of Open Access Journals (Sweden)

    Muwei Li

    Full Text Available Machine learning techniques, along with imaging markers extracted from structural magnetic resonance images, have been shown to increase the accuracy to differentiate patients with Alzheimer's disease (AD from normal elderly controls. Several forms of anatomical features, such as cortical volume, shape, and thickness, have demonstrated discriminative capability. These approaches rely on accurate non-linear image transformation, which could invite several nuisance factors, such as dependency on transformation parameters and the degree of anatomical abnormality, and an unpredictable influence of residual registration errors. In this study, we tested a simple method to extract disease-related anatomical features, which is suitable for initial stratification of the heterogeneous patient populations often encountered in clinical data. The method employed gray-level invariant features, which were extracted from linearly transformed images, to characterize AD-specific anatomical features. The intensity information from a disease-specific spatial masking, which was linearly registered to each patient, was used to capture the anatomical features. We implemented a two-step feature selection for anatomic recognition. First, a statistic-based feature selection was implemented to extract AD-related anatomical features while excluding non-significant features. Then, seven knowledge-based ROIs were used to capture the local discriminative powers of selected voxels within areas that were sensitive to AD or mild cognitive impairment (MCI. The discriminative capability of the proposed feature was measured by its performance in differentiating AD or MCI from normal elderly controls (NC using a support vector machine. The statistic-based feature selection, together with the knowledge-based masks, provided a promising solution for capturing anatomical features of the brain efficiently. For the analysis of clinical populations, which are inherently heterogeneous

  4. Featured Image: Identifying a Glowing Shell

    Science.gov (United States)

    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

  5. Robust Image Hashing Using Radon Transform and Invariant Features

    Directory of Open Access Journals (Sweden)

    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.

  6. MR Imaging Features of Fibrocystic Change of the Breast

    Science.gov (United States)

    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

  7. Can CT and MR Shape and Textural Features Differentiate Benign Versus Malignant Pleural Lesions?

    Science.gov (United States)

    Pena, Elena; Ojiaku, MacArinze; Inacio, Joao R; Gupta, Ashish; Macdonald, D Blair; Shabana, Wael; Seely, Jean M; Rybicki, Frank J; Dennie, Carole; Thornhill, Rebecca E

    2017-10-01

    The study aimed to identify a radiomic approach based on CT and or magnetic resonance (MR) features (shape and texture) that may help differentiate benign versus malignant pleural lesions, and to assess if the radiomic model may improve confidence and accuracy of radiologists with different subspecialty backgrounds. Twenty-nine patients with pleural lesions studied on both contrast-enhanced CT and MR imaging were reviewed retrospectively. Three texture and three shape features were extracted. Combinations of features were used to generate logistic regression models using histopathology as outcome. Two thoracic and two abdominal radiologists evaluated their degree of confidence in malignancy. Diagnostic accuracy of radiologists was determined using contingency tables. Cohen's kappa coefficient was used to assess inter-reader agreement. Using optimal threshold criteria, sensitivity, specificity, and accuracy of each feature and combination of features were obtained and compared to the accuracy and confidence of radiologists. The CT model that best discriminated malignant from benign lesions revealed an AUC CT  = 0.92 ± 0.05 (P textural and shape analysis may help distinguish malignant from benign lesions. A radiomics-based approach may increase diagnostic confidence of abdominal radiologists on CT and MR and may potentially improve radiologists' accuracy in the assessment of pleural lesions characterized by MR. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

  8. Features Selection for Skin Micro-Image Symptomatic Recognition

    Institute of Scientific and Technical Information of China (English)

    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.

  9. Features Selection for Skin Micro-Image Symptomatic Recognition

    Institute of Scientific and Technical Information of China (English)

    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.

  10. CT imaging features of anaplastic thyroid carcinoma

    International Nuclear Information System (INIS)

    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)

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

    Directory of Open Access Journals (Sweden)

    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.

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

    International Nuclear Information System (INIS)

    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

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

    Directory of Open Access Journals (Sweden)

    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.

  14. Breast image feature learning with adaptive deconvolutional networks

    Science.gov (United States)

    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).

  15. The analysis of image feature robustness using cometcloud

    Directory of Open Access Journals (Sweden)

    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.

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

    DEFF Research Database (Denmark)

    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...

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

    Science.gov (United States)

    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.

  18. Image feature extraction based on the camouflage effectiveness evaluation

    Science.gov (United States)

    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.

  19. Featured Image: Orbiting Stars Share an Envelope

    Science.gov (United States)

    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

  20. Featured Image: Making Dust in the Lab

    Science.gov (United States)

    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

  1. CT and MR imaging features of hydrocephalus

    International Nuclear Information System (INIS)

    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

  2. Smart Images Search based on Visual Features Fusion

    International Nuclear Information System (INIS)

    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

  3. Disorders of the pediatric pancreas: imaging features

    International Nuclear Information System (INIS)

    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.)

  4. Disorders of the pediatric pancreas: imaging features

    Energy Technology Data Exchange (ETDEWEB)

    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.)

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

    Science.gov (United States)

    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

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

  9. SAR Image Classification Based on Its Texture Features

    Institute of Scientific and Technical Information of China (English)

    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.

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

    CSIR Research Space (South Africa)

    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...

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  13. Neural Differentiation of Lexico-Syntactic Categories or Semantic Features?

    NARCIS (Netherlands)

    Kellenbach, ML; Wijers, AA; Hovius, M; Mulder, Juul; Mulder, Gysbertus

    2002-01-01

    Event-related potentials (ERPs) were used to investigate whether processing differences between nouns and verbs can be accounted for by the differential salience of visual-perceptual and motor attributes in their semantic specifications. Three subclasses of nouns and verbs were selected, which

  14. Online Feature Selection for Classifying Emphysema in HRCT Images

    Directory of Open Access Journals (Sweden)

    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.

  15. Image Recommendation Algorithm Using Feature-Based Collaborative Filtering

    Science.gov (United States)

    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.

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

    International Nuclear Information System (INIS)

    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)

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

    Science.gov (United States)

    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.

  18. Simultenious binary hash and features learning for image retrieval

    Science.gov (United States)

    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.

  19. Imaging appearance of well-differentiated liposarcomas with myxoid stroma.

    Science.gov (United States)

    Morag, Yoav; Yablon, Corrie; Brigido, Monica Kalume; Jacobson, Jon; Lucas, David

    2018-04-16

    Describe the imaging appearance of well-differentiated liposarcoma with myxoid stroma (WDLMS) and correlate with histopathology. A keyword search of the institution medical records was performed from 1 January 2000 to 30 June 2017. The histopathology slides of cases identified in this fashion were then reviewed by a pathologist. Additional cases were prospectively collected from extramural referrals and tumor boards. Diagnostic imaging studies of pathologically proven cases of WDLMS were then reviewed in consensus and correlated with pathology. Ten cases of pathologically proven WDLMS were identified (7 men, 3 women, ages 26-81). Tumor location included the retroperitoneum (n = 5), thigh (n = 4), and the shin (n = 1). Nine patients had macroscopic fat on imaging. The nonlipomatous components had a variable appearance, including septal, nodular, and lacelike patterns. Two cases included two distinct areas that were predominantly myxoid or lipomatous ("bi-morphic"). One tumor had no macroscopic fat on imaging. On CT, the nonlipomatous nodular components were hypodense/had hypodense areas. On MRI, the nodular components had intermediate/bright T2W signal. Interval nonlipomatous nodular growth was identified in 3 cases. WDLMS may present on imaging as a mass with variable morphology and amounts of nonlipomatous components. Histopathological diagnosis of WDLMS is challenging and imaging correlation may be helpful, as this tumor may have ≥50% fatty volume, may have a myxoid nodular component or bi-morphic appearance, or may be located in the retroperitoneum, features that are unusual for myxoid liposarcoma. WDLMS with a nodular component cannot be distinguished from dedifferentiated liposarcoma based on imaging alone.

  20. Value of MR imaging in the differentiation of benign and malignant orbital tumors in adults

    International Nuclear Information System (INIS)

    Xian, Junfang; Zhang, Zhengyu; Wang, Zhenchang; Li, Jing; Yang, Bentao; Man, Fengyuan; Chang, Qinglin; Zhang, Yunting

    2010-01-01

    To prospectively evaluate magnetic resonance (MR) imaging including dynamic contrast-enhanced MR imaging in the differentiation of benign from malignant orbital masses and to evaluate which MR imaging features are most predictive of malignant tumors. The study was approved by the institutional review board and signed informed consent was obtained. Nonenhanced, static, and dynamic contrast-enhanced MR imaging was performed in 102 adult patients with an orbital mass. Diagnosis was based on histologic findings. MR imaging features of benign and malignant orbital lesions were evaluated correlated with histological findings. Multivariate logistic regression analysis was employed to identify the best combination of MR imaging features that might be predictive of malignancy. Nonenhanced, static, and dynamic enhancement MR imaging was significantly superior to two other models in prediction of malignancy (p < 0.05). Multivariate logistic regression analysis identified that the most discriminating MR imaging features were isointense mass on T2-weighted imaging and a washout-type time-intensity curve for both observers. Nonenhanced, static, and dynamic enhancement MR imaging improved differentiation between benign and malignant orbital masses in adult patients. (orig.)

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

    Science.gov (United States)

    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.

  2. Improved image retrieval based on fuzzy colour feature vector

    Science.gov (United States)

    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.

  3. HDR IMAGING FOR FEATURE DETECTION ON DETAILED ARCHITECTURAL SCENES

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

  8. Granulocytic sarcoma presenting with necrotic cervical lymph nodes as an initial manifestation of childhood leukaemia: imaging features

    Energy Technology Data Exchange (ETDEWEB)

    An, Sang Bu; Cheon, Jung-Eun; Kim, In-One; Kim, Woo Sun [Seoul National University College of Medicine, Department of Radiology, Seoul (Korea); Seoul National University Medical Research Center, Institute of Radiation Medicine, Seoul (Korea); Ahn, Hyo Seop; Shin, Hee Young; Kang, Hyoung Jin; Yeon, Kyung Mo [Seoul National University College of Medicine, Department of Pediatrics, Cancer Research Institute, Seoul (Korea)

    2008-06-15

    We present two cases of granulocytic sarcoma of the cervical lymph nodes with central necrosis as an initial manifestation of childhood leukaemia, focusing on the imaging features. Recognition of the CT and MR imaging findings of granulocytic sarcoma involving the cervical lymph nodes assists the differential diagnosis of noninfective lymphadenopathy in children. (orig.)

  9. Skull base chordoid meningioma: Imaging features and pathology

    International Nuclear Information System (INIS)

    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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  12. Imaging features of maxillary osteoblastoma and its malignant transformation

    International Nuclear Information System (INIS)

    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.)

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

    Directory of Open Access Journals (Sweden)

    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.

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

    International Nuclear Information System (INIS)

    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

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

    International Nuclear Information System (INIS)

    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)

  16. Hyperspectral image classifier based on beach spectral feature

    International Nuclear Information System (INIS)

    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

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

    Directory of Open Access Journals (Sweden)

    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.

  18. Clinical Features and Differential Diagnoses in Laryngeal Mucoepidermoid Carcinoma

    OpenAIRE

    Mokhtari, Sepideh; Mokhtari, Saeedeh

    2011-01-01

    Mucoepidermoid carcinoma is the most common malignant tumor of salivary glands. However, it is a rare entity in larynx. Laryngeal cases are frequently misdiagnosed with other malignancies and they are under-reported. So, recognizing the clinical and histological features of this tumor is essential. Laryngeal mucoepidermoid carcinoma can arise in supraglottis, glottis and subglottis. Generally, it presents as a submucosal mass; therefore, progressive symptoms without any identifiable lesion in...

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

    International Nuclear Information System (INIS)

    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

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  3. Diffusion-weighted imaging features in spinal cord infarction

    International Nuclear Information System (INIS)

    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

  4. Differential Diagnosis of Patients with Inconclusive Parkinsonian Features Using [{sup 18}F]FP-CIT PET/CT

    Energy Technology Data Exchange (ETDEWEB)

    Park, Eunkyung; Hwang, Yu Mi; Lee, Channyoung; Oh, Sun Young; Kim, Young Chul; Choe, Jae Gol; Park, Kun Woo [Korea Univ., Seoul (Korea, Republic of); Kim, Sujin [Seoul National Univ. College of Medicine, Seoul (Korea, Republic of)

    2014-06-15

    It is often difficult to differentiate parkinsonism, especially when patients show uncertain parkinsonian features. We investigated the usefulness of dopamine transporter (DAT) imaging for the differential diagnosis of inconclusive parkinsonism using [{sup 18}F]FP-CIT PET. Twenty-four patients with inconclusive parkinsonian features at initial clinical evaluation and nine healthy controls were studied. Patients consisted of three subgroups: nine patients whose diagnoses were unclear concerning whether they had idiopathic Parkinson's disease or drug-induced parkinsonism ('PD/DIP'), nine patients who fulfilled neither the diagnostic criteria of PD nor of essential tremor ('PD/ET'), and six patients who were alleged to have either PD or atypical parkinsonian syndrome ('PD/APS'). Brain PET images were obtained 120 min after injection of 185 MBq [{sup 18}F]FP-CIT. Imaging results were quantified and compared with follow-up clinical diagnoses. Overall, 11 of 24 patients demonstrated abnormally decreased DAT availability on the PET scans, whereas 13 were normal. PET results could diagnose PD/DIP and PD/ET patients as having PD in six patients, DIP in seven, and ET in five; however, the diagnoses of all six PD/APS patients remained inconclusive. Among 15 patients who obtained a final follow-up diagnosis, the image-based diagnosis was congruent with the follow-up diagnosis in 11 patients. Four unsolved cases had normal DAT availability, but clinically progressed to PD during the follow-up period. [{sup 18}F]FP-CIT PET imaging is useful in the differential diagnosis of patients with inconclusive parkinsonian features, except in patients who show atypical features or who eventually progress to PD.

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

    International Nuclear Information System (INIS)

    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

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

    Energy Technology Data Exchange (ETDEWEB)

    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

  7. Tracking image features with PCA-SURF descriptors

    CSIR Research Space (South Africa)

    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...

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

    International Nuclear Information System (INIS)

    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

  9. Adaptive Colour Feature Identification in Image for Object Tracking

    Directory of Open Access Journals (Sweden)

    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.

  10. Feature extraction from mammographic images using fast marching methods

    International Nuclear Information System (INIS)

    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

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  14. Quantitative phase imaging and differential interference contrast imaging for biological TEM

    International Nuclear Information System (INIS)

    Allman, B.E.; McMahon, P.J.; Barone-Nugent, E.D.; Nugent, E.D.

    2002-01-01

    Full text: Phase microscopy is a central technique in science. An experienced microscopist uses this effect to visualise (edge) structure within transparent samples by slightly defocusing the microscope. Although widespread in optical microscopy, phase contrast transmission electron microscopy (TEM) has not been widely adopted. TEM for biological specimens has largely relied on staining techniques to yield sufficient contrast. We show here a simple method for quantitative TEM phase microscopy that quantifies this phase contrast effect. Starting with conventional, digital, bright field images of the sample, our algorithm provides quantitative phase information independent of the sample's bright field intensity image. We present TEM phase images of a range of stained and unstained, biological and material science specimens. This independent phase and intensity information is then used to emulate a range of phase visualisation images familiar to optical microscopy, e.g. differential interference contrast. The phase images contain features not visible with the other imaging modalities. Further, if the TEM samples have been prepared on a microtome to a uniform thickness, the phase information can be converted into refractive index structure of the specimen. Copyright (2002) Australian Society for Electron Microscopy Inc

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  17. Comparative imaging features of brucellar and tuberculous spondylitis

    International Nuclear Information System (INIS)

    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

  18. Differential CT features of infectious pneumonia versus bronchioloalveolar carcinoma (BAC) mimicking pneumonia

    International Nuclear Information System (INIS)

    Kim, Tae Hoon; Kim, Sang Jin; Ryu, Young Hoon; Chung, Soo Yoon; Seo, Jae Seung; Kim, Young Jin; Choi, Byoung Wook; Lee, Sun Hwa; Cho, Sang Ho

    2006-01-01

    The purpose of this study was to evaluate retrospectively the differential CT features of bronchioloalveolar carcinoma (BAC) mimicking pneumonia and infectious pneumonia at the lung periphery. CT images were reviewed in 47 patients with focal areas of parenchymal opacification at the lung periphery. We evaluated the presence of ground-glass attenuation, marginal conspicuity of the lesion, CT angiogram sign, air-bronchogram sign, a bubble-like low-attenuation area within the lesion, presence of pleural thickening and retraction associated with the lesion, presence of pleural effusion and extra-pleural fatty hypertrophy, presence of bronchial wall thickening proximal to the lesion, and air-trapping in the normal lung near the lesion. BAC (n=18) depicted the presence of a bubble-like low-attenuation area within the lesion, whereas infectious pneumonia (n=29) represented the pleural thickening associated with the lesion and bronchial wall thickening proximal to the lesion (P 0.05). The focal areas of the parenchymal opacification on the CT images may suggest infectious pneumonia rather than BAC when they show bronchial wall thickening proximal to the lesion and pleural thickening associated with the lesion, whereas BAC is characterized as the presence of a bubble-like low attenuation area within the tumor. (orig.)

  19. Differential CT features of infectious pneumonia versus bronchioloalveolar carcinoma (BAC) mimicking pneumonia

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Tae Hoon [Yonsei University College of Medicine, Department of Radiology, Seoul (Korea); Yongdong Severance Hospital, Department of Radiology, Seoul (Korea); Kim, Sang Jin; Ryu, Young Hoon; Chung, Soo Yoon; Seo, Jae Seung; Kim, Young Jin; Choi, Byoung Wook [Yonsei University College of Medicine, Department of Radiology, Seoul (Korea); Lee, Sun Hwa [NeoDin Medical Institute, Department of Clinical Pathology, Seoul (Korea); Cho, Sang Ho [Yonsei University College of Medicine, Department of Pathology, Seoul (Korea)

    2006-08-15

    The purpose of this study was to evaluate retrospectively the differential CT features of bronchioloalveolar carcinoma (BAC) mimicking pneumonia and infectious pneumonia at the lung periphery. CT images were reviewed in 47 patients with focal areas of parenchymal opacification at the lung periphery. We evaluated the presence of ground-glass attenuation, marginal conspicuity of the lesion, CT angiogram sign, air-bronchogram sign, a bubble-like low-attenuation area within the lesion, presence of pleural thickening and retraction associated with the lesion, presence of pleural effusion and extra-pleural fatty hypertrophy, presence of bronchial wall thickening proximal to the lesion, and air-trapping in the normal lung near the lesion. BAC (n=18) depicted the presence of a bubble-like low-attenuation area within the lesion, whereas infectious pneumonia (n=29) represented the pleural thickening associated with the lesion and bronchial wall thickening proximal to the lesion (P<0.05). The other CT findings showed no significant differences (P>0.05). The focal areas of the parenchymal opacification on the CT images may suggest infectious pneumonia rather than BAC when they show bronchial wall thickening proximal to the lesion and pleural thickening associated with the lesion, whereas BAC is characterized as the presence of a bubble-like low attenuation area within the tumor. (orig.)

  20. Ability of FDG PET and CT radiomics features to differentiate between primary and metastatic lung lesions.

    Science.gov (United States)

    Kirienko, Margarita; Cozzi, Luca; Rossi, Alexia; Voulaz, Emanuele; Antunovic, Lidija; Fogliata, Antonella; Chiti, Arturo; Sollini, Martina

    2018-04-06

    To evaluate the ability of CT and PET radiomics features to classify lung lesions as primary or metastatic, and secondly to differentiate histological subtypes of primary lung cancers. A cohort of 534 patients with lung lesions were retrospectively studied. Radiomics texture features were extracted using the LIFEx package from semiautomatically segmented PET and CT images. Histology data were recorded in all patients. The patient cohort was divided into a training and a validation group and linear discriminant analysis (LDA) was performed to classify the lesions using both direct and backward stepwise methods. The robustness of the procedure was tested by repeating the entire process 100 times with different assignments to the training and validation groups. Scoring metrics included analysis of the receiver operating characteristic curves in terms of area under the curve (AUC), sensitivity, specificity and accuracy. Radiomics features extracted from CT and PET datasets were able to differentiate primary tumours from metastases in both the training and the validation group (AUCs 0.79 ± 0.03 and 0.70 ± 0.04, respectively, from the CT dataset; AUCs 0.92 ± 0.01 and 0.91 ± 0.03, respectively, from the PET dataset). The AUC cut-off thresholds identified by LDA using direct and backward elimination strategies were -0.79 ± 0.06 and -0.81 ± 0.08, respectively (CT dataset) and -0.69 ± 0.05 and -0.68 ± 0.04, respectively (PET dataset). For differentiation between primary subgroups based on CT features, the AUCs in the training and validation groups were 0.81 ± 0.02 and 0.69 ± 0.04 for adenocarcinoma (Adc) vs. squamous cell carcinoma (Sqc) or "Other", 0.85 ± 0.02 and 0.70 ± 0.05 for Sqc vs. Adc or Other, and 0.77 ± 0.03 and 0.57 ± 0.05 for Other vs. Adc or Sqc. The same analyses for the PET data revealed AUCs of 0.90 ± 0.10 and 0.80 ± 0.04, 0.80 ± 0.02 and 0.61 ± 0.06, and 0.97 ± 0

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

    Directory of Open Access Journals (Sweden)

    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.

  2. Cervical spine injury in the elderly: imaging features

    Energy Technology Data Exchange (ETDEWEB)

    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.)

  3. FRACTAL IMAGE FEATURE VECTORS WITH APPLICATIONS IN FRACTOGRAPHY

    Directory of Open Access Journals (Sweden)

    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.

  4. Multi-spectral endogenous fluorescence imaging for bacterial differentiation

    Science.gov (United States)

    Chernomyrdin, Nikita V.; Babayants, Margarita V.; Korotkov, Oleg V.; Kudrin, Konstantin G.; Rimskaya, Elena N.; Shikunova, Irina A.; Kurlov, Vladimir N.; Cherkasova, Olga P.; Komandin, Gennady A.; Reshetov, Igor V.; Zaytsev, Kirill I.

    2017-07-01

    In this paper, the multi-spectral endogenous fluorescence imaging was implemented for bacterial differentiation. The fluorescence imaging was performed using a digital camera equipped with a set of visual bandpass filters. Narrowband 365 nm ultraviolet radiation passed through a beam homogenizer was used to excite the sample fluorescence. In order to increase a signal-to-noise ratio and suppress a non-fluorescence background in images, the intensity of the UV excitation was modulated using a mechanical chopper. The principal components were introduced for differentiating the samples of bacteria based on the multi-spectral endogenous fluorescence images.

  5. Effect of zooming on texture features of ultrasonic images

    Directory of Open Access Journals (Sweden)

    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.

  6. Research of image retrieval technology based on color feature

    Science.gov (United States)

    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

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

    International Nuclear Information System (INIS)

    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)

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

    Energy Technology Data Exchange (ETDEWEB)

    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)

  9. Genetic algorithms for thyroid gland ultrasound image feature reduction

    Czech Academy of Sciences Publication Activity Database

    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

  10. Associations between spondyloarthritis features and magnetic resonance imaging findings

    DEFF Research Database (Denmark)

    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...

  11. Clinical features and 123I-FP-CIT SPECT imaging in drug-induced parkinsonism and Parkinson's disease

    International Nuclear Information System (INIS)

    Diaz-Corrales, Francisco J.; Escobar-Delgado, Teresa; Sanz-Viedma, Salome; Garcia-Solis, David; Mir, Pablo

    2010-01-01

    To determine clinical predictors and accuracy of 123 I-FP-CIT SPECT imaging in the differentiation of drug-induced parkinsonism (DIP) and Parkinson's disease (PD). Several clinical features and 123 I-FP-CIT SPECT images in 32 patients with DIP, 25 patients with PD unmasked by antidopaminergic drugs (PDu) and 22 patients with PD without a previous history of antidopaminergic treatment (PDc) were retrospectively evaluated. DIP and PD shared all clinical features except symmetry of parkinsonian signs which was more frequently observed in patients with DIP (46.9%) than in patients with PDu (16.0%, p 123 I-FP-CIT SPECT images were normal in 29 patients with DIP (90.6%) and abnormal in all patients with PD, and this imaging technique showed high levels of accuracy. DIP and PD are difficult to differentiate based on clinical signs. The precision of clinical diagnosis could be reliably enhanced by 123 I-FP-CIT SPECT imaging. (orig.)

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

    Science.gov (United States)

    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.

  13. 3D shape recovery from image focus using Gabor features

    Science.gov (United States)

    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.

  14. Unusual acute encephalitis involving the thalamus: imaging features

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    Institute of Scientific and Technical Information of China (English)

    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.

  16. Multispectral image feature fusion for detecting land mines

    Energy Technology Data Exchange (ETDEWEB)

    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.

  17. CFA-aware features for steganalysis of color images

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    International Nuclear Information System (INIS)

    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

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  1. Comparison on imaging features of central serous chorioretinopathy fundus

    Directory of Open Access Journals (Sweden)

    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.

  2. Lipofibromatosis: magnetic resonance imaging features and pathological correlation in three cases

    International Nuclear Information System (INIS)

    Vogel, Daniela; Righi, Alberto; Kreshak, Jennifer; Dei Tos, Angelo Paolo; Merlino, Biagio; Brunocilla, Eugenio; Vanel, Daniel

    2014-01-01

    Lipofibromatosis is a rare, benign, but infiltrative, soft tissue tumor seen in children. We present three cases of lipofibromatosis, each with different magnetic resonance imaging features and correlate this with the histological findings. The patients comprised two males and one female who presented in infancy; at birth, 5 months, and 7 months of age. Clinically, the masses were painless and slow-growing. The masses ranged in size from 2 to 6 cm and involved the distal extremities in two cases (one foot, one wrist) and the trunk. Magnetic resonance imaging showed lipomatous lesions with varying amounts of adipose and solid components in each case. There were no capsules at the periphery of the lesions. One case showed a fat-predominant lesion, another an equal mixture of fat and solid tissue, and the third was predominantly solid. This was reflected in the histology, which showed corresponding features. Radiological and histopathological differential diagnoses are reviewed. (orig.)

  3. Lipofibromatosis: magnetic resonance imaging features and pathological correlation in three cases

    Energy Technology Data Exchange (ETDEWEB)

    Vogel, Daniela; Righi, Alberto; Kreshak, Jennifer; Dei Tos, Angelo Paolo [Istituto Ortopedico Rizzoli, Bologna (Italy); Merlino, Biagio [Universita Cattolica del Sacro Cuore Policlinico ' ' A. Gemelli' ' , Dipartimento di Scienze Radiologiche, Roma (Italy); Brunocilla, Eugenio [U.O. di UROLOGIA, Dipartimento di Medicina Specialistica, Diagnostica e Sperimentale, Bologna (Italy); Vanel, Daniel [Istituto Ortopedico Rizzoli, Anatomia Patologica, Bologna (Italy)

    2014-05-15

    Lipofibromatosis is a rare, benign, but infiltrative, soft tissue tumor seen in children. We present three cases of lipofibromatosis, each with different magnetic resonance imaging features and correlate this with the histological findings. The patients comprised two males and one female who presented in infancy; at birth, 5 months, and 7 months of age. Clinically, the masses were painless and slow-growing. The masses ranged in size from 2 to 6 cm and involved the distal extremities in two cases (one foot, one wrist) and the trunk. Magnetic resonance imaging showed lipomatous lesions with varying amounts of adipose and solid components in each case. There were no capsules at the periphery of the lesions. One case showed a fat-predominant lesion, another an equal mixture of fat and solid tissue, and the third was predominantly solid. This was reflected in the histology, which showed corresponding features. Radiological and histopathological differential diagnoses are reviewed. (orig.)

  4. CT imaging and histopathological features of renal epithelioid angiomyolipomas

    International Nuclear Information System (INIS)

    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.

  5. Collaborative Tracking of Image Features Based on Projective Invariance

    Science.gov (United States)

    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

  6. Fourier domain image fusion for differential X-ray phase-contrast breast imaging

    International Nuclear Information System (INIS)

    Coello, Eduardo; Sperl, Jonathan I.; Bequé, Dirk; Benz, Tobias; Scherer, Kai; Herzen, Julia; Sztrókay-Gaul, Anikó; Hellerhoff, Karin; Pfeiffer, Franz; Cozzini, Cristina; Grandl, Susanne

    2017-01-01

    X-Ray Phase-Contrast (XPC) imaging is a novel technology with a great potential for applications in clinical practice, with breast imaging being of special interest. This work introduces an intuitive methodology to combine and visualize relevant diagnostic features, present in the X-ray attenuation, phase shift and scattering information retrieved in XPC imaging, using a Fourier domain fusion algorithm. The method allows to present complementary information from the three acquired signals in one single image, minimizing the noise component and maintaining visual similarity to a conventional X-ray image, but with noticeable enhancement in diagnostic features, details and resolution. Radiologists experienced in mammography applied the image fusion method to XPC measurements of mastectomy samples and evaluated the feature content of each input and the fused image. This assessment validated that the combination of all the relevant diagnostic features, contained in the XPC images, was present in the fused image as well.

  7. Fourier domain image fusion for differential X-ray phase-contrast breast imaging

    Energy Technology Data Exchange (ETDEWEB)

    Coello, Eduardo, E-mail: eduardo.coello@tum.de [GE Global Research, Garching (Germany); Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality, Institut für Informatik, Technische Universität München, Garching (Germany); Sperl, Jonathan I.; Bequé, Dirk [GE Global Research, Garching (Germany); Benz, Tobias [Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality, Institut für Informatik, Technische Universität München, Garching (Germany); Scherer, Kai; Herzen, Julia [Lehrstuhl für Biomedizinische Physik, Physik-Department & Institut für Medizintechnik, Technische Universität München, Garching (Germany); Sztrókay-Gaul, Anikó; Hellerhoff, Karin [Institute for Clinical Radiology, Ludwig-Maximilians-University Hospital, Munich (Germany); Pfeiffer, Franz [Lehrstuhl für Biomedizinische Physik, Physik-Department & Institut für Medizintechnik, Technische Universität München, Garching (Germany); Cozzini, Cristina [GE Global Research, Garching (Germany); Grandl, Susanne [Institute for Clinical Radiology, Ludwig-Maximilians-University Hospital, Munich (Germany)

    2017-04-15

    X-Ray Phase-Contrast (XPC) imaging is a novel technology with a great potential for applications in clinical practice, with breast imaging being of special interest. This work introduces an intuitive methodology to combine and visualize relevant diagnostic features, present in the X-ray attenuation, phase shift and scattering information retrieved in XPC imaging, using a Fourier domain fusion algorithm. The method allows to present complementary information from the three acquired signals in one single image, minimizing the noise component and maintaining visual similarity to a conventional X-ray image, but with noticeable enhancement in diagnostic features, details and resolution. Radiologists experienced in mammography applied the image fusion method to XPC measurements of mastectomy samples and evaluated the feature content of each input and the fused image. This assessment validated that the combination of all the relevant diagnostic features, contained in the XPC images, was present in the fused image as well.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  10. Analysis and classification of commercial ham slice images using directional fractal dimension features.

    Science.gov (United States)

    Mendoza, Fernando; Valous, Nektarios A; Allen, Paul; Kenny, Tony A; Ward, Paddy; Sun, Da-Wen

    2009-02-01

    This paper presents a novel and non-destructive approach to the appearance characterization and classification of commercial pork, turkey and chicken ham slices. Ham slice images were modelled using directional fractal (DF(0°;45°;90°;135°)) dimensions and a minimum distance classifier was adopted to perform the classification task. Also, the role of different colour spaces and the resolution level of the images on DF analysis were investigated. This approach was applied to 480 wafer thin ham slices from four types of hams (120 slices per type): i.e., pork (cooked and smoked), turkey (smoked) and chicken (roasted). DF features were extracted from digitalized intensity images in greyscale, and R, G, B, L(∗), a(∗), b(∗), H, S, and V colour components for three image resolution levels (100%, 50%, and 25%). Simulation results show that in spite of the complexity and high variability in colour and texture appearance, the modelling of ham slice images with DF dimensions allows the capture of differentiating textural features between the four commercial ham types. Independent DF features entail better discrimination than that using the average of four directions. However, DF dimensions reveal a high sensitivity to colour channel, orientation and image resolution for the fractal analysis. The classification accuracy using six DF dimension features (a(90°)(∗),a(135°)(∗),H(0°),H(45°),S(0°),H(90°)) was 93.9% for training data and 82.2% for testing data.

  11. Breast cancer mitosis detection in histopathological images with spatial feature extraction

    Science.gov (United States)

    Albayrak, Abdülkadir; Bilgin, Gökhan

    2013-12-01

    In this work, cellular mitosis detection in histopathological images has been investigated. Mitosis detection is very expensive and time consuming process. Development of digital imaging in pathology has enabled reasonable and effective solution to this problem. Segmentation of digital images provides easier analysis of cell structures in histopathological data. To differentiate normal and mitotic cells in histopathological images, feature extraction step is very crucial step for the system accuracy. A mitotic cell has more distinctive textural dissimilarities than the other normal cells. Hence, it is important to incorporate spatial information in feature extraction or in post-processing steps. As a main part of this study, Haralick texture descriptor has been proposed with different spatial window sizes in RGB and La*b* color spaces. So, spatial dependencies of normal and mitotic cellular pixels can be evaluated within different pixel neighborhoods. Extracted features are compared with various sample sizes by Support Vector Machines using k-fold cross validation method. According to the represented results, it has been shown that separation accuracy on mitotic and non-mitotic cellular pixels gets better with the increasing size of spatial window.

  12. MR imaging features and staging of neuroendocrine carcinomas of the uterine cervix with pathological correlations

    Energy Technology Data Exchange (ETDEWEB)

    Duan, Xiaohui; Zhang, Xiang; Hu, Huijun; Li, Guozhao; Wang, Dongye; Zhang, Fang; Shen, Jun [Sun Yat-Sen University, Department of Radiology, Sun Yat-Sen Memorial Hospital, Guangzhou (China); Ban, Xiaohua [Sun Yat-Sen University, Medical Imaging and Minimally Invasive Interventional Center and State Key Laboratory of Oncology in Southern China, Cancer Center, Guangzhou, Guangdong (China); Wang, Charles Qian [Sun Yat-Sen University, Department of Radiology, Sun Yat-Sen Memorial Hospital, Guangzhou (China); University of New South Wales, JMO, Westmead Hospital, Sydney (Australia)

    2016-12-15

    To determine MR imaging features and staging accuracy of neuroendocrine carcinomas (NECs) of the uterine cervix with pathological correlations. Twenty-six patients with histologically proven NECs, 60 patients with squamous cell carcinomas (SCCs), and 30 patients with adenocarcinomas of the uterine cervix were included. The clinical data, pathological findings, and MRI findings were reviewed retrospectively. MRI features of cervical NECs, SCCs, and adenocarcinomas were compared, and MRI staging of cervical NECs was compared with the pathological staging. Cervical NECs showed a higher tendency toward a homogeneous signal intensity on T2-weighted imaging and a homogeneous enhancement pattern, as well as a lower ADC value of tumour and a higher incidence of lymphadenopathy, compared with SCCs and adenocarcinomas (P < 0.05). An ADC value cutoff of 0.90 x 10{sup -3} mm{sup 2}/s was robust for differentiation between cervical NECs and other cervical cancers, with a sensitivity of 63.3 % and a specificity of 95 %. In 21 patients who underwent radical hysterectomy and lymphadenectomy, the overall accuracy of tumour staging by MR imaging was 85.7 % with reference to pathology staging. Homogeneous lesion texture and low ADC value are likely suggestive features of cervical NECs and MR imaging is reliable for the staging of cervical NECs. (orig.)

  13. Mutual information based feature selection for medical image retrieval

    Science.gov (United States)

    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.

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

    International Nuclear Information System (INIS)

    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

  15. Infective endocarditis: the specific features of its course, the criteria for diagnosis, differential diagnosis (part II

    Directory of Open Access Journals (Sweden)

    B S Belov

    2008-01-01

    Full Text Available Infective endocarditis (IE is today characterized by polyetiology due to a wide range of pathogens. The paper describes the specific features of the clinical picture of the disease in relation to the etiological agent, which have, in some cases, a crucial role in the choice of empiric antibiotic therapy. Significant clinical polymorphism, obscure symptoms, and monosyndromic onset as guises all enhance the importance of the differential diagnosis of IE, at its early stages in particular. Basic approaches to differentiating IE from the diseases in which differentially diagnostic problems arise to the utmost are outlined.

  16. MR imaging features of chronically torn anterior cruciate ligament

    International Nuclear Information System (INIS)

    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)

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

    Science.gov (United States)

    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.

  18. Featured Image: New Detail in the Toothbrush Cluster

    Science.gov (United States)

    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

  19. Wavelength calibration of imaging spectrometer using atmospheric absorption features

    Science.gov (United States)

    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.

  20. Analysis of muscle fatigue conditions using time-frequency images and GLCM features

    Directory of Open Access Journals (Sweden)

    Karthick P.A.

    2016-09-01

    Full Text Available In this work, an attempt has been made to differentiate muscle non-fatigue and fatigue conditions using sEMG signals and texture representation of the time-frequency images. The sEMG signals are recorded from the biceps brachii muscle of 25 healthy adult volunteers during dynamic fatiguing contraction. The first and last curls of these signals are considered as the non-fatigue and fatigue zones, respectively. These signals are preprocessed and the time-frequency spectrum is computed using short time fourier transform (STFT. Gray-Level Co-occurrence Matrix (GLCM is extracted from low (15–45 Hz, medium (46–95 Hz and high (96–150 Hz frequency bands of the time-frequency images. Further, the features such as contrast, correlation, energy and homogeneity are calculated from the resultant matrices. The results show that the high frequency band based features are able to differentiate non-fatigue and fatigue conditions. The features such as correlation, contrast and homogeneity extracted at angles 0°, 45°, 90°, and 135° are found to be distinct with high statistical significance (p < 0.0001. Hence, this framework can be used for analysis of neuromuscular disorders.

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

    Energy Technology Data Exchange (ETDEWEB)

    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

  2. Differentiating emotional responses to images and words

    DEFF Research Database (Denmark)

    Jensen, Camilla Birgitte Falk; Petersen, Michael Kai; Larsen, Jakob Eg

    responses are characterized by only small voltage changes that have typically been found in group studies involving multiple trials and large numbers of participants. Hypothesizing that spatial filtering might enhance retrieval, we apply independent component analysis (ICA) to cluster scalp maps and time...... series responses in a single subject based on only a few trials. Comparing our results against previous findings we identify multiple early and late ICA components that are similarly modulated by neutral, pleasant and unpleasant content in both images and words. Suggesting that we might be able to model...

  3. Clinicopathological and imaging features of lipoastrocytoma: Case report.

    Science.gov (United States)

    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.

  4. Low dose reconstruction algorithm for differential phase contrast imaging.

    Science.gov (United States)

    Wang, Zhentian; Huang, Zhifeng; Zhang, Li; Chen, Zhiqiang; Kang, Kejun; Yin, Hongxia; Wang, Zhenchang; Marco, Stampanoni

    2011-01-01

    Differential phase contrast imaging computed tomography (DPCI-CT) is a novel x-ray inspection method to reconstruct the distribution of refraction index rather than the attenuation coefficient in weakly absorbing samples. In this paper, we propose an iterative reconstruction algorithm for DPCI-CT which benefits from the new compressed sensing theory. We first realize a differential algebraic reconstruction technique (DART) by discretizing the projection process of the differential phase contrast imaging into a linear partial derivative matrix. In this way the compressed sensing reconstruction problem of DPCI reconstruction can be transformed to a resolved problem in the transmission imaging CT. Our algorithm has the potential to reconstruct the refraction index distribution of the sample from highly undersampled projection data. Thus it can significantly reduce the dose and inspection time. The proposed algorithm has been validated by numerical simulations and actual experiments.

  5. Iterative feature refinement for accurate undersampled MR image reconstruction

    Science.gov (United States)

    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.

  6. Iterative feature refinement for accurate undersampled MR image reconstruction

    International Nuclear Information System (INIS)

    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)

  7. Clinical feature and imaging findings of juvenile ankylosing spondylitis

    International Nuclear Information System (INIS)

    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

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

    International Nuclear Information System (INIS)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  10. 3-D repositioning and differential images of volumetric CT measurements

    International Nuclear Information System (INIS)

    Muench, B.; Rueegsegger, P.

    1993-01-01

    In quantitative computed tomography (QCT), time serial measurements are performed to detect a global bone density loss or to identify localized bone density changes. A prerequisite for an unambiguous analysis is the comparison of identical bone volumes. Usually, manual repositioning is too coarse. The authors therefore developed a mathematical procedure that allows matching two three-dimensional image volumes. The algorithm is based on correlation techniques. The procedure has been optimized and applied to computer-tomographic 3-D images of the human knee. It has been tested with both artificially created and in vivo measured image data. Furthermore, typical results of differential images calculated from real bone measurements are presented

  11. Susceptibility weighted imaging: differentiating between calcification and hemosiderin

    Energy Technology Data Exchange (ETDEWEB)

    Barbosa, Jeam Haroldo Oliveira; Salmon, Carlos Ernesto Garrido, E-mail: jeamharoldo@hotmail.com [Universidade de Sao Paulo (FFCLRP/USP), Ribeirao Preto, SP (Brazil). Faculdade de Filosofia, Ciencias e Letras; Santos, Antonio Carlos [Universidade de Sao Paulo (FMRP/USP), Ribeirao Preto, SP (Brazil). Faculdade de Medicina

    2015-03-15

    Objective: to present a detailed explanation on the processing of magnetic susceptibility weighted imaging (SWI), demonstrating the effects of echo time and sensitive mask on the differentiation between calcification and hemosiderin. Materials and methods: computed tomography and magnetic resonance (magnitude and phase) images of six patients (age range 41-54 years; four men) were retrospectively selected. The SWI images processing was performed using the Matlab's own routine. Results: four out of the six patients showed calcifications at computed tomography images and their SWI images demonstrated hyperintense signal at the calcification regions. The other patients did not show any calcifications at computed tomography, and SWI revealed the presence of hemosiderin deposits with hypointense signal. Conclusion: the selection of echo time and of the mask may change all the information on SWI images, and compromise the diagnostic reliability. Amongst the possible masks, the authors highlight that the sigmoid mask allows for contrasting calcifications and hemosiderin on a single SWI image. (author)

  12. Unusual Features of Extraarticular Skeletal Tuberculosis: New Classification and Differential Diagnosis

    International Nuclear Information System (INIS)

    Kim, Kun Sang; Park, Soo Soung

    1983-01-01

    Twenty two cases of extra articular skeletal tuberculosis which showed unusual radiological features are reported and classified into several categories with discussion on the differential diagnosis. Radiological patterns of skeletal tuberculosis is so variable that with any kind of skeletal changes the possibility of the skeletal tuberculosis should not be excluded between of lack of its classical patterns.

  13. Clinical features and differential diagnosis of type 2 diabetes mellitus in children

    Directory of Open Access Journals (Sweden)

    Tamara Leonidovna Kuraeva

    2009-09-01

    Full Text Available This review was designed to evaluate prevalence, specific clinical features, and differential diagnosis of type 2 diabetes mellitus (DM2 in childrenand adolescents. Special emphasis is laid on the importance of immunological and molecular-genetic studies for the verification of diagnosis and activecase detection in h groups.

  14. Differential clinical features and stool findings in shigellosis and amoebic dysentery

    NARCIS (Netherlands)

    Speelman, P.; McGlaughlin, R.; Kabir, I.; Butler, T.

    1987-01-01

    To obtain information that could assist the clinician to differentiate between shigellosis and amoebic dysentery, we compared clinical features and stool findings in 58 adult male patients in Bangladesh. Mean values indicated that patients with invasive amoebiasis were older and had a longer

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

    Science.gov (United States)

    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☆

    Science.gov (United States)

    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. Clinical and imaging features of neonatal chlamydial pneumonia

    International Nuclear Information System (INIS)

    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)

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

    Science.gov (United States)

    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

  19. Spectral differential imaging detection of planets about nearby stars

    International Nuclear Information System (INIS)

    Smith, W.H.

    1987-01-01

    Direct ground-based optical imaging of planets in orbit about nearby stars may be accomplished by spectral differential imaging using multiple passband acoustooptic filters with a CCD. This technique provides two essential results. First, it provides a means to modulate the stellar flux reflected from a planet while leaving the flux from the star and other sources in the same field of view unmodulated. Second, spectral differential imaging enables the CCD detector to achieve a sufficiently high dynamic range to locate planets near a star in spite of an integrated brightness differential of 5 x 10 8 . Spectral differential imaging at nearby diffraction limited imaging conditions with telescope apodization can reduce the time to conduct a sensitive planetary search to a few hours in some cases. The feasibility of this idea is discussed here and shown to provide, in principle, the discrimination and sensitivity to detect a Jovian-class planet about stars at distances of about 10 parsecs. The detection of brown dwarfs is shown to be feasible as well. 31 references

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  2. Differentiation of true anophthalmia from clinical anophthalmia using neuroradiological imaging

    OpenAIRE

    Celebi, Ali Riza Cenk; Sasani, Hadi

    2014-01-01

    Anophthalmia is a condition of the absence of an eye and the presence of a small eye within the orbit. It is associated with many known syndromes. Clinical findings, as well as imaging modalities and genetic analysis, are important in making the diagnosis. Imaging modalities are crucial scanning methods. Cryptophthalmos, cyclopia, synophthalmia and congenital cystic eye should be considered in differential diagnoses. We report two clinical anophthalmic siblings, emphasizing the importance of ...

  3. Differentiating high-grade from low-grade chondrosarcoma with MR imaging

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, Hye Jin; Hong, Sung Hwan; Choi, Ja-Young; Choi, Jung-Ah; Kang, Heung Sik [Seoul National University College of Medicine, Department of Radiology and Institute of Radiation Medicine, Seoul (Korea); Moon, Kyung Chul [Seoul National University College of Medicine, Department of Pathology, Seoul (Korea); Kim, Han-Soo [Seoul National University College of Medicine, Department of Orthopedic Surgery, Seoul (Korea)

    2009-12-15

    The purpose of the study was to evaluate the MR imaging features that differentiate between low-grade chondrosarcoma (LGCS) and high-grade chondrosarcoma (HGCS) and to determine the most reliable predictors for differentiation. MR images of 42 pathologically proven chondrosarcomas (28 LGCS and 14 HGCS) were retrospectively reviewed. There were 13 male and 29 female patients with an age range of 23-72 years (average age 51 years). On MR images, signal intensity, specific morphological characteristics including entrapped fat, internal lobular architecture, and outer lobular margin, soft tissue mass formation and contrast enhancement pattern were analysed. MR imaging features used to identify LGCS and HGCS were compared using univariate analysis and multivariate stepwise logistic regression analysis. On T1-weighted images, a central area of high signal intensity, which was not seen in LGCS, was frequently observed in HGCS (n = 5, 36%) (p < 0.01). Entrapped fat within the tumour was commonly seen in LGCS (n = 26, 93%), but not in HGCS (n = 1, 4%) (p < 0.01). LGCS more commonly (n = 24, 86%) preserved the characteristic internal lobular structures within the tumour than HGCSs (n = 4, 29%) (p < 0.01). Soft tissue formation was more frequently observed in HGCS (n = 11, 79%) than in LGCS (n = 1, 4%) (p < 0.01). On gadolinium-enhanced images, large central nonenhancing areas were exhibited in only two (7.1%) of LGCS, while HGCS frequently (n = 9, 64%) had a central nonenhancing portion (p < 0.01). Results of multivariate stepwise logistic regression analysis showed that soft tissue formation and entrapped fat within the tumour were the variables that could be used to independently differentiate LGCS from HGCS. There were several MR imaging features of chondrosarcoma that could be helpful in distinguishing HGCS from LGCS. Among them, soft tissue mass formation favoured the diagnosis of HGCS, and entrapped fat within the tumour was highly indicative of LGCS. (orig.)

  4. Differentiating high-grade from low-grade chondrosarcoma with MR imaging

    International Nuclear Information System (INIS)

    Yoo, Hye Jin; Hong, Sung Hwan; Choi, Ja-Young; Choi, Jung-Ah; Kang, Heung Sik; Moon, Kyung Chul; Kim, Han-Soo

    2009-01-01

    The purpose of the study was to evaluate the MR imaging features that differentiate between low-grade chondrosarcoma (LGCS) and high-grade chondrosarcoma (HGCS) and to determine the most reliable predictors for differentiation. MR images of 42 pathologically proven chondrosarcomas (28 LGCS and 14 HGCS) were retrospectively reviewed. There were 13 male and 29 female patients with an age range of 23-72 years (average age 51 years). On MR images, signal intensity, specific morphological characteristics including entrapped fat, internal lobular architecture, and outer lobular margin, soft tissue mass formation and contrast enhancement pattern were analysed. MR imaging features used to identify LGCS and HGCS were compared using univariate analysis and multivariate stepwise logistic regression analysis. On T1-weighted images, a central area of high signal intensity, which was not seen in LGCS, was frequently observed in HGCS (n = 5, 36%) (p < 0.01). Entrapped fat within the tumour was commonly seen in LGCS (n = 26, 93%), but not in HGCS (n = 1, 4%) (p < 0.01). LGCS more commonly (n = 24, 86%) preserved the characteristic internal lobular structures within the tumour than HGCSs (n = 4, 29%) (p < 0.01). Soft tissue formation was more frequently observed in HGCS (n = 11, 79%) than in LGCS (n = 1, 4%) (p < 0.01). On gadolinium-enhanced images, large central nonenhancing areas were exhibited in only two (7.1%) of LGCS, while HGCS frequently (n = 9, 64%) had a central nonenhancing portion (p < 0.01). Results of multivariate stepwise logistic regression analysis showed that soft tissue formation and entrapped fat within the tumour were the variables that could be used to independently differentiate LGCS from HGCS. There were several MR imaging features of chondrosarcoma that could be helpful in distinguishing HGCS from LGCS. Among them, soft tissue mass formation favoured the diagnosis of HGCS, and entrapped fat within the tumour was highly indicative of LGCS. (orig.)

  5. Spindle epithelial tumor with thymus-like differentiation of the thyroid gland: A case report with ultrasonography and CT features, cytological findings and histopathological results

    International Nuclear Information System (INIS)

    Kang, Dong Joo; Lee, Yoo Jin; Kim, Dong Wook; Jung, Soo Jin

    2016-01-01

    Spindle epithelial tumor with thymus-like differentiation (SETTLE) of the thyroid gland is a very rare tumor. It is believed to originate from ectopic thymus tissue within the thyroid gland or from branchial pouch remnants that differentiate along the thymic line. A few reports of SETTLE have been presented, but to the best of our knowledge, there is no case report in which detailed preoperative imaging features of SETTLE have been described. In addition, there are no case reports of SETTLE in Korean patients. Thus, we report a case of SETTLE with detailed preoperative ultrasonography and computed tomography features, cytological findings and histopathological results

  6. Spindle epithelial tumor with thymus-like differentiation of the thyroid gland: A case report with ultrasonography and CT features, cytological findings and histopathological results

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Dong Joo; Lee, Yoo Jin; Kim, Dong Wook; Jung, Soo Jin [Busan Paik Hospital, Inje University College of Medicine, Busan (Korea, Republic of)

    2016-11-15

    Spindle epithelial tumor with thymus-like differentiation (SETTLE) of the thyroid gland is a very rare tumor. It is believed to originate from ectopic thymus tissue within the thyroid gland or from branchial pouch remnants that differentiate along the thymic line. A few reports of SETTLE have been presented, but to the best of our knowledge, there is no case report in which detailed preoperative imaging features of SETTLE have been described. In addition, there are no case reports of SETTLE in Korean patients. Thus, we report a case of SETTLE with detailed preoperative ultrasonography and computed tomography features, cytological findings and histopathological results.

  7. CT imaging features of tuberculous spondylitis in children

    International Nuclear Information System (INIS)

    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

  8. A chondroblastoma versus a giant cell tumor: emphasis on the MR imaging features

    Energy Technology Data Exchange (ETDEWEB)

    Chai, Jee Won; Hong, Sung Hwan; Choi, Ja Young; Kim, Na Ra; Choi, Jung Ah; Kang, Heung Sik [Seoul National University College of Medicine, Seoul (Korea, Republic of)

    2007-10-15

    To assess the MR imaging features in differentiating a chondroblastoma (CB) from a giant cell tumor (GCT), with an emphasis on the accompanying peritumoral bone marrow edema. MR imaging findings in 20 patients with CB were compared with the imaging features of 22 patients with GCT. The location of the lesion, signal intensity, adjacent cortical change, degree of accompanying bone marrow edema, synovitis in the adjacent joint and cystic change were analyzed. The findings of CB and GCT were examined statistically with use of Fisher's exact test. The incidence ratios of MR imaging findings were as follows (CB:GCT). Metaphyseal dominant involvement (2:21), partial cortical disruption (2:14), extensive bone marrow edema surrounding the tumor (14:0) and synovitis in the adjacent joint (11:2) were statistically different in incidence between CB and GCT ({rho} < 0.01). The inhomogeneous signal intensity (17:17) and cystic change (10:15) were not different in incidence between a CB and GCT. The presence of metaphyseal dominant involvement and cortical disruption favors a diagnosis of a GCT rather than a CB. In contrast, extensive bone marrow edema surrounding the tumor and synovitis in the adjacent joint are highly indicative of a CB.

  9. A chondroblastoma versus a giant cell tumor: emphasis on the MR imaging features

    International Nuclear Information System (INIS)

    Chai, Jee Won; Hong, Sung Hwan; Choi, Ja Young; Kim, Na Ra; Choi, Jung Ah; Kang, Heung Sik

    2007-01-01

    To assess the MR imaging features in differentiating a chondroblastoma (CB) from a giant cell tumor (GCT), with an emphasis on the accompanying peritumoral bone marrow edema. MR imaging findings in 20 patients with CB were compared with the imaging features of 22 patients with GCT. The location of the lesion, signal intensity, adjacent cortical change, degree of accompanying bone marrow edema, synovitis in the adjacent joint and cystic change were analyzed. The findings of CB and GCT were examined statistically with use of Fisher's exact test. The incidence ratios of MR imaging findings were as follows (CB:GCT). Metaphyseal dominant involvement (2:21), partial cortical disruption (2:14), extensive bone marrow edema surrounding the tumor (14:0) and synovitis in the adjacent joint (11:2) were statistically different in incidence between CB and GCT (ρ < 0.01). The inhomogeneous signal intensity (17:17) and cystic change (10:15) were not different in incidence between a CB and GCT. The presence of metaphyseal dominant involvement and cortical disruption favors a diagnosis of a GCT rather than a CB. In contrast, extensive bone marrow edema surrounding the tumor and synovitis in the adjacent joint are highly indicative of a CB

  10. Combining deep learning and coherent anti-Stokes Raman scattering imaging for automated differential diagnosis of lung cancer

    Science.gov (United States)

    Weng, Sheng; Xu, Xiaoyun; Li, Jiasong; Wong, Stephen T. C.

    2017-10-01

    Lung cancer is the most prevalent type of cancer and the leading cause of cancer-related deaths worldwide. Coherent anti-Stokes Raman scattering (CARS) is capable of providing cellular-level images and resolving pathologically related features on human lung tissues. However, conventional means of analyzing CARS images requires extensive image processing, feature engineering, and human intervention. This study demonstrates the feasibility of applying a deep learning algorithm to automatically differentiate normal and cancerous lung tissue images acquired by CARS. We leverage the features learned by pretrained deep neural networks and retrain the model using CARS images as the input. We achieve 89.2% accuracy in classifying normal, small-cell carcinoma, adenocarcinoma, and squamous cell carcinoma lung images. This computational method is a step toward on-the-spot diagnosis of lung cancer and can be further strengthened by the efforts aimed at miniaturizing the CARS technique for fiber-based microendoscopic imaging.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  12. Reversible acute methotrexate leukoencephalopathy: atypical brain MR imaging features

    International Nuclear Information System (INIS)

    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.)

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

    Science.gov (United States)

    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.

  14. Perfusion MR imaging for differentiation of benign and malignant meningiomas

    NARCIS (Netherlands)

    Zhang, Hao; Rodiger, Lars A.; Shen, Tianzhen; Miao, Jingtao; Oudkerk, Matthijs

    Introduction Our purpose was to determine whether perfusion MR imaging can be used to differentiate benign and malignant meningiomas on the basis of the differences in perfusion of tumor parenchyma and/or peritumoral edema. Methods A total of 33 patients with preoperative meningiomas (25 benign and

  15. Electrodynamics, Differential Forms and the Method of Images

    Science.gov (United States)

    Low, Robert J.

    2011-01-01

    This paper gives a brief description of how Maxwell's equations are expressed in the language of differential forms and use this to provide an elegant demonstration of how the method of images (well known in electrostatics) also works for electrodynamics in the presence of an infinite plane conducting boundary. The paper should be accessible to an…

  16. Medical Imaging in Differentiating the Diabetic Charcot Foot from Osteomyelitis.

    Science.gov (United States)

    Short, Daniel J; Zgonis, Thomas

    2017-01-01

    Diabetic Charcot neuroarthropathy (DCN) poses a great challenge to diagnose in the early stages and when plain radiographs do not depict any initial signs of osseous fragmentation or dislocation in a setting of a high clinical index of suspicion. Medical imaging, including magnetic resonance imaging, computed tomography, and advanced bone scintigraphy, has its own unique clinical indications when treating the DCN with or without concomitant osteomyelitis. This article reviews different clinical case scenarios for choosing the most accurate medical imaging in differentiating DCN from osteomyelitis. Copyright © 2016 Elsevier Inc. All rights reserved.

  17. Prenatal MR imaging features of isolated cerebellar haemorrhagic lesions

    International Nuclear Information System (INIS)

    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.)

  18. The imaging feature of multidrug-resistant tuberculosis

    International Nuclear Information System (INIS)

    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)

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

    International Nuclear Information System (INIS)

    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.

  20. Statistical analysis of textural features for improved classification of oral histopathological images.

    Science.gov (United States)

    Muthu Rama Krishnan, M; Shah, Pratik; Chakraborty, Chandan; Ray, Ajoy K

    2012-04-01

    The objective of this paper is to provide an improved technique, which can assist oncopathologists in correct screening of oral precancerous conditions specially oral submucous fibrosis (OSF) with significant accuracy on the basis of collagen fibres in the sub-epithelial connective tissue. The proposed scheme is composed of collagen fibres segmentation, its textural feature extraction and selection, screening perfomance enhancement under Gaussian transformation and finally classification. In this study, collagen fibres are segmented on R,G,B color channels using back-probagation neural network from 60 normal and 59 OSF histological images followed by histogram specification for reducing the stain intensity variation. Henceforth, textural features of collgen area are extracted using fractal approaches viz., differential box counting and brownian motion curve . Feature selection is done using Kullback-Leibler (KL) divergence criterion and the screening performance is evaluated based on various statistical tests to conform Gaussian nature. Here, the screening performance is enhanced under Gaussian transformation of the non-Gaussian features using hybrid distribution. Moreover, the routine screening is designed based on two statistical classifiers viz., Bayesian classification and support vector machines (SVM) to classify normal and OSF. It is observed that SVM with linear kernel function provides better classification accuracy (91.64%) as compared to Bayesian classifier. The addition of fractal features of collagen under Gaussian transformation improves Bayesian classifier's performance from 80.69% to 90.75%. Results are here studied and discussed.

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

    Science.gov (United States)

    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.

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

    International Nuclear Information System (INIS)

    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)

  3. Optical Imaging for Stem Cell Differentiation to Neuronal Lineage

    International Nuclear Information System (INIS)

    Hwang, Do Won; Lee, Dong Soo

    2012-01-01

    In regenerative medicine, the prospect of stem cell therapy hold great promise for the recovery of injured tissues and effective treatment of intractable diseases. Tracking stem cell fate provides critical information to understand and evaluate the success of stem cell therapy. The recent emergence of in vivo noninvasive molecular imaging has enabled assessment of the behavior of grafted stem cells in living subjects. In this review, we provide an overview of current optical imaging strategies based on cell or tissue specific reporter gene expression and of in vivo methods to monitor stem cell differentiation into neuronal lineages. These methods use optical reporters either regulated by neuron-specific promoters or containing neuron-specific microRNA binding sites. Both systems revealed dramatic changes in optical reporter imaging signals in cells differentiating a yeast GAL4 amplification system or an engineering-enhanced luciferase reported gene. Furthermore, we propose an advanced imaging system to monitor neuronal differentiation during neurogenesis that uses in vivo multiplexed imaging techniques capable of detecting several targets simultaneously

  4. Evaluation of feature selection algorithms for classification in temporal lobe epilepsy based on MR images

    Science.gov (United States)

    Lai, Chunren; Guo, Shengwen; Cheng, Lina; Wang, Wensheng; Wu, Kai

    2017-02-01

    It's very important to differentiate the temporal lobe epilepsy (TLE) patients from healthy people and localize the abnormal brain regions of the TLE patients. The cortical features and changes can reveal the unique anatomical patterns of brain regions from the structural MR images. In this study, structural MR images from 28 normal controls (NC), 18 left TLE (LTLE), and 21 right TLE (RTLE) were acquired, and four types of cortical feature, namely cortical thickness (CTh), cortical surface area (CSA), gray matter volume (GMV), and mean curvature (MCu), were explored for discriminative analysis. Three feature selection methods, the independent sample t-test filtering, the sparse-constrained dimensionality reduction model (SCDRM), and the support vector machine-recursive feature elimination (SVM-RFE), were investigated to extract dominant regions with significant differences among the compared groups for classification using the SVM classifier. The results showed that the SVM-REF achieved the highest performance (most classifications with more than 92% accuracy), followed by the SCDRM, and the t-test. Especially, the surface area and gray volume matter exhibited prominent discriminative ability, and the performance of the SVM was improved significantly when the four cortical features were combined. Additionally, the dominant regions with higher classification weights were mainly located in temporal and frontal lobe, including the inferior temporal, entorhinal cortex, fusiform, parahippocampal cortex, middle frontal and frontal pole. It was demonstrated that the cortical features provided effective information to determine the abnormal anatomical pattern and the proposed method has the potential to improve the clinical diagnosis of the TLE.

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

    International Nuclear Information System (INIS)

    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

  6. Adaptive differential correspondence imaging based on sorting technique

    Directory of Open Access Journals (Sweden)

    Heng Wu

    2017-04-01

    Full Text Available We develop an adaptive differential correspondence imaging (CI method using a sorting technique. Different from the conventional CI schemes, the bucket detector signals (BDS are first processed by a differential technique, and then sorted in a descending (or ascending order. Subsequently, according to the front and last several frames of the sorted BDS, the positive and negative subsets (PNS are created by selecting the relative frames from the reference detector signals. Finally, the object image is recovered from the PNS. Besides, an adaptive method based on two-step iteration is designed to select the optimum number of frames. To verify the proposed method, a single-detector computational ghost imaging (GI setup is constructed. We experimentally and numerically compare the performance of the proposed method with different GI algorithms. The results show that our method can improve the reconstruction quality and reduce the computation cost by using fewer measurement data.

  7. Pseudoachondroplasia in a child: The role of anthropometric measurements and skeletal imaging in differential diagnosis

    Directory of Open Access Journals (Sweden)

    Radwa Gamal, MSc

    2017-03-01

    Full Text Available Pseudoachondroplasia is a rare osteochondrodysplasia characterized by disproportionate short stature and limb deformity. Diagnostic accuracy is based on a detailed evaluation of the radioclinical features. We report a boy with pseudoachondroplasia. We aim to underscore why is accurate delineation of the pattern of radioclinical skeletal abnormalities in pseudoachondroplasia a weighty part of diagnosis. Furthermore, we aim to highlight the main clinical and skeletal imaging features of skeletal dysplasias that overlap with pseudoachondroplasia using clinical cases evaluated in our institution. The findings affirm that anthropometric measurements and skeletal radiography are important contributors to the differential diagnosis and classification of disproportionate growth.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  10. Social Graph Community Differentiated by Node Features with Partly Missing Information

    Directory of Open Access Journals (Sweden)

    V. O. Chesnokov

    2015-01-01

    Full Text Available This paper proposes a new algorithm for community differentiation in social graphs, which uses information both on the graph structure and on the vertices. We consider user's ego-network i.e. his friends, with no himself, where each vertex has a set of features such as details on a workplace, institution, etc. The task is to determine missing or unspecified features of the vertices, based on their neighbors' features, and use these features to differentiate the communities in the social graph. Two vertices are believed to belong to the same community if they have a common feature. A hypothesis has been put forward that if most neighbors of a vertex have a common feature, there is a good probability that the vertex has this feature as well. The proposed algorithm is iterative and updates features of vertices, based on its neighbors, according to the hypothesis. Share of neighbors that form a majority is specified by the algorithm parameter. Complexity of single iteration depends linearly on the number of edges in the graph.To assess the quality of clustering three normalized metrics were used, namely: expected density, silhouette index, and Hubert's Gamma Statistic. The paper describes a method for test sampling of 2.000 graphs of the user's social network \\VKontakte". The API requests addressed \\VKontakte" and parsing HTML-pages of user's profiles and search results provided crawling. Information on user's group membership, secondary and higher education, and workplace was used as features. To store data the PostgreSQL DBMS was used, and the gexf format was used for data processing. For the test sample, metrics for several values of algorithm parameter were estimated: the value of index silhouettes was low (0.14-0.20, but within the normal range; the value of expected density was high, i.e. 1.17-1.52; the value of Hubert's gamma statistic was 0.94-0.95 that is close to the maximum. The number of vertices with no features was calculated before

  11. The utility of diffusion-weighted MR imaging for differentiating uterine sarcomas from benign leiomyomas

    International Nuclear Information System (INIS)

    Tamai, Ken; Saga, Tsuneo; Morisawa, Nobuko; Fujimoto, Koji; Togashi, Kaori; Koyama, Takashi; Mikami, Yoshiki

    2008-01-01

    The usefulness of diffusion-weighted (DW) magnetic resonance (MR) imaging for the diagnosis of uterine sarcomas was investigated, as well as whether DW images and quantitative measurement of apparent diffusion coefficient (ADC) values can facilitate differentiating uterine sarcomas from benign leiomyomas. MR images including DW images were obtained in 43 surgically treated patients with 58 myometrial tumors, including seven uterine sarcomas (five leiomyosarcomas and two endometrial stromal sarcomas) and 51 benign leiomyomas (43 ordinary leiomyomas, two cellular leiomyomas and six degenerated leiomyomas). Qualitative analysis of non-enhanced and postcontrast MR images and DW images and quantitative measurement of ADC values were performed for each myometrial tumor. Both uterine sarcomas and cellular leiomyomas exhibited high signal intensity on DW images, whereas ordinary leiomyomas and most degenerated leiomyomas showed low signal intensity. The mean ADC value (10 -3 mm 2 /s) of sarcomas was 1.17 ± 0.15, which was lower than those of the normal myometrium (1.62 ± 0.11) and degenerated leiomyomas (1.70 ± 0.11) without any overlap; however, they were overlapped with those of ordinary leiomyomas and cellular leiomyomas. In addition to morphological features on nonenhanced and postcontrast MR sequences, DW imaging and ADC measurement may have a potential ability to differentiate uterine sarcomas from benign leiomyomas. (orig.)

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

    Science.gov (United States)

    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

  13. Fake/Bogus Conferences; Their Features and Some Subtle Ways to Differentiate Them from Real Ones

    DEFF Research Database (Denmark)

    Asadi, Amin; Rahbar, Nader; Rezvani, Mohammad Javad

    2018-01-01

    The main objective of the present paper is to introduce some features of fake/bogus conferences and some viable approaches to differentiate them from the real ones. These fake/bogus conferences introduce themselves as international conferences, which are multidisciplinary and indexed in major sci...... scientific digital libraries. Furthermore, most of the fake/bogus conference holders offer publishing the accepted papers in ISI journals and use other techniques in their advertisement e-mails.......The main objective of the present paper is to introduce some features of fake/bogus conferences and some viable approaches to differentiate them from the real ones. These fake/bogus conferences introduce themselves as international conferences, which are multidisciplinary and indexed in major...

  14. Sciatica-like symptoms and the sacroiliac joint: clinical features and differential diagnosis

    NARCIS (Netherlands)

    Visser, L.H.; Nijssen, P.G.; Tijssen, C.C.; Middendorp, J.J. van; Schieving, J.H.

    2013-01-01

    PURPOSE: To compare the clinical features of patients with sacroiliac joint (SIJ)-related sciatica-like symptoms to those with sciatica from nerve root compression and to investigate the necessity to perform radiological imaging in patients with sciatica-like symptoms derived from the SIJ. METHODS:

  15. Fake/Bogus Conferences: Their Features and Some Subtle Ways to Differentiate Them from Real Ones.

    Science.gov (United States)

    Asadi, Amin; Rahbar, Nader; Rezvani, Mohammad Javad; Asadi, Fahime

    2018-04-01

    The main objective of the present paper is to introduce some features of fake/bogus conferences and some viable approaches to differentiate them from the real ones. These fake/bogus conferences introduce themselves as international conferences, which are multidisciplinary and indexed in major scientific digital libraries. Furthermore, most of the fake/bogus conference holders offer publishing the accepted papers in ISI journals and use other techniques in their advertisement e-mails.

  16. Fake/Bogus Conferences; Their Features and Some Subtle Ways to Differentiate Them from Real Ones

    DEFF Research Database (Denmark)

    Asadi, Amin; Rahbar, Nader; Rezvani, Mohammad Javad

    2018-01-01

    The main objective of the present paper is to introduce some features of fake/bogus conferences and some viable approaches to differentiate them from the real ones. These fake/bogus conferences introduce themselves as international conferences, which are multidisciplinary and indexed in major sci...... scientific digital libraries. Furthermore, most of the fake/bogus conference holders offer publishing the accepted papers in ISI journals and use other techniques in their advertisement e-mails....

  17. Automatic Classification of Normal and Cancer Lung CT Images Using Multiscale AM-FM Features

    Directory of Open Access Journals (Sweden)

    Eman Magdy

    2015-01-01

    Full Text Available Computer-aided diagnostic (CAD systems provide fast and reliable diagnosis for medical images. In this paper, CAD system is proposed to analyze and automatically segment the lungs and classify each lung into normal or cancer. Using 70 different patients’ lung CT dataset, Wiener filtering on the original CT images is applied firstly as a preprocessing step. Secondly, we combine histogram analysis with thresholding and morphological operations to segment the lung regions and extract each lung separately. Amplitude-Modulation Frequency-Modulation (AM-FM method thirdly, has been used to extract features for ROIs. Then, the significant AM-FM features have been selected using Partial Least Squares Regression (PLSR for classification step. Finally, K-nearest neighbour (KNN, support vector machine (SVM, naïve Bayes, and linear classifiers have been used with the selected AM-FM features. The performance of each classifier in terms of accuracy, sensitivity, and specificity is evaluated. The results indicate that our proposed CAD system succeeded to differentiate between normal and cancer lungs and achieved 95% accuracy in case of the linear classifier.

  18. Tie Points Extraction for SAR Images Based on Differential Constraints

    Science.gov (United States)

    Xiong, X.; Jin, G.; Xu, Q.; Zhang, H.

    2018-04-01

    Automatically extracting tie points (TPs) on large-size synthetic aperture radar (SAR) images is still challenging because the efficiency and correct ratio of the image matching need to be improved. This paper proposes an automatic TPs extraction method based on differential constraints for large-size SAR images obtained from approximately parallel tracks, between which the relative geometric distortions are small in azimuth direction and large in range direction. Image pyramids are built firstly, and then corresponding layers of pyramids are matched from the top to the bottom. In the process, the similarity is measured by the normalized cross correlation (NCC) algorithm, which is calculated from a rectangular window with the long side parallel to the azimuth direction. False matches are removed by the differential constrained random sample consensus (DC-RANSAC) algorithm, which appends strong constraints in azimuth direction and weak constraints in range direction. Matching points in the lower pyramid images are predicted with the local bilinear transformation model in range direction. Experiments performed on ENVISAT ASAR and Chinese airborne SAR images validated the efficiency, correct ratio and accuracy of the proposed method.

  19. TIE POINTS EXTRACTION FOR SAR IMAGES BASED ON DIFFERENTIAL CONSTRAINTS

    Directory of Open Access Journals (Sweden)

    X. Xiong

    2018-04-01

    Full Text Available Automatically extracting tie points (TPs on large-size synthetic aperture radar (SAR images is still challenging because the efficiency and correct ratio of the image matching need to be improved. This paper proposes an automatic TPs extraction method based on differential constraints for large-size SAR images obtained from approximately parallel tracks, between which the relative geometric distortions are small in azimuth direction and large in range direction. Image pyramids are built firstly, and then corresponding layers of pyramids are matched from the top to the bottom. In the process, the similarity is measured by the normalized cross correlation (NCC algorithm, which is calculated from a rectangular window with the long side parallel to the azimuth direction. False matches are removed by the differential constrained random sample consensus (DC-RANSAC algorithm, which appends strong constraints in azimuth direction and weak constraints in range direction. Matching points in the lower pyramid images are predicted with the local bilinear transformation model in range direction. Experiments performed on ENVISAT ASAR and Chinese airborne SAR images validated the efficiency, correct ratio and accuracy of the proposed method.

  20. Clinical features and imaging of central poststroke pain

    Directory of Open Access Journals (Sweden)

    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.

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

    International Nuclear Information System (INIS)

    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

  2. Automated local bright feature image analysis of nuclear protein distribution identifies changes in tissue phenotype

    International Nuclear Information System (INIS)

    Knowles, David; Sudar, Damir; Bator, Carol; Bissell, Mina

    2006-01-01

    The organization of nuclear proteins is linked to cell and tissue phenotypes. When cells arrest proliferation, undergo apoptosis, or differentiate, the distribution of nuclear proteins changes. Conversely, forced alteration of the distribution of nuclear proteins modifies cell phenotype. Immunostaining and fluorescence microscopy have been critical for such findings. However, there is an increasing need for quantitative analysis of nuclear protein distribution to decipher epigenetic relationships between nuclear structure and cell phenotype, and to unravel the mechanisms linking nuclear structure and function. We have developed imaging methods to quantify the distribution of fluorescently-stained nuclear protein NuMA in different mammary phenotypes obtained using three-dimensional cell culture. Automated image segmentation of DAPI-stained nuclei was generated to isolate thousands of nuclei from three-dimensional confocal images. Prominent features of fluorescently-stained NuMA were detected using a novel local bright feature analysis technique, and their normalized spatial density calculated as a function of the distance from the nuclear perimeter to its center. The results revealed marked changes in the distribution of the density of NuMA bright features as non-neoplastic cells underwent phenotypically normal acinar morphogenesis. In contrast, we did not detect any reorganization of NuMA during the formation of tumor nodules by malignant cells. Importantly, the analysis also discriminated proliferating non-neoplastic cells from proliferating malignant cells, suggesting that these imaging methods are capable of identifying alterations linked not only to the proliferation status but also to the malignant character of cells. We believe that this quantitative analysis will have additional applications for classifying normal and pathological tissues

  3. Automated local bright feature image analysis of nuclear proteindistribution identifies changes in tissue phenotype

    Energy Technology Data Exchange (ETDEWEB)

    Knowles, David; Sudar, Damir; Bator, Carol; Bissell, Mina

    2006-02-01

    The organization of nuclear proteins is linked to cell and tissue phenotypes. When cells arrest proliferation, undergo apoptosis, or differentiate, the distribution of nuclear proteins changes. Conversely, forced alteration of the distribution of nuclear proteins modifies cell phenotype. Immunostaining and fluorescence microscopy have been critical for such findings. However, there is an increasing need for quantitative analysis of nuclear protein distribution to decipher epigenetic relationships between nuclear structure and cell phenotype, and to unravel the mechanisms linking nuclear structure and function. We have developed imaging methods to quantify the distribution of fluorescently-stained nuclear protein NuMA in different mammary phenotypes obtained using three-dimensional cell culture. Automated image segmentation of DAPI-stained nuclei was generated to isolate thousands of nuclei from three-dimensional confocal images. Prominent features of fluorescently-stained NuMA were detected using a novel local bright feature analysis technique, and their normalized spatial density calculated as a function of the distance from the nuclear perimeter to its center. The results revealed marked changes in the distribution of the density of NuMA bright features as non-neoplastic cells underwent phenotypically normal acinar morphogenesis. In contrast, we did not detect any reorganization of NuMA during the formation of tumor nodules by malignant cells. Importantly, the analysis also discriminated proliferating non-neoplastic cells from proliferating malignant cells, suggesting that these imaging methods are capable of identifying alterations linked not only to the proliferation status but also to the malignant character of cells. We believe that this quantitative analysis will have additional applications for classifying normal and pathological tissues.

  4. Imaging features of anterior cruciate ligament reconstruction graft insufficiency

    International Nuclear Information System (INIS)

    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)

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  6. Edge detection of optical subaperture image based on improved differential box-counting method

    Science.gov (United States)

    Li, Yi; Hui, Mei; Liu, Ming; Dong, Liquan; Kong, Lingqin; Zhao, Yuejin

    2018-01-01

    Optical synthetic aperture imaging technology is an effective approach to improve imaging resolution. Compared with monolithic mirror system, the image of optical synthetic aperture system is often more complex at the edge, and as a result of the existence of gap between segments, which makes stitching becomes a difficult problem. So it is necessary to extract the edge of subaperture image for achieving effective stitching. Fractal dimension as a measure feature can describe image surface texture characteristics, which provides a new approach for edge detection. In our research, an improved differential box-counting method is used to calculate fractal dimension of image, then the obtained fractal dimension is mapped to grayscale image to detect edges. Compared with original differential box-counting method, this method has two improvements as follows: by modifying the box-counting mechanism, a box with a fixed height is replaced by a box with adaptive height, which solves the problem of over-counting the number of boxes covering image intensity surface; an image reconstruction method based on super-resolution convolutional neural network is used to enlarge small size image, which can solve the problem that fractal dimension can't be calculated accurately under the small size image, and this method may well maintain scale invariability of fractal dimension. The experimental results show that the proposed algorithm can effectively eliminate noise and has a lower false detection rate compared with the traditional edge detection algorithms. In addition, this algorithm can maintain the integrity and continuity of image edge in the case of retaining important edge information.

  7. Evaluation of MR diffusion-weighted imaging in differentiating endometriosis infiltrating the bowel from colorectal carcinoma

    International Nuclear Information System (INIS)

    Busard, M.P.H.; Pieters-van den Bos, I.C.; Mijatovic, V.; Van Kuijk, C.; Bleeker, M.C.G.; Waesberghe, J.H.T.M. van

    2012-01-01

    Objective: Endometriosis infiltrating the bowel may be difficult to differentiate from colorectal carcinoma in cases that present with non-specific clinical and imaging features. The aim of this study is to assess the value of MR diffusion-weighted imaging (DWI) in differentiating endometriosis infiltrating the bowel from colorectal carcinoma. Methods: In 66 patients, MR DWI was added to the standard imaging protocol in patients visiting our outdoor MR clinic for the analysis of suspected or known deep infiltrating endometriosis (DIE). In patients diagnosed with DIE infiltrating the bowel on MR imaging, high b-value diffusion-weighted images were qualitatively assessed by two readers in consensus and compared to high b-value diffusion weighted images in 15 patients evaluated for colorectal carcinoma. In addition, ADC values of lesions were calculated, using b-values of 50, 400 and 800 s/mm 2 . Results: A total of 15 patients were diagnosed with DIE infiltrating the bowel on MR imaging. Endometriosis infiltrating the bowel showed low signal intensity on high b-value diffusion-weighted images in all patients, whereas colorectal carcinoma showed high signal intensity on high b-value diffusion-weighted images in all patients. Mean ADC value in endometriosis infiltrating the bowel (0.80 ± 0.06 × 10 −3 mm 2 /s) was significantly lower compared to mean ADC value in colorectal carcinoma (0.86 ± 0.06 × 10 −3 mm 2 /s), but with considerable overlap between ADC values. Conclusion: Only qualitative assessment of MR DWI may be valuable to facilitate differentiation between endometriosis infiltrating the bowel and colorectal carcinoma.

  8. Body imaging in the differential diagnosis of jaundice

    International Nuclear Information System (INIS)

    Kuno, Nobuyoshi; Endo, Tokiko; Kasugai, Tatsuzo

    1981-01-01

    Forty-five jaundiced patients with confirmed pancreatico-biliary diseases were studied to determine the value of body imaging in the differential diagnosis of jaundice. In this study, body imaging included five tests, which were US, CT, ERCP, PTC and RI. The results indicate that each to these five tests is useful and highly accurate in differentiating between obstructive and nonobstructive jaundice (about 90%). The site of obstruction was delineated in 91.3%, 90.9%, 82.5%, 66.7% and 50% by PTC, ERCP, CT, US and RI, respectively. ERCP, PTC, CT, US and RI helped determine the etiology of jaundice in 79.5%, 65.2%, 57.5%, 50% and 0%, respectively. ERCP and US were highly accurate in establishing the diagnosis of resectable pancreatico-biliary cancer with obstructive jaundice. On the basis of these results, we propose a diagnostic approach to obstructive jaundice as in Table 5. (author)

  9. Image fusion in x-ray differential phase-contrast imaging

    Science.gov (United States)

    Haas, W.; Polyanskaya, M.; Bayer, F.; Gödel, K.; Hofmann, H.; Rieger, J.; Ritter, A.; Weber, T.; Wucherer, L.; Durst, J.; Michel, T.; Anton, G.; Hornegger, J.

    2012-02-01

    Phase-contrast imaging is a novel modality in the field of medical X-ray imaging. The pioneer method is the grating-based interferometry which has no special requirements to the X-ray source and object size. Furthermore, it provides three different types of information of an investigated object simultaneously - absorption, differential phase-contrast and dark-field images. Differential phase-contrast and dark-field images represent a completely new information which has not yet been investigated and studied in context of medical imaging. In order to introduce phase-contrast imaging as a new modality into medical environment the resulting information about the object has to be correctly interpreted. The three output images reflect different properties of the same object the main challenge is to combine and visualize these data in such a way that it diminish the information explosion and reduce the complexity of its interpretation. This paper presents an intuitive image fusion approach which allows to operate with grating-based phase-contrast images. It combines information of the three different images and provides a single image. The approach is implemented in a fusion framework which is aimed to support physicians in study and analysis. The framework provides the user with an intuitive graphical user interface allowing to control the fusion process. The example given in this work shows the functionality of the proposed method and the great potential of phase-contrast imaging in medical practice.

  10. Prediction of pancreatic neuroendocrine tumour grade with MR imaging features: added value of diffusion-weighted imaging

    Energy Technology Data Exchange (ETDEWEB)

    Lotfalizadeh, Emad; Vullierme, Marie-Pierre; Allaham, Wassim [University Hospitals Paris Nord Val de Seine, Department of Radiology, Clichy, Hauts-de-Seine (France); Ronot, Maxime; Vilgrain, Valerie [University Hospitals Paris Nord Val de Seine, Department of Radiology, Clichy, Hauts-de-Seine (France); University Paris Diderot, Paris (France); INSERM U1149, Centre de Recherche Biomedicale Bichat-Beaujon, CRB3, Paris (France); Wagner, Mathilde [University Hospitals Paris Nord Val de Seine, Department of Radiology, Clichy, Hauts-de-Seine (France); INSERM U1149, Centre de Recherche Biomedicale Bichat-Beaujon, CRB3, Paris (France); Cros, Jerome; Couvelard, Anne [University Paris Diderot, Paris (France); University Hospitals Paris Nord Val de Seine, Department of Pathology, Clichy, Hauts-de-Seine (France); Hentic, Olivia; Ruzniewski, Philippe [University Hospitals Paris Nord Val de Seine, Department of Gastroenterology, Clichy, Hauts-de-Seine (France)

    2017-04-15

    To evaluate the value of MR imaging including diffusion-weighted imaging (DWI) for the grading of pancreatic neuroendocrine tumours (pNET). Between 2006 and 2014, all resected pNETs with preoperative MR imaging including DWI were included. Tumour grading was based on the 2010 WHO classification. MR imaging features included size, T1-w, and T2-w signal intensity, enhancement pattern, apparent (ADC) and true diffusion (D) coefficients. One hundred and eight pNETs (mean 40 ± 33 mm) were evaluated in 94 patients (48 women, 51 %, mean age 52 ± 12). Fifty-five (51 %), 42 (39 %), and 11 (10 %) tumours were given the following grades (G): G1, G2, and G3. Mean ADC and D values were significantly lower as grade increased (ADC: 2.13 ± 0.70, 1.78 ± 0.72, and 0.86 ± 0.22 10{sup -3} mm{sup 2}/s, and D: 1.92 ± 0.70, 1.75 ± 0.74, and 0.82 ± 0.19 10{sup -3} mm{sup 2}/s G1, G2, and G3, all p < 0.001). A higher grade was associated with larger sized tumours (p < 0.001). The AUROC of ADC and D to differentiate G3 and G1-2 were 0.96 ± 0.02 and 0.95 ± 0.02. Optimal cut-off values for the identification of G3 were 1.19 10{sup -3} mm{sup 2}/s for ADC (sensitivity 100 %, specificity 92 %) and 1.04 10{sup -3} mm{sup 2}/s for D (sensitivity 82 %, specificity 92 %). Morphological/functional MRI features of pNETS depend on tumour grade. DWI is useful for the identification of high-grade tumours. (orig.)

  11. MR imaging of transient synovitis: differentiation from septic arthritis

    International Nuclear Information System (INIS)

    Yang, W.J.; Im, S.A.; Lim, G.Y.; Chun, H.J.; Jung, N.Y.; Sung, M.S.; Choi, B.G.

    2006-01-01

    Transient synovitis is the most common cause of acute hip pain in children. However, MR imaging findings in transient synovitis and the role of MR imaging in differentiating transient synovitis from septic arthritis have not been fully reported. To describe the MR findings of transient synovitis and to determine whether the MR characteristics can differentiate this disease entity from septic arthritis. Clinical findings and MR images of 49 patients with transient synovitis (male/female 36/13, mean age 6.1 years) and 18 patients with septic arthritis (male/female 10/8, mean age 4.9 years) were retrospectively reviewed. MR findings of transient synovitis were symptomatic joint effusion, synovial enhancement, contralateral joint effusion, synovial thickening, and signal intensity (SI) alterations and enhancement in surrounding soft tissue. Among these, SI alterations and enhancement in bone marrow and soft tissue, contralateral joint effusion, and synovial thickening were statistically significant MR findings in differentiating transient synovitis from septic arthritis. The statistically significant MR findings in transient synovitis are contralateral (asymptomatic) joint effusions and the absence of SI abnormalities of the bone marrow. It is less common to have SI alterations and contrast enhancement of the soft tissues. The statistically significant MR findings in septic arthritis are SI alterations of the bone marrow, and SI alterations and contrast enhancement of the soft tissue. Ipsilateral effusion and synovial thickening and enhancement are present in both diseases

  12. Gilbert’s syndrome: clinical features, diagnostics, differential diagnosis and treatment (part 2

    Directory of Open Access Journals (Sweden)

    T.V. Sorokman

    2017-02-01

    discoloration of the skin (“teinte bilieuse”, especially on the face, hands, and feet without a distinct scleral icterus. Sometimes the development of repeatedly intermittent episodes of jaundice with high bilirubinemia (indirect bilirubin without the evidence of hemolysis (differential diagnostic feature is observed. 2. A tendency to development of pigmented and vascular nevi and xanthelasma of the eyelids, and hyperpigmentation around the eyes; to bradycardia, hypothermia, migraine, postural, intermittent albuminuria or to alimentary glycosuria. 3. An increased tendency to pigmentation under the influence of light, heat, and also chemical and mechanical stimuli. 4. A neuromuscular hyperexcitability. 5. Increased sensitivity to cold. 6. Dyspeptic complaints (pain, nausea, abdominal bloa­ting, diarrhea or constipation. 7. No signs of increased hemolysis (differential diagnostic feature with increasing content in, bilirubin (differential diagnostic feature. 8. The majority of patients have normal liver function tests (differential diagnostic feature also normal bromsulphalein test is also normal (differential diagnostic feature. 9. The biochemical abnormality is not detected by histological methods (differential diagnostic feature .10. Frequently, a family disease of the liver is observed. The differential diagnosis of GS is conducted with all types of hyperbilirubinemias, hemolytic anemias, congenital hepatic cirrhosis, hepatitis, cholecystopathy, atresia of biliary ducts or the small intestine. Medications are used only in severe hyperbilirubinemias and as concomitant therapy in the presence of symptoms of vitamin deficiencies, violations of a motor-evacuation function of the upper digestive tract in the clinical picture and to prevent complications (cholelithiasis.

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

    International Nuclear Information System (INIS)

    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

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  15. Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

    Directory of Open Access Journals (Sweden)

    Shengwen Guo

    2017-05-01

    Full Text Available 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, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI, the converted MCI (cMCI, and the normal control (NC groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM. An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and

  16. MR imaging of the neonatal brain: Pathologic features

    International Nuclear Information System (INIS)

    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

  17. Identification of the Causative Disease of Intermittent Claudication through Walking Motion Analysis: Feature Analysis and Differentiation

    Directory of Open Access Journals (Sweden)

    Tetsuyou Watanabe

    2014-01-01

    Full Text Available Intermittent claudication is a walking symptom. Patients with intermittent claudication experience lower limb pain after walking for a short time. However, rest relieves the pain and allows the patient to walk again. Unfortunately, this symptom predominantly arises from not 1 but 2 different diseases: LSS (lumber spinal canal stenosis and PAD (peripheral arterial disease. Patients with LSS can be subdivided by the affected vertebra into 2 main groups: L4 and L5. It is clinically very important to determine whether patients with intermittent claudication suffer from PAD, L4, or L5. This paper presents a novel SVM- (support vector machine- based methodology for such discrimination/differentiation using minimally required data, simple walking motion data in the sagittal plane. We constructed a simple walking measurement system that is easy to set up and calibrate and suitable for use by nonspecialists in small spaces. We analyzed the obtained gait patterns and derived input parameters for SVM that are also visually detectable and medically meaningful/consistent differentiation features. We present a differentiation methodology utilizing an SVM classifier. Leave-one-out cross-validation of differentiation/classification by this method yielded a total accuracy of 83%.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  20. Features of the differential diagnosis of persons with gender identity disorders

    Directory of Open Access Journals (Sweden)

    Z.D. Novikova

    2013-10-01

    Full Text Available We presented a study of the features of gender identity in people undergoing gender, psychological and psychiatric examination to address the issue of gender reassignment. We analyze the specifics of gender identity, levels of masculinity and femininity, the similarities and differentiation within four nosological groups, which include persons with gender identity disorders (GID with transsexualism, personality disorders, diseases of the schizophrenia spectrum, and with organic mental disorders. We address the question of the differential diagnosis in the process of psychological screening of people with transsexualism and other types of GID. The analytical description of the four algorithms and their comparison are psychologically specific, qualitative research, almost impossible using statistical method of data processing. The data presented may be useful to specialists involved in the study of persons with gender identity disorders

  1. Early differential processing of material images: Evidence from ERP classification.

    Science.gov (United States)

    Wiebel, Christiane B; Valsecchi, Matteo; Gegenfurtner, Karl R

    2014-06-24

    Investigating the temporal dynamics of natural image processing using event-related potentials (ERPs) has a long tradition in object recognition research. In a classical Go-NoGo task two characteristic effects have been emphasized: an early task independent category effect and a later task-dependent target effect. Here, we set out to use this well-established Go-NoGo paradigm to study the time course of material categorization. Material perception has gained more and more interest over the years as its importance in natural viewing conditions has been ignored for a long time. In addition to analyzing standard ERPs, we conducted a single trial ERP pattern analysis. To validate this procedure, we also measured ERPs in two object categories (people and animals). Our linear classification procedure was able to largely capture the overall pattern of results from the canonical analysis of the ERPs and even extend it. We replicate the known target effect (differential Go-NoGo potential at frontal sites) for the material images. Furthermore, we observe task-independent differential activity between the two material categories as early as 140 ms after stimulus onset. Using our linear classification approach, we show that material categories can be differentiated consistently based on the ERP pattern in single trials around 100 ms after stimulus onset, independent of the target-related status. This strengthens the idea of early differential visual processing of material categories independent of the task, probably due to differences in low-level image properties and suggests pattern classification of ERP topographies as a strong instrument for investigating electrophysiological brain activity. © 2014 ARVO.

  2. FLAIR imaging for differential diagnosis of new cerebral microbleeds

    International Nuclear Information System (INIS)

    Watanabe, Akira

    2009-01-01

    It may be difficult to determine the time of appearance of cerebral microbleeds (MBs) in T2*-weighted MR imaging (MRI), because most MBs take more than several years to become absorbed. The presence of MBs is closely related to intracerebral hemorrhage, and it is important to detect new MBs in order to prevent intracerebral hemorrhage. We evaluated 108 patients on maintenance hemodialysis with MRI at least twice from May 2003 to May 2008. Seventy-two new MBs were detected and 59 MBs disappeared. Initial fluid-attenuated inversion recovery (FLAIR) imaging revealed 3 MBs with surrounding hyperintensity (SH), but follow-up FLAIR imaging demonstrated disappearance of the SH in all cases. Five of the 72 new MBs had SH, but follow-up FLAIR imaging demonstrated disappearance of the SH in all cases. In one case, SH with the enlarged MB disappeared in follow-up FLAIR images. In conclusion, we considered SH of new MBs to be vasogenic edema accompanying new intracerebral hemorrhage. It was useful to compare T2*-weighted MRI with FLAIR imaging to determine the differential diagnosis of new MBs. (author)

  3. Differentiation between ovarian fibroma and subserosal leiomyoma by MR imaging

    International Nuclear Information System (INIS)

    Choi, Sang Yeol; Lee, Jun Woo; Kim, Chang Won; Kim, Yong Woo; Lee, Suck Hong

    2000-01-01

    To evaluate the findings and differential points of ovarian fibroma and subserosal leiomyoma, as seen on MR images. The MRimaging findings of 31 surgically confirmed cases of ovarian fibroma (n=3D6) and subserosal leiomyoma (n=3D25; 28) lesions were evaluated. Multiplanar T1-T2-weighted and postcontrast T1-weighted images were obtained using a 1.5T MR unit, and histologic examination was also performed. The MR findings were analyzed in terms of signal intensity, the presence and definition of margin, the histologic finding of hyperintense lesion on T2-weighted images, the presence of the bridging vessel sign, degree of enhancement, and the presence of ipsilateral ovary and ascites. Both fibromas and leiomyomas showed hypo- or isointensity compared with uterine myometrium on T1-weighted images and compared with skeletal muscle on T2-weighted images. The latter revealed intratumoral hyperintense lesions in most cases of ovarian fibroma and subserosal leiomyoma. Three of four ovarian fibromas had a well defined margin after cystic change, but in 24 of 26 subserosal leiomyomas the margin was ill defined. The 'bridging vessel sign' was visible only in subserosal leiomyomas (22/28), and in all cases the enhancement of ovarian fibromas were less than that of myomtetrium. Subserosal leiomyomas (12/28), seen on enhancement as isointense or hyperintense to myometrium, showed a greater degree of enhancement than ovarian fibromas (0/6). Ipsilateral ovary was rarely seen in ovarian fibromas (1/6), but commonly seen in subserosal leiomyomas (20/250. Ascites was present in one case of ovarian fibroma. A defined margin of an intratumoral hyperintense lesion, as seen on T2-weighted images, and the presence or absence of the 'bridging vessel sign' and ipsilateral ovary are useful signs when differentiating between ovarian fibromas and subserosal leiomyomas. (author)

  4. Differentiation between ovarian fibroma and subserosal leiomyoma by MR imaging

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Sang Yeol; Lee, Jun Woo; Kim, Chang Won; Kim, Yong Woo; Lee, Suck Hong [College of Medicine, Pusan National University, Pusan (Korea, Republic of)

    2000-01-01

    To evaluate the findings and differential points of ovarian fibroma and subserosal leiomyoma, as seen on MR images. The MRimaging findings of 31 surgically confirmed cases of ovarian fibroma (n=3D6) and subserosal leiomyoma (n=3D25; 28) lesions were evaluated. Multiplanar T1-T2-weighted and postcontrast T1-weighted images were obtained using a 1.5T MR unit, and histologic examination was also performed. The MR findings were analyzed in terms of signal intensity, the presence and definition of margin, the histologic finding of hyperintense lesion on T2-weighted images, the presence of the bridging vessel sign, degree of enhancement, and the presence of ipsilateral ovary and ascites. Both fibromas and leiomyomas showed hypo- or isointensity compared with uterine myometrium on T1-weighted images and compared with skeletal muscle on T2-weighted images. The latter revealed intratumoral hyperintense lesions in most cases of ovarian fibroma and subserosal leiomyoma. Three of four ovarian fibromas had a well defined margin after cystic change, but in 24 of 26 subserosal leiomyomas the margin was ill defined. The 'bridging vessel sign' was visible only in subserosal leiomyomas (22/28), and in all cases the enhancement of ovarian fibromas were less than that of myomtetrium. Subserosal leiomyomas (12/28), seen on enhancement as isointense or hyperintense to myometrium, showed a greater degree of enhancement than ovarian fibromas (0/6). Ipsilateral ovary was rarely seen in ovarian fibromas (1/6), but commonly seen in subserosal leiomyomas (20/250. Ascites was present in one case of ovarian fibroma. A defined margin of an intratumoral hyperintense lesion, as seen on T2-weighted images, and the presence or absence of the 'bridging vessel sign' and ipsilateral ovary are useful signs when differentiating between ovarian fibromas and subserosal leiomyomas. (author)

  5. A Modified Image Comparison Algorithm Using Histogram Features

    OpenAIRE

    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...

  6. Amide proton transfer imaging for differentiation of benign and atypical meningiomas

    Energy Technology Data Exchange (ETDEWEB)

    Joo, Bio [The Armed Forces Capital Hospital, Department of Radiology, Seongnam, Gyeonggi-do (Korea, Republic of); Han, Kyunghwa; Choi, Yoon Seong; Lee, Seung-Koo [Yonsei University College of Medicine, Department of Radiology and Research Institute of Radiological Science, College of Medicine, Seoul (Korea, Republic of); Ahn, Sung Soo [Yonsei University College of Medicine, Department of Radiology and Research Institute of Radiological Science, College of Medicine, Seoul (Korea, Republic of); Yonsei University, Department of Radiology, College of Medicine, Seoul (Korea, Republic of); Chang, Jong Hee; Kang, Seok-Gu [Yonsei University College of Medicine, Department of Neurosurgery, Seoul (Korea, Republic of); Kim, Se Hoon [Yonsei University College of Medicine, Department of Pathology, Seoul (Korea, Republic of); Zhou, Jinyuan [Johns Hopkins University School of Medicine, Division of MRI Research, Department of Radiology, Baltimore, MD (United States)

    2018-01-15

    To investigate the difference in amide proton transfer (APT)-weighted signals between benign and atypical meningiomas and determine the value of APT imaging for differentiating the two. Fifty-seven patients with pathologically diagnosed meningiomas (benign, 44; atypical, 13), who underwent preoperative MRI with APT imaging between December 2014 and August 2016 were included. We compared normalised magnetisation transfer ratio asymmetry (nMTR{sub asym}) values between benign and atypical meningiomas on APT-weighted images. Conventional MRI features were qualitatively assessed. Both imaging features were evaluated by multivariable logistic regression analysis. The discriminative value of MRI with and without nMTR{sub asym} was evaluated. The nMTR{sub asym} of atypical meningiomas was significantly greater than that of benign meningiomas (2.46% vs. 1.67%; P < 0.001). In conventional MR images, benign and atypical meningiomas exhibited significant differences in maximum tumour diameter, non-skull base location, and heterogeneous enhancement. On multivariable logistic regression analysis, high nMTR{sub asym} was an independent predictor of atypical meningiomas (adjusted OR, 11.227; P = 0.014). The diagnostic performance of MRI improved with nMTR{sub asym} for predicting atypical meningiomas. Atypical meningiomas exhibited significantly higher APT-weighted signal intensities than benign meningiomas. The discriminative value of conventional MRI improved significantly when combined with APT imaging for diagnosis of atypical meningioma. (orig.)

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

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

    CSIR Research Space (South Africa)

    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...

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

    OpenAIRE

    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...

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

    Science.gov (United States)

    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.

  12. Differentiated thyroid carcinomas: prediction of tumor invasion with MR imaging

    International Nuclear Information System (INIS)

    Takashima, S.; Takayama, F.; Wang, Q.; Kawakami, S.; Saito, A.; Sone, S.; Kobayashi, S.

    2000-01-01

    Purpose: To assess diagnostic accuracy for tumor invasion of surrounding organs by measurement of tumor circumferences on MR images in patients with differentiated thyroid carcinomas. Material and Methods: Surgical and MR imaging findings in 50 patients with differentiated thyroid carcinoma (43 primary, 7 recurrent lesions) were retrospectively reviewed. The degrees of circumference of tumor encroachment to the organs were measured, and the measurements and morphologic diagnosis of tumor invasion made by a head and neck radiologist were compared with surgical and pathologic findings using receiver operating characteristic curves. Results: Diagnosis of tumor invasion by the radiologist was superior to the measurements of the carotid artery and cartilage, while the reverse was true for the trachea and esophagus. However, no statistical differences were noted between them for each structure. Optimal thresholds for tumor invasion were 90 deg or more for the cartilage (94% accuracy) and esophagus (86% accuracy), 135 deg or more for the trachea (86% accuracy), and 225 deg or more for the carotid artery (90% accuracy). Conclusion: Tumor invasion was more accurately diagnosed by measurement of tumor circumferences of each organ on MR images

  13. Automated oral cancer identification using histopathological images: a hybrid feature extraction paradigm.

    Science.gov (United States)

    Krishnan, M Muthu Rama; Venkatraghavan, Vikram; Acharya, U Rajendra; Pal, Mousumi; Paul, Ranjan Rashmi; Min, Lim Choo; Ray, Ajoy Kumar; Chatterjee, Jyotirmoy; Chakraborty, Chandan

    2012-02-01

    Oral cancer (OC) is the sixth most common cancer in the world. In India it is the most common malignant neoplasm. Histopathological images have widely been used in the differential diagnosis of normal, oral precancerous (oral sub-mucous fibrosis (OSF)) and cancer lesions. However, this technique is limited by subjective interpretations and less accurate diagnosis. The objective of this work is to improve the classification accuracy based on textural features in the development of a computer assisted screening of OSF. The approach introduced here is to grade the histopathological tissue sections into normal, OSF without Dysplasia (OSFWD) and OSF with Dysplasia (OSFD), which would help the oral onco-pathologists to screen the subjects rapidly. The biopsy sections are stained with H&E. The optical density of the pixels in the light microscopic images is recorded and represented as matrix quantized as integers from 0 to 255 for each fundamental color (Red, Green, Blue), resulting in a M×N×3 matrix of integers. Depending on either normal or OSF condition, the image has various granular structures which are self similar patterns at different scales termed "texture". We have extracted these textural changes using Higher Order Spectra (HOS), Local Binary Pattern (LBP), and Laws Texture Energy (LTE) from the histopathological images (normal, OSFWD and OSFD). These feature vectors were fed to five different classifiers: Decision Tree (DT), Sugeno Fuzzy, Gaussian Mixture Model (GMM), K-Nearest Neighbor (K-NN), Radial Basis Probabilistic Neural Network (RBPNN) to select the best classifier. Our results show that combination of texture and HOS features coupled with Fuzzy classifier resulted in 95.7% accuracy, sensitivity and specificity of 94.5% and 98.8% respectively. Finally, we have proposed a novel integrated index called Oral Malignancy Index (OMI) using the HOS, LBP, LTE features, to diagnose benign or malignant tissues using just one number. We hope that this OMI can

  14. Time-lapse Raman imaging of osteoblast differentiation

    Science.gov (United States)

    Hashimoto, Aya; Yamaguchi, Yoshinori; Chiu, Liang-Da; Morimoto, Chiaki; Fujita, Katsumasa; Takedachi, Masahide; Kawata, Satoshi; Murakami, Shinya; Tamiya, Eiichi

    2015-07-01

    Osteoblastic mineralization occurs during the early stages of bone formation. During this mineralization, hydroxyapatite (HA), a major component of bone, is synthesized, generating hard tissue. Many of the mechanisms driving biomineralization remain unclear because the traditional biochemical assays used to investigate them are destructive techniques incompatible with viable cells. To determine the temporal changes in mineralization-related biomolecules at mineralization spots, we performed time-lapse Raman imaging of mouse osteoblasts at a subcellular resolution throughout the mineralization process. Raman imaging enabled us to analyze the dynamics of the related biomolecules at mineralization spots throughout the entire process of mineralization. Here, we stimulated KUSA-A1 cells to differentiate into osteoblasts and conducted time-lapse Raman imaging on them every 4 hours for 24 hours, beginning 5 days after the stimulation. The HA and cytochrome c Raman bands were used as markers for osteoblastic mineralization and apoptosis. From the Raman images successfully acquired throughout the mineralization process, we found that β-carotene acts as a biomarker that indicates the initiation of osteoblastic mineralization. A fluctuation of cytochrome c concentration, which indicates cell apoptosis, was also observed during mineralization. We expect time-lapse Raman imaging to help us to further elucidate osteoblastic mineralization mechanisms that have previously been unobservable.

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

    Science.gov (United States)

    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.

  16. Functional features of gene expression profiles differentiating gastrointestinal stromal tumours according to KIT mutations and expression

    International Nuclear Information System (INIS)

    Ostrowski, Jerzy; Dobosz, Anna Jerzak Vel; Jarosz, Dorota; Ruka, Wlodzimierz; Wyrwicz, Lucjan S; Polkowski, Marcin; Paziewska, Agnieszka; Skrzypczak, Magdalena; Goryca, Krzysztof; Rubel, Tymon; Kokoszyñska, Katarzyna; Rutkowski, Piotr; Nowecki, Zbigniew I

    2009-01-01

    Gastrointestinal stromal tumours (GISTs) represent a heterogeneous group of tumours of mesenchymal origin characterized by gain-of-function mutations in KIT or PDGFRA of the type III receptor tyrosine kinase family. Although mutations in either receptor are thought to drive an early oncogenic event through similar pathways, two previous studies reported the mutation-specific gene expression profiles. However, their further conclusions were rather discordant. To clarify the molecular characteristics of differentially expressed genes according to GIST receptor mutations, we combined microarray-based analysis with detailed functional annotations. Total RNA was isolated from 29 frozen gastric GISTs and processed for hybridization on GENECHIP ® HG-U133 Plus 2.0 microarrays (Affymetrix). KIT and PDGFRA were analyzed by sequencing, while related mRNA levels were analyzed by quantitative RT-PCR. Fifteen and eleven tumours possessed mutations in KIT and PDGFRA, respectively; no mutation was found in three tumours. Gene expression analysis identified no discriminative profiles associated with clinical or pathological parameters, even though expression of hundreds of genes differentiated tumour receptor mutation and expression status. Functional features of genes differentially expressed between the two groups of GISTs suggested alterations in angiogenesis and G-protein-related and calcium signalling. Our study has identified novel molecular elements likely to be involved in receptor-dependent GIST development and allowed confirmation of previously published results. These elements may be potential therapeutic targets and novel markers of KIT mutation status

  17. Nicotinamide: a vitamin able to shift macrophage differentiation toward macrophages with restricted inflammatory features.

    Science.gov (United States)

    Weiss, Ronald; Schilling, Erik; Grahnert, Anja; Kölling, Valeen; Dorow, Juliane; Ceglarek, Uta; Sack, Ulrich; Hauschildt, Sunna

    2015-11-01

    The differentiation of human monocytes into macrophages is influenced by environmental signals. Here we asked in how far nicotinamide (NAM), a vitamin B3 derivative known to play a major role in nicotinamide adenine dinucleotide (NAD)-mediated signaling events, is able to modulate monocyte differentiation into macrophages developed in the presence of granulocyte macrophage colony-stimulating factor (GM-MØ) or macrophage colony-stimulating factor (M-MØ). We found that GM-MØ undergo biochemical, morphological and functional modifications in response to NAM, whereas M-MØ were hardly affected. GM-MØ exposed to NAM acquired an M-MØ-like structure while the LPS-induced production of pro-inflammatory cytokines and COX-derived eicosanoids were down-regulated. In contrast, NAM had no effect on the production of IL-10 or the cytochrome P450-derived eicosanoids. Administration of NAM enhanced intracellular NAD concentrations; however, it did not prevent the LPS-mediated drain on NAD pools. In search of intracellular molecular targets of NAM known to be involved in LPS-induced cytokine and eicosanoid synthesis, we found NF-κB activity to be diminished. In conclusion, our data show that vitamin B3, when present during the differentiation of monocytes into GM-MØ, interferes with biochemical pathways resulting in strongly reduced pro-inflammatory features. © The Author(s) 2015.

  18. Differential diagnosis of scrub typhus meningitis from tuberculous meningitis using clinical and laboratory features.

    Science.gov (United States)

    Valappil, Ashraf V; Thiruvoth, Sohanlal; Peedikayil, Jabir M; Raghunath, Praveenkumar; Thekkedath, Manojan

    2017-12-01

    The involvement of the central nervous system in the form of meningitis or meningoencephalitis is common in scrub typhus and is an important differential diagnosis of other lymphocytic meningitis like tuberculous meningitis (TBM). The aim of this study was to identify the clinical and laboratory parameters that may be helpful in differentiating scrub typhus meningitis from TBM. We compared of the clinical and laboratory features of 57 patients admitted with scrub typhus meningitis or TBM during a 3-year period. Patients who had abnormal cerebrospinal fluid (CSF) and positive scrub typhus enzyme-linked immunosorbent assay serology (n=28) were included in the scrub typhus meningitis group, while the TBM group included those who satisfied the consensus diagnostic criteria of TBM (n=29). Compared with the TBM group, the mean duration of symptoms was less in patients with scrub typhus meningitis, who also had a lower magnitude of neurological deficits, such as altered mental status and cranial nerve and motor deficits. Patients with scrub typhus meningitis had a lower CSF white blood-cell count (WBC) than the TBM group (130.8±213 195±175 cells/mm 3 , P=0.002), lower CSF protein elevation (125±120 vs. 195.2±108.2mg/dl, P=0.002), and higher CSF sugar (70.1±32.4 vs. 48.7±23.4mg/dl, P=0.006). Features predictive of the diagnosis of scrub typhus meningitis included the absence of neurological impairment at presentation, blood serum glutamic-oxaloacetic transaminase>40 international units (IU)/L, serum glutamic-pyruvic transaminase>60 IU/L, total blood leukocyte count>10,000/mm 3 , CSF protein50mg/dl, CSF WBC<100 cells/mm 3 . All patients with scrub typhus meningitis recovered completely following doxycycline therapy CONCLUSIONS: This study suggests that, clinical features, including duration of fever, neurological deficits at presentation and laboratory parameters such as CSF pleocytosis,CSF protein elevation, CSF sugar levels and liver enzyme values are helpful in

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  1. Differential role of molten globule and protein folding in distinguishing unique features of botulinum neurotoxin.

    Science.gov (United States)

    Kumar, Raj; Kukreja, Roshan V; Cai, Shuowei; Singh, Bal R

    2014-06-01

    Botulinum neurotoxins (BoNTs) are proteins of great interest not only because of their extreme toxicity but also paradoxically for their therapeutic applications. All the known serotypes (A-G) have varying degrees of longevity and potency inside the neuronal cell. Differential chemical modifications such as phosphorylation and ubiquitination have been suggested as possible mechanisms for their longevity, but the molecular basis of the longevity remains unclear. Since the endopeptidase domain (light chain; LC) of toxin apparently survives inside the neuronal cells for months, it is important to examine the structural features of this domain to understand its resistance to intracellular degradation. Published crystal structures (both botulinum neurotoxins and endopeptidase domain) have not provided adequate explanation for the intracellular longevity of the domain. Structural features obtained from spectroscopic analysis of LCA and LCB were similar, and a PRIME (PReImminent Molten Globule Enzyme) conformation appears to be responsible for their optimal enzymatic activity at 37°C. LCE, on the other hand, was although optimally active at 37°C, but its active conformation differed from the PRIME conformation of LCA and LCB. This study establishes and confirms our earlier finding that an optimally active conformation of these proteins in the form of PRIME exists for the most poisonous poison, botulinum neurotoxin. There are substantial variations in the structural and functional characteristics of these active molten globule related structures among the three BoNT endopeptidases examined. These differential conformations of LCs are important in understanding the fundamental structural features of proteins, and their possible connection to intracellular longevity could provide significant clues for devising new countermeasures and effective therapeutics. Copyright © 2014 Elsevier B.V. All rights reserved.

  2. Multiphase contrast-enhanced magnetic resonance imaging features of Bacillus Calmette-Guerin-induced granulomatous prostatitis in five patients

    Energy Technology Data Exchange (ETDEWEB)

    Kawada, Hiroshi; Kanematsu, Masayuki; Goshima, Satoshi; Kondo, Hiroshi; Watanabe, Haruo; Noda, Yoshifumi; Tanahashi, Yukichi; Kawai, Nobuyuki; Hoshi, Hiroaki [Gifu University Hospital, Gifu (Japan)

    2015-04-15

    To evaluate the multiphase contrast-enhanced magnetic resonance (MR) imaging features of Bacillus Calmette-Guerin (BCG)-induced granulomatous prostatitis (GP). Magnetic resonance images obtained from five patients with histopathologically proven BCG-induced GP were retrospectively analyzed for tumor location, size, signal intensity on T2-weighted images (T2WI) and diffusion-weighted images (DWI), apparent diffusion coefficient (ADC) value, and appearance on gadolinium-enhanced multiphase images. MR imaging findings were compared with histopathological findings. Bacillus Calmette-Guerin-induced GP (size range, 9-40 mm; mean, 21.2 mm) were identified in the peripheral zone in all patients. The T2WI showed lower signal intensity compared with the normal peripheral zone. The DWIs demonstrated high signal intensity and low ADC values (range, 0.44-0.68 x 10(-3) mm2/sec; mean, 0.56 x 10(-3) mm2/sec), which corresponded to GP. Gadolinium-enhanced multiphase MR imaging performed in five patients showed early and prolonged ring enhancement in all cases of GP. Granulomatous tissues with central caseation necrosis were identified histologically, which corresponded to ring enhancement and a central low intensity area on gadolinium-enhanced MR imaging. The findings on T2WI, DWI, and gadolinium-enhanced images became gradually obscured with time. Bacillus Calmette-Guerin-induced GP demonstrates early and prolonged ring enhancement on gadolinium-enhanced MR imaging which might be a key finding to differentiate it from prostate cancer.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

  5. Differential Spatio-temporal Multiband Satellite Image Clustering using K-means Optimization With Reinforcement Programming

    Directory of Open Access Journals (Sweden)

    Irene Erlyn Wina Rachmawan

    2015-06-01

    Full Text Available Deforestration is one of the crucial issues in Indonesia because now Indonesia has world's highest deforestation rate. In other hand, multispectral image delivers a great source of data for studying spatial and temporal changeability of the environmental such as deforestration area. This research present differential image processing methods for detecting nature change of deforestration. Our differential image processing algorithms extract and indicating area automatically. The feature of our proposed idea produce extracted information from multiband satellite image and calculate the area of deforestration by years with calculating data using temporal dataset. Yet, multiband satellite image consists of big data size that were difficult to be handled for segmentation. Commonly, K- Means clustering is considered to be a powerfull clustering algorithm because of its ability to clustering big data. However K-Means has sensitivity of its first generated centroids, which could lead into a bad performance. In this paper we propose a new approach to optimize K-Means clustering using Reinforcement Programming in order to clustering multispectral image. We build a new mechanism for generating initial centroids by implementing exploration and exploitation knowledge from Reinforcement Programming. This optimization will lead a better result for K-means data cluster. We select multispectral image from Landsat 7 in past ten years in Medawai, Borneo, Indonesia, and apply two segmentation areas consist of deforestration land and forest field. We made series of experiments and compared the experimental results of K-means using Reinforcement Programming as optimizing initiate centroid and normal K-means without optimization process. Keywords: Deforestration, Multispectral images, landsat, automatic clustering, K-means.

  6. Tularemia in differential diagnosis of cervical lymphadenopathy: cytologic features of tularemia lymphadenitis.

    Science.gov (United States)

    Markoc, Fatma; Koseoglu, Resid Dogan; Koc, Sema; Gurbuzler, Levent

    2014-01-01

    Tularemia can cause cervical lymphadenopathy. Fine-needle aspiration (FNA) cytology is the first step in the workup for cervical lymphadenopathy; however, little has been published regarding the cytomorphological features of tularemia lymphadenitis. The aim of this study was to evaluate the FNA cytology of tularemia lymphadenitis. Review of medical records identified 36 patients with serologically proven tularemia, and who had undergone lymph node FNA. In each case, the original May-Grünwald-Giemsa-stained FNA smears from enlarged cervical lymph node were reevaluated. Suppuration and cytolysis were frequent cytological findings. Twenty-three (63.8%) of the 36 cases were assessed as suppurative inflammation. In 10 of these cases (27.8% of the total), cytolysis was prominent. In 7 cases (19.4%) the smears featured microgranulomas as well as suppuration, and 2 of these (5.6%) also featured giant cells. In 1 case (2.8%), there was caseous necrosis. In 2 cases (5.6%), the cytopathological findings were consistent with reactive lymphoid hyperplasia. Three aspirates (8.3%) were inadequate for evaluation. Cytopathological findings on FNA of tularemia lymphadenitis are nonspecific; however, in regions where tularemia is endemic, this disease should be considered in the differential diagnosis for suppurative lymphadenitis. © 2013 S. Karger AG, Basel.

  7. Combining Landform Thematic Layer and Object-Oriented Image Analysis to Map the Surface Features of Mountainous Flood Plain Areas

    Science.gov (United States)

    Chuang, H.-K.; Lin, M.-L.; Huang, W.-C.

    2012-04-01

    The Typhoon Morakot on August 2009 brought more than 2,000 mm of cumulative rainfall in southern Taiwan, the extreme rainfall event caused serious damage to the Kaoping River basin. The losses were mostly blamed on the landslides along sides of the river, and shifting of the watercourse even led to the failure of roads and bridges, as well as flooding and levees damage happened around the villages on flood bank and terraces. Alluvial fans resulted from debris flow of stream feeders blocked the main watercourse and debris dam was even formed and collapsed. These disasters have highlighted the importance of identification and map the watercourse alteration, surface features of flood plain area and artificial structures soon after the catastrophic typhoon event for natural hazard mitigation. Interpretation of remote sensing images is an efficient approach to acquire spatial information for vast areas, therefore making it suitable for the differentiation of terrain and objects near the vast flood plain areas in a short term. The object-oriented image analysis program (Definiens Developer 7.0) and multi-band high resolution satellite images (QuickBird, DigitalGlobe) was utilized to interpret the flood plain features from Liouguei to Baolai of the the Kaoping River basin after Typhoon Morakot. Object-oriented image interpretation is the process of using homogenized image blocks as elements instead of pixels for different shapes, textures and the mutual relationships of adjacent elements, as well as categorized conditions and rules for semi-artificial interpretation of surface features. Digital terrain models (DTM) are also employed along with the above process to produce layers with specific "landform thematic layers". These layers are especially helpful in differentiating some confusing categories in the spectrum analysis with improved accuracy, such as landslides and riverbeds, as well as terraces, riverbanks, which are of significant engineering importance in disaster

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

    International Nuclear Information System (INIS)

    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.

  9. Differentiation of intrahepatic mass-forming cholangiocarcinoma from hepatocellular carcinoma on gadoxetic acid-enhanced liver MR imaging

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Rihyeon; Shin, Cheong-Il; Yoon, Jeong Hee; Joo, Ijin; Kim, Seong Ho; Hwang, Inpyeong [Seoul National University Hospital, Department of Radiology, Seoul (Korea, Republic of); Lee, Jeong Min; Han, Joon Koo [Seoul National University Hospital, Department of Radiology, Seoul (Korea, Republic of); Seoul National University Hospital, Institute of Radiation Medicine, Seoul (Korea, Republic of); Lee, Eun Sun; Choi, Byung Ihn [Chung-Ang University Hospital, Department of Radiology, Seoul (Korea, Republic of)

    2016-06-15

    To determine the different imaging features of intrahepatic mass-forming cholangiocarcinoma (IMCC) from hepatocellular carcinoma (HCC) on gadoxetic acid-enhanced magnetic resonance imaging (MRI). This retrospective study was institutional review board approved and the requirement for informed consent was waived. Patients who underwent gadoxetic acid-enhanced MRI with histologically confirmed IMCCs (n = 46) or HCCs (n = 58) were included. Imaging features of IMCCs and HCCs on gadoxetic acid-enhanced MRI including T2- and T1-weighted, diffusion weighted images, dynamic study and hepatobiliary phase (HBP) images were analyzed. Univariate and multivariate logistic regression analyses were performed to identify relevant differentiating features between IMCCs and HCCs. Multivariate analysis revealed heterogeneous T2 signal intensity and a hypointense rim on the HBP as suggestive findings of IMCCs and the wash-in and ''portal wash-out'' enhancement pattern as well as focal T1 high signal intensity foci as indicative of HCCs (all, p < 0.05). When we combined any three of the above four imaging features, we were able to diagnose IMCCs with 94 % (43/46) sensitivity and 86 % (50/58) specificity. Combined interpretation of enhancement characteristics including HBP images, morphologic features, and strict application of the ''portal wash-out'' pattern helped more accurate discrimination of IMCCs from HCCs. (orig.)

  10. Imaging features of diffuse pulmonary hemorrhage; Roentgenmorphologie von diffusen Lungenhaemorrhagien

    Energy Technology Data Exchange (ETDEWEB)

    Schmit, M.; Vogel, W.; Horger, M.

    2006-09-15

    There are diverse etiologies of diffuse pulmonary hemorrhage, so specific diagnosis may be difficult. Conventional radiography tends to be misleading as hemoptysis may lacking in patients with hemorrhagic anemia. Diffuse pulmonary hemorrhage should be differentiated from focal pulmonary hemorrhage resulting from chronic bronchitis, bronchiectasis, active infection (tuberculosis) neoplasia, trauma, or embolism. (orig.)

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    KAUST Repository

    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.

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

    KAUST Repository

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  17. Global image feature extraction using slope pattern spectra

    CSIR Research Space (South Africa)

    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...

  18. Caroli's disease: magnetic resonance imaging features

    Energy Technology Data Exchange (ETDEWEB)

    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.)

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

    International Nuclear Information System (INIS)

    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

  20. New feature of the neutron color image intensifier

    Science.gov (United States)

    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.

  1. New feature of the neutron color image intensifier

    International Nuclear Information System (INIS)

    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.

  2. Statistical methods for detecting differentially abundant features in clinical metagenomic samples.

    Directory of Open Access Journals (Sweden)

    James Robert White

    2009-04-01

    Full Text Available Numerous studies are currently underway to characterize the microbial communities inhabiting our world. These studies aim to dramatically expand our understanding of the microbial biosphere and, more importantly, hope to reveal the secrets of the complex symbiotic relationship between us and our commensal bacterial microflora. An important prerequisite for such discoveries are computational tools that are able to rapidly and accurately compare large datasets generated from complex bacterial communities to identify features that distinguish them.We present a statistical method for comparing clinical metagenomic samples from two treatment populations on the basis of count data (e.g. as obtained through sequencing to detect differentially abundant features. Our method, Metastats, employs the false discovery rate to improve specificity in high-complexity environments, and separately handles sparsely-sampled features using Fisher's exact test. Under a variety of simulations, we show that Metastats performs well compared to previously used methods, and significantly outperforms other methods for features with sparse counts. We demonstrate the utility of our method on several datasets including a 16S rRNA survey of obese and lean human gut microbiomes, COG functional profiles of infant and mature gut microbiomes, and bacterial and viral metabolic subsystem data inferred from random sequencing of 85 metagenomes. The application of our method to the obesity dataset reveals differences between obese and lean subjects not reported in the original study. For the COG and subsystem datasets, we provide the first statistically rigorous assessment of the differences between these populations. The methods described in this paper are the first to address clinical metagenomic datasets comprising samples from multiple subjects. Our methods are robust across datasets of varied complexity and sampling level. While designed for metagenomic applications, our software

  3. Differential clinicopathological features in microsatellite instability-positive colorectal cancers depending on CIMP status.

    Science.gov (United States)

    Bae, Jeong Mo; Kim, Mi Jung; Kim, Jung Ho; Koh, Jae Moon; Cho, Nam-Yun; Kim, Tae-You; Kang, Gyeong Hoon

    2011-07-01

    Microsatellite instability-positive (MSI+) colorectal cancers (CRCs) are divided into CpG island methylator phenotype-positive (CIMP+) and CpG island methylator phenotype-negative (CIMP-) tumors. The repertoire of inactivated genes in CIMP+/MSI+ CRCs overlaps with but is likely to differ from that of CIMP-/MSI+ CRCs. Because epigenotypic differences are likely to be manifested as phenotypic differences, CIMP+/MSI+ CRCs are expected to differ from CIMP-/MSI+ CRCs in some clinicopathological features. This study aimed to characterize both common and different features between the two subtypes. A total of 72 MSI+ CRCs were analyzed for their methylation status in eight CIMP panel markers using MethyLight assay. CIMP+/MSI+ and CIMP-/MSI+ CRCs were compared regarding clinicopathologic features and mutation in KRAS/BRAF. An independent set of MSI+ CRCs (n = 97) was analyzed for their relationship of CIMP+ status with clinical outcome. Eighteen cases (25%) were CIMP+, and this CIMP+ subtype was highly correlated with older age (P CIMP-/MSI+ CRCs (18.5%, P = 0.057). CIMP+/MSI+ CRCs were closely associated with poor differentiation, medullary appearance, signet ring cell appearance, and acinar-form appearance, whereas the CIMP-/MSI+ subtype was closely associated with intraglandular eosinophilic mucin and stratified nuclei (all P values CIMP+/MSI+ CRCs showed worse overall survival than patients with CIMP-/MSI+ CRCs. Our results demonstrate heterogeneity in the clinicopathological features of MSI+ CRCs depending on CIMP status. The observation that CIMP+ and CIMP- subtypes showed different clinical behaviors may provide a clue for establishing subtype-specific therapeutic strategies for these two subtypes.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

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

    International Nuclear Information System (INIS)

    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

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    DEFF Research Database (Denmark)

    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...

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    OpenAIRE

    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...

  12. Hepatocellular carcinoma with bile duct tumor thrombi: Correlation of magnetic resonance imaging features to histopathologic manifestations

    Energy Technology Data Exchange (ETDEWEB)

    Liu Qingyu, E-mail: liu.qingyu@163.co [Department of Radiology, Second Affiliated Hospital of Sun Yat-sen University, 107 Yan Jiang Xi Road, Guangzhou, 510120, Guangdong Province (China); Chen Jianyu, E-mail: chenjianyu5562@sina.co [Department of Radiology, The Second Affiliated Hospital of Sun Yat-sen University, 107 Yan Jiang Xi Road, Guangzhou, 510120, Guangdong Province (China); Li Haigang, E-mail: lhg00433@yahoo.com.c [Department of Pathology, Second Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong Province (China); Liang Biling, E-mail: liangbl@163.ne [Department of Radiology, Second Affiliated Hospital of Sun Yat-sen University, 107 Yan Jiang Xi Road, Guangzhou, 510120, Guangdong Province (China); Zhang Lei, E-mail: zhanglei646@126.co [Department of Hepatobiliary Surgery, Second Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong Province (China); Hu Tao, E-mail: htwuaini@hotmail.co [Department of Radiology, Second Affiliated Hospital of Sun Yat-sen University, 107 Yan Jiang Xi Road, Guangzhou, 510120, Guangdong Province (China)

    2010-10-15

    Purpose: This study was to analyze the magnetic resonance imaging (MRI) features of hepatocellular carcinoma (HCC) with bile duct tumor thrombi, and explore their correlations to histopathology to improve the accuracy of diagnosis. Materials and methods: 21 patients with pathologically confirmed HCC with bile duct tumor thrombi was performed with a superconducting 1.5-T MR imager within two weeks before operation. Magnetic resonance cholangiopancreatography (MRCP) was performed on 18 patients. Images were retrospectively assessed for the size, location and MRI manifestations of HCC lesions and associated bile duct tumor thrombi. The differentiation of HCC lesions and the pathologic changes of bile duct tumor thrombi were retrospectively analyzed under microscope. Results: The average diameter of HCC lesions was 5.8 {+-} 2.8 cm, and {<=}5.0 cm in nine cases. Capsule formation was observed on MRI or pathology in 4 cases of HCC (19%). Of the 21 cases with bile duct tumor thrombi, 20 were clearly presented on MRI as cord-like or columnar masses in the bile duct with proximal cholangiectasis. The tumor thrombi showed slightly hypointense on T1WI and slightly hyperintense on T2WI. On enhanced scan, three cases of tumor thrombi, which were mainly consisted of necrotic tissue, did not show enhancement; 17 cases, which were mainly consisted of cancer cells, showed mild or moderate enhancement. On magnetic resonance cholangiopancreatogram (MRCP), 14 cases of tumor thrombi presented as filling defect in the bile duct, abrupt obstruction of the bile duct, and cholangiectasis above the obstruction; four presented as dilated intra-hepatic bile ducts with missing common bile duct. Of the 21 patients, 16 had biliary hemorrhage; three also had tumor thrombi in the portal vein. Seventeen of the 21 HCC with biliary thrombi were poorly differentiated, unencapsulated and with an invasive growth. Nineteen of 21 bile duct tumor thrombi did not invade the bile duct wall and could be

  13. Hepatocellular carcinoma with bile duct tumor thrombi: Correlation of magnetic resonance imaging features to histopathologic manifestations

    International Nuclear Information System (INIS)

    Liu Qingyu; Chen Jianyu; Li Haigang; Liang Biling; Zhang Lei; Hu Tao

    2010-01-01

    Purpose: This study was to analyze the magnetic resonance imaging (MRI) features of hepatocellular carcinoma (HCC) with bile duct tumor thrombi, and explore their correlations to histopathology to improve the accuracy of diagnosis. Materials and methods: 21 patients with pathologically confirmed HCC with bile duct tumor thrombi was performed with a superconducting 1.5-T MR imager within two weeks before operation. Magnetic resonance cholangiopancreatography (MRCP) was performed on 18 patients. Images were retrospectively assessed for the size, location and MRI manifestations of HCC lesions and associated bile duct tumor thrombi. The differentiation of HCC lesions and the pathologic changes of bile duct tumor thrombi were retrospectively analyzed under microscope. Results: The average diameter of HCC lesions was 5.8 ± 2.8 cm, and ≤5.0 cm in nine cases. Capsule formation was observed on MRI or pathology in 4 cases of HCC (19%). Of the 21 cases with bile duct tumor thrombi, 20 were clearly presented on MRI as cord-like or columnar masses in the bile duct with proximal cholangiectasis. The tumor thrombi showed slightly hypointense on T1WI and slightly hyperintense on T2WI. On enhanced scan, three cases of tumor thrombi, which were mainly consisted of necrotic tissue, did not show enhancement; 17 cases, which were mainly consisted of cancer cells, showed mild or moderate enhancement. On magnetic resonance cholangiopancreatogram (MRCP), 14 cases of tumor thrombi presented as filling defect in the bile duct, abrupt obstruction of the bile duct, and cholangiectasis above the obstruction; four presented as dilated intra-hepatic bile ducts with missing common bile duct. Of the 21 patients, 16 had biliary hemorrhage; three also had tumor thrombi in the portal vein. Seventeen of the 21 HCC with biliary thrombi were poorly differentiated, unencapsulated and with an invasive growth. Nineteen of 21 bile duct tumor thrombi did not invade the bile duct wall and could be easily

  14. Perfusion MR imaging for differentiation of benign and malignant meningiomas

    International Nuclear Information System (INIS)

    Zhang, Hao; Roediger, Lars A.; Oudkerk, Matthijs; Shen, Tianzhen; Miao, Jingtao

    2008-01-01

    Our purpose was to determine whether perfusion MR imaging can be used to differentiate benign and malignant meningiomas on the basis of the differences in perfusion of tumor parenchyma and/or peritumoral edema. A total of 33 patients with preoperative meningiomas (25 benign and 8 malignant) underwent conventional and dynamic susceptibility contrast perfusion MR imaging. Maximal relative cerebral blood volume (rCBV) and the corresponding relative mean time to enhance (rMTE) (relative to the contralateral normal white matter) in both tumor parenchyma and peritumoral edema were measured. The independent samples t-test was used to determine whether there was a statistically significant difference in the mean rCBV and rMTE ratios between benign and malignant meningiomas. The mean maximal rCBV values of benign and malignant meningiomas were 7.16±4.08 (mean±SD) and 5.89±3.86, respectively, in the parenchyma, and 1.05±0.96 and 3.82±1.39, respectively, in the peritumoral edema. The mean rMTE values were 1.16±0.24 and 1.30±0.32, respectively, in the parenchyma, and 0.91±0.25 and 1.24±0.35, respectively, in the peritumoral edema. The differences in rCBV and rMTE values between benign and malignant meningiomas were not statistically significant (P>0.05) in the parenchyma, but both were statistically significant (P<0.05) in the peritumoral edema. Perfusion MR imaging can provide useful information on meningioma vascularity which is not available from conventional MRI. Measurement of maximal rCBV and corresponding rMTE values in the peritumoral edema is useful in the preoperative differentiation between benign and malignant meningiomas. (orig.)

  15. Perfusion MR imaging for differentiation of benign and malignant meningiomas

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Hao [University of Groningen, Department of Radiology, University Medical Center Groningen, Groningen (Netherlands); Shanghai Jiaotong University, Department of Radiology, First People' s Hospital, Shanghai (China); Roediger, Lars A.; Oudkerk, Matthijs [University of Groningen, Department of Radiology, University Medical Center Groningen, Groningen (Netherlands); Shen, Tianzhen [Fudan University, Department of Radiology, Huashan Hospital, Shanghai (China); Miao, Jingtao [Shanghai Jiaotong University, Department of Radiology, First People' s Hospital, Shanghai (China)

    2008-06-15

    Our purpose was to determine whether perfusion MR imaging can be used to differentiate benign and malignant meningiomas on the basis of the differences in perfusion of tumor parenchyma and/or peritumoral edema. A total of 33 patients with preoperative meningiomas (25 benign and 8 malignant) underwent conventional and dynamic susceptibility contrast perfusion MR imaging. Maximal relative cerebral blood volume (rCBV) and the corresponding relative mean time to enhance (rMTE) (relative to the contralateral normal white matter) in both tumor parenchyma and peritumoral edema were measured. The independent samples t-test was used to determine whether there was a statistically significant difference in the mean rCBV and rMTE ratios between benign and malignant meningiomas. The mean maximal rCBV values of benign and malignant meningiomas were 7.16{+-}4.08 (mean{+-}SD) and 5.89{+-}3.86, respectively, in the parenchyma, and 1.05{+-}0.96 and 3.82{+-}1.39, respectively, in the peritumoral edema. The mean rMTE values were 1.16{+-}0.24 and 1.30{+-}0.32, respectively, in the parenchyma, and 0.91{+-}0.25 and 1.24{+-}0.35, respectively, in the peritumoral edema. The differences in rCBV and rMTE values between benign and malignant meningiomas were not statistically significant (P>0.05) in the parenchyma, but both were statistically significant (P<0.05) in the peritumoral edema. Perfusion MR imaging can provide useful information on meningioma vascularity which is not available from conventional MRI. Measurement of maximal rCBV and corresponding rMTE values in the peritumoral edema is useful in the preoperative differentiation between benign and malignant meningiomas. (orig.)

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    International Nuclear Information System (INIS)

    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

  18. Clinicopathological features of alpha-fetoprotein producing early gastric cancer with enteroblastic differentiation.

    Science.gov (United States)

    Matsumoto, Kohei; Ueyama, Hiroya; Matsumoto, Kenshi; Akazawa, Yoichi; Komori, Hiroyuki; Takeda, Tsutomu; Murakami, Takashi; Asaoka, Daisuke; Hojo, Mariko; Tomita, Natsumi; Nagahara, Akihito; Kajiyama, Yoshiaki; Yao, Takashi; Watanabe, Sumio

    2016-09-28

    To investigate clinicopathological features of early stage gastric cancer with enteroblastic differentiation (GCED). We retrospectively investigated data on 6 cases of early stage GCED and 186 cases of early stage conventional gastric cancer (CGC: well or moderately differentiated adenocarcinoma) who underwent endoscopic submucosal dissection or endoscopic mucosal resection from September 2011 to February 2015 in our hospital. GCED was defined as a tumor having a primitive intestine-like structure composed of cuboidal or columnar cells with clear cytoplasm and immunohistochemical positivity for either alpha-fetoprotein, Glypican 3 or SALL4. The following were compared between GCED and CGC: age, gender, location and size of tumor, macroscopic type, ulceration, depth of invasion, lymphatic and venous invasion, positive horizontal and vertical margin, curative resection rate. Six cases (5 males, 1 female; mean age 75.7 years; 6 lesions) of early gastric cancer with a GCED component and 186 cases (139 males, 47 females; mean age 72.7 years; 209 lesions) of early stage CGC were investigated. Mean tumor diameters were similar but rates of submucosal invasion, lymphatic invasion, venous invasion, and non-curative resection were higher in GCED than CGC (66.6% vs 11.4%, 33.3% vs 2.3%, 66.6% vs 0.4%, 83.3% vs 11% respectively, P < 0.01). Deep submucosal invasion was not revealed endoscopically or by preoperative biopsy. Histologically, in GCED the superficial mucosal layer was covered with a CGC component. The GCED component tended to exist in the deeper part of the mucosa to the submucosa by lymphatic and/or venous invasion, without severe stromal reaction. In addition, Glypican 3 was the most sensitive marker for GCED (positivity, 83.3%), immunohistochemically. Even in the early stage GCED has high malignant potential, and preoperative diagnosis is considered difficult. Endoscopists and pathologists should know the clinicopathological features of this highly malignant type

  19. About features of differentiated use of Semipalatinsk Test Site territories in sphere of agroindustrial manufactures

    International Nuclear Information System (INIS)

    Alipbekov, O.A.; Eleshev, R.E.; Saparov, A.S.

    2003-01-01

    Full text: The liquidation experience of pollution consequences in the East-Ural and Chernobyl traces of radioactive falls have shown that recommendations developed with the regard for levels of radioactivity pollution, but without taking into account the features of economy, structure are practically unrealizable. Practical unacceptability of such recommendations lies not in requirements for restriction of lands' use but these requirements could be carried out only by certain economy in size and structure in the given concrete conditions. While drawing up these recommendations two concepts have been wrongly identified; 'specialization of grounds' and 'specialization of economy'. The recommendations were determining a specialization of grounds depending on the level of their radioactive pollution quite validly from the radiating point of view, at the same time they did not take into account the features of land tenure and economy of existing managing structures at all. The detailed analysis of conditions on radioactive traces of experts have convinced that for successful realization on differentiated use of the polluted territory each concrete economy should meet the following specific requirements: - to have enough pure lands to receive foodstuffs of good quality for realization onto a foreign market and internal consumption; - to have such numbers of polluted lands which would give an opportunity to realize production received on them inside the given economy completely; the number of economy and their organizational and administrative structure should be convenient for realization of the precautionary radiation hygienic control. Observance of the above-stated principles of the structural organization of the lands, probably, will allow carrying out the principle of differentiated use of polluted lands practically in the territory of Semipalatinsk test area as well

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

    International Nuclear Information System (INIS)

    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

  1. Large-scale computations on histology images reveal grade-differentiating parameters for breast cancer

    Directory of Open Access Journals (Sweden)

    Katsinis Constantine

    2006-10-01

    Full Text Available Abstract Background Tumor classification is inexact and largely dependent on the qualitative pathological examination of the images of the tumor tissue slides. In this study, our aim was to develop an automated computational method to classify Hematoxylin and Eosin (H&E stained tissue sections based on cancer tissue texture features. Methods Image processing of histology slide images was used to detect and identify adipose tissue, extracellular matrix, morphologically distinct cell nuclei types, and the tubular architecture. The texture parameters derived from image analysis were then applied to classify images in a supervised classification scheme using histologic grade of a testing set as guidance. Results The histologic grade assigned by pathologists to invasive breast carcinoma images strongly correlated with both the presence and extent of cell nuclei with dispersed chromatin and the architecture, specifically the extent of presence of tubular cross sections. The two parameters that differentiated tumor grade found in this study were (1 the number density of cell nuclei with dispersed chromatin and (2 the number density of tubular cross sections identified through image processing as white blobs that were surrounded by a continuous string of cell nuclei. Classification based on subdivisions of a whole slide image containing a high concentration of cancer cell nuclei consistently agreed with the grade classification of the entire slide. Conclusion The automated image analysis and classification presented in this study demonstrate the feasibility of developing clinically relevant classification of histology images based on micro- texture. This method provides pathologists an invaluable quantitative tool for evaluation of the components of the Nottingham system for breast tumor grading and avoid intra-observer variability thus increasing the consistency of the decision-making process.

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

    Science.gov (United States)

    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.

  3. Image Retrieval based on Integration between Color and Geometric Moment Features

    International Nuclear Information System (INIS)

    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.

  4. Improved Feature Detection in Fused Intensity-Range Images with Complex SIFT (ℂSIFT

    Directory of Open Access Journals (Sweden)

    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.

  5. Iris image enhancement for feature recognition and extraction

    CSIR Research Space (South Africa)

    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...

  6. Interpretation of archaeological small-scale features in spectral images

    DEFF Research Database (Denmark)

    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...

  7. Spectral CT imaging in the differential diagnosis of necrotic hepatocellular carcinoma and hepatic abscess

    International Nuclear Information System (INIS)

    Yu, Y.; Guo, L.; Hu, C.; Chen, K.

    2014-01-01

    Aim: To explore the value of CT spectral imaging in the differential diagnosis of necrotic hepatocellular carcinoma (nHCC) and hepatic abscess (HA) during the arterial phase (AP) and portal venous phase (PP). Materials and methods: Sixty patients with 36 nHCCs and 24 HAs underwent spectral CT during AP and PP. Iodine or water concentration were measured and the normalized iodine concentration (NIC) and lesion-normal parenchyma iodine concentration ratio (LNR) were calculated. The two-sample t-test was used to compare quantitative parameters. Two readers qualitatively assessed lesion types according to imaging features. Sensitivity and specificity were compared between the qualitative and quantitative studies. Results: NIC and LNR in the AP for the wall of nHCC (0.14 ± 0.04 mg/ml; 2.77 ± 0.74) were higher than those of HA (0.13 ± 0.02 mg/ml; 1.4 ± 0.9). NIC and LNR in the PP for the wall of HA (0.66 ± 0.05 mg/ml; 1.2 ± 0.2) were higher than those of nHCC (0.5 ± 0.11 mg/ml; 0.94 ± 0.12). The differences in NIC in the AP were not significant but the differences in LNR in AP, and NIC and LNR in the PP were significant. The best quantitative parameter was LNR in AP, and a threshold of 1.52 would yield a sensitivity and specificity of 100% and 91.7%, respectively, for differentiating nHCC from HA. Conclusion: CT spectral imaging with quantitative iodine concentration analysis may help to increase the accuracy of differentiating nHCC from HA. - Highlights: • We preliminarily investigate the usefulness of CT spectral imaging in differentiating nHCC from HA. • CT spectral imaging may help differentiate necrotic hepatocellular carcinoma from hepatic abscess. • CT spectral imaging can evaluate the blood supply and necrotic degree of lesions. • Quantitative analysis of iodine concentration provides greater diagnostic confidence

  8. Features Speech Signature Image Recognition on Mobile Devices

    Directory of Open Access Journals (Sweden)

    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.

  9. Posteromedial impingement (POMI) of the ankle: MR imaging features

    International Nuclear Information System (INIS)

    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

  10. Olfactory and imaging features in atypical Alzheimer’s disease

    Directory of Open Access Journals (Sweden)

    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.

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

    African Journals Online (AJOL)

    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 ...

  12. Differential impairment of social cognition factors in bipolar disorder with and without psychotic features and schizophrenia.

    Science.gov (United States)

    Thaler, Nicholas S; Allen, Daniel N; Sutton, Griffin P; Vertinski, Mary; Ringdahl, Erik N

    2013-12-01

    While it is well-established that patients with schizophrenia and bipolar disorder exhibit deficits in social cognition, few studies have separately examined bipolar disorder with and without psychotic features. The current study addressed this gap by comparing patients with bipolar disorder with (BD+) and without (BD-) psychotic features, patients with schizophrenia (SZ), and healthy controls (NC) across social cognitive measures. Principal factor analysis on five social cognition tasks extracted a two-factor structure comprised of social/emotional processing and theory of mind. Factor scores were compared among the four groups. Results identified differential patterns of impairment between the BD+ and BD- group on the social/emotional processing factor while all clinical groups performed poorer than controls on the theory of mind factor. This provides evidence that a history of psychosis should be taken into account while evaluating social cognition in patients with bipolar disorder and also raises hypotheses about the relationship between social cognition and psychosis. Copyright © 2013 Elsevier Ltd. All rights reserved.

  13. Transient Features in Nanosecond Pulsed Electric Fields Differentially Modulate Mitochondria and Viability

    Science.gov (United States)

    Beebe, Stephen J.; Chen, Yeong-Jer; Sain, Nova M.; Schoenbach, Karl H.; Xiao, Shu

    2012-01-01

    It is hypothesized that high frequency components of nanosecond pulsed electric fields (nsPEFs), determined by transient pulse features, are important for maximizing electric field interactions with intracellular structures. For monopolar square wave pulses, these transient features are determined by the rapid rise and fall of the pulsed electric fields. To determine effects on mitochondria membranes and plasma membranes, N1-S1 hepatocellular carcinoma cells were exposed to single 600 ns pulses with varying electric fields (0–80 kV/cm) and short (15 ns) or long (150 ns) rise and fall times. Plasma membrane effects were evaluated using Fluo-4 to determine calcium influx, the only measurable source of increases in intracellular calcium. Mitochondria membrane effects were evaluated using tetramethylrhodamine ethyl ester (TMRE) to determine mitochondria membrane potentials (ΔΨm). Single pulses with short rise and fall times caused electric field-dependent increases in calcium influx, dissipation of ΔΨm and cell death. Pulses with long rise and fall times exhibited electric field-dependent increases in calcium influx, but diminished effects on dissipation of ΔΨm and viability. Results indicate that high frequency components have significant differential impact on mitochondria membranes, which determines cell death, but lesser variances on plasma membranes, which allows calcium influxes, a primary determinant for dissipation of ΔΨm and cell death. PMID:23284682

  14. Assessing the features of extreme smog in China and the differentiated treatment strategy

    Science.gov (United States)

    Deng, Lu; Zhang, Zhengjun

    2018-01-01

    Extreme smog can have potentially harmful effects on human health, the economy and daily life. However, the average (mean) values do not provide strategically useful information on the hazard analysis and control of extreme smog. This article investigates China's smog extremes by applying extreme value analysis to hourly PM2.5 data from 2014 to 2016 obtained from monitoring stations across China. By fitting a generalized extreme value (GEV) distribution to exceedances over a station-specific extreme smog level at each monitoring location, all study stations are grouped into eight different categories based on the estimated mean and shape parameter values of fitted GEV distributions. The extreme features characterized by the mean of the fitted extreme value distribution, the maximum frequency and the tail index of extreme smog at each location are analysed. These features can provide useful information for central/local government to conduct differentiated treatments in cities within different categories and conduct similar prevention goals and control strategies among those cities belonging to the same category in a range of areas. Furthermore, hazardous hours, breaking probability and the 1-year return level of each station are demonstrated by category, based on which the future control and reduction targets of extreme smog are proposed for the cities of Beijing, Tianjin and Hebei as an example.

  15. MR imaging features of foot involvement in ankylosing spondylitis

    Energy Technology Data Exchange (ETDEWEB)

    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

  16. MR imaging features of foot involvement in ankylosing spondylitis

    International Nuclear Information System (INIS)

    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

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

    Science.gov (United States)

    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

  18. Hyperspectral Image Classification Based on the Combination of Spatial-spectral Feature and Sparse Representation

    Directory of Open Access Journals (Sweden)

    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.

  19. Imaging features of gossypiboma: report of two cases.

    Directory of Open Access Journals (Sweden)

    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.

  20. A standardised protocol for texture feature analysis of endoscopic images in gynaecological cancer

    Directory of Open Access Journals (Sweden)

    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

  1. Radiomic features analysis in computed tomography images of lung nodule classification.

    Directory of Open Access Journals (Sweden)

    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.

  2. Convolutional deep belief network with feature encoding for classification of neuroblastoma histological images

    Directory of Open Access Journals (Sweden)

    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.

  3. Uniform competency-based local feature extraction for remote sensing images

    Science.gov (United States)

    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.

  4. Haralick texture features from apparent diffusion coefficient (ADC) MRI images depend on imaging and pre-processing parameters.

    Science.gov (United States)

    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.

  5. Hepatocellular carcinoma with neuroendocrine differentiation: clinical and imaging findings in five patients

    International Nuclear Information System (INIS)

    Park, Seong Hoon; Kang, Myeong Jin; Cho, Jin Han

    2008-01-01

    To describe the clinical and imaging findings of hepatocellular carcinoma with neuroendocrine differentiation, which is an extremely rare variant of hepatocellular carcinoma. We collected five patients who had histopathologically proven hepatocellular carcinoma with neuroendocrine differentiation, and described morphologic feature, enhancement pattern of tumors, extrahepatic manifestation and clinical findings. At CT, the tumor size ranged from 8 to 17 cm (mean: 12 cm) in maximum diameter. The tumor margin was well-defined and smooth in four patients and all tumors were heterogeneously hypoattenuating. Four tumor showed rim enhancement on arterial and portal phases. Local invasion to the portal vein, intrahepatic duct and gallbladder were seen. Extrahepatic manifestations included hepatic metastases, lymph node metastasis. At ultrasonography, the tumor showed heterogeneously hyperechoic in all patients and hypoechoic rim was found in four patients. Of four patients who were followed up, one survived for 16 months after initial diagnosis, while the other three died within 3 months after initial diagnosis. As described above, clinical and imaging findings of hepatocellular carcinoma with neuroendocrine differentiation were not specific. However, this rare variant of hepatocellular carcinoma could be considered when hepatic tumor is found in an advanced stage and shows persistent rim enhancement at CT

  6. Imaging features of posterior mediastinal chordoma in a child

    Energy Technology Data Exchange (ETDEWEB)

    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.)

  7. TRADEMARK IMAGE RETRIEVAL USING LOW LEVEL FEATURE EXTRACTION IN CBIR

    OpenAIRE

    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...

  8. Bubble feature extracting based on image processing of coal flotation froth

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    Science.gov (United States)

    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.

  10. A Novel Feature Extraction Technique Using Binarization of Bit Planes for Content Based Image Classification

    Directory of Open Access Journals (Sweden)

    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.

  11. The mental representation of living and nonliving things: differential weighting and interactivity of sensorial and non-sensorial features.

    Science.gov (United States)

    Ventura, Paulo; Morais, José; Brito-Mendes, Carlos; Kolinsky, Régine

    2005-02-01

    Warrington and colleagues (Warrington & McCarthy, 1983, 1987; Warrington & Shallice, 1984) claimed that sensorial and functional-associative (FA) features are differentially important in determining the meaning of living things (LT) and nonliving things (NLT). The first aim of the present study was to evaluate this hypothesis through two different access tasks: feature generation (Experiment 1) and cued recall (Experiment 2). The results of both experiments provided consistent empirical support for Warrington and colleagues' assumption. The second aim of the present study was to test a new differential interactivity hypothesis that combines Warrington and colleagueS' assumption with the notion of a higher number of intercorrelations and hence of a stronger connectivity between sensorial and non-sensorial features for LTs than for NLTs. This hypothesis was motivated by previoUs reports of an uncrossed interaction between domain (LTs vs NLTs) and attribute type (sensorial vs FA) in, for example, a feature verification task (Laws, Humber, Ramsey, & McCarthy, 1995): while FA attributes are verified faster than sensorial attributes for NLTs, no difference is observed for LTs. We replicated and generalised this finding using several feature verification tasks on both written words and pictures (Experiment 3), including in conditions aimed at minimising the intervention of priming biases and strategic or mnemonic processes (Experiment 4). The whole set of results suggests that both privileged relations between features and categories, and the differential importance of intercorrelations between features as a function of category, modulate access to semantic features.

  12. Significance of the impact of motion compensation on the variability of PET image features

    Science.gov (United States)

    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

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

    Directory of Open Access Journals (Sweden)

    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.

  14. Feature learning and change feature classification based on deep learning for ternary change detection in SAR images

    Science.gov (United States)

    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.

  15. Polarimetric SAR Image Classification Using Multiple-feature Fusion and Ensemble Learning

    Directory of Open Access Journals (Sweden)

    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.

  16. Infectious diseases of the brain: imaging and differential diagnosis; Infektioese Hirnerkrankungen: Bildgebung und differenzialdiagnostische Aspekte

    Energy Technology Data Exchange (ETDEWEB)

    Haehnel, S.; Seitz, A. [Abt. Neuroradiologie, Neurologische Klinik, Universitaetsklinikum Heidelberg (Germany); Storch-Hagenlocher, B. [Abt. Neurologie, Neurologische Klinik, Universitaetsklinikum Heidelberg (Germany)

    2006-09-15

    Infectious diseases of the central nervous system have to be considered in differential diagnosis particularly in immunocompromised persons. Neuro-imaging, specifically advanced techniques such as diffusion weighted MRI and perfusion MRI contribute much to the differentiation of brain infections and for differentiating brain infections from other, for instance, neoplastic diseases. In this review we present the imaging criteria of the most important brains infections in adults and in pediatric patients and discuss differential diagnostic aspects in detail. (orig.)

  17. Compact Representation of High-Dimensional Feature Vectors for Large-Scale Image Recognition and Retrieval.

    Science.gov (United States)

    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.

  18. Efficient and robust model-to-image alignment using 3D scale-invariant features.

    Science.gov (United States)

    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.

  19. Imaging features of ductal plate malformations in adults

    Energy Technology Data Exchange (ETDEWEB)

    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.

  20. Clinical and CT imaging features of abdominal fat necrosis

    International Nuclear Information System (INIS)

    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)

  1. Prostate cancer multi-feature analysis using trans-rectal ultrasound images

    International Nuclear Information System (INIS)

    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)

  2. High resolution x-ray lensless imaging by differential holographic encoding

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, D.; Guizar-Sicairos, M.; Wu, B.; Scherz, A.; Acremann, Y.; Tylisczcak, T.; Fischer, P.; Friedenberger, N.; Ollefs, K.; Farle, M.; Fienup, J. R.; Stohr, J.

    2009-11-02

    X-ray free electron lasers (X-FEL{sub s}) will soon offer femtosecond pulses of laterally coherent x-rays with sufficient intensity to record single-shot coherent scattering patterns for nanoscale imaging. Pulse trains created by splitand-delay techniques even open the door for cinematography on unprecedented nanometer length and femtosecond time scales. A key to real space ultrafast motion pictures is fast and reliable inversion of the recorded reciprocal space scattering patterns. Here we for the first time demonstrate in the x-ray regime the power of a novel technique for lensless high resolution imaging, previously suggested by Guizar-Sicairos and Fienup termed holography with extended reference by autocorrelation linear differential operation, HERALD0. We have achieved superior resolution over conventional x-ray Fourier transform holography (FTH) without sacrifices in SNR or significant increase in algorithmic complexity. By combining images obtained from individual sharp features on an extended reference, we further show that the resolution can be even extended beyond the reference fabrication limits. Direct comparison to iterative phase retrieval image reconstruction and images recorded with stateof- the-art zone plate microscopes is presented. Our results demonstrate the power of HERALDO as a favorable candidate for robust inversion of single-shot coherent scattering patterns.

  3. High-Resolution X-Ray Lensless Imaging by Differential Holographic Encoding

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, Diling [Stanford Univ., CA (United States). Dept. of Applied Physics; SLAC National Accelerator Lab., Menlo Park, CA (United States). Stanford Inst. for Material and Energy Science; Guizar-Sicairos, Manuel [Univ. of Rochester, NY (United States). Inst. of Optics; Wu, Benny [Stanford Univ., CA (United States). Dept. of Applied Physics; SLAC National Accelerator Lab., Menlo Park, CA (United States). Stanford Inst. for Material and Energy Science; Scherz, Andreas [SLAC National Accelerator Lab., Menlo Park, CA (United States). Stanford Inst. for Material and Energy Science; Acremann, Yves [SLAC National Accelerator Lab., Menlo Park, CA (United States). Photon Ultrafast Laser Science and Engineering Inst. (PULSE); Tyliszczak, Tolek [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Advanced Light Source (ALS); Fischer, Peter [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Center for X-ray Optics; Friedenberger, Nina [Universitat Duisburg-Essen (Germany). Dept. of Physics and Center for Nanointegration Duisburg-Essen (CeNIDE); Ollefs, Katharina [Universitat Duisburg-Essen (Germany). Dept. of Physics and Center for Nanointegration Duisburg-Essen (CeNIDE); Farle, Michael [Universitat Duisburg-Essen (Germany). Dept. of Physics and Center for Nanointegration Duisburg-Essen (CeNIDE); Fienup, James R. [Univ. of Rochester, NY (United States). Inst. of Optics; Stöhr, Joachim [SLAC National Accelerator Lab., Menlo Park, CA (United States). Linac Coherent Light Source (LCLS)

    2010-07-01

    X-ray free electron lasers (X-FELs) will soon offer femtosecond pulses of laterally coherent x-rays with sufficient intensity to record single-shot coherent scattering patterns for nanoscale imaging. Pulse trains created by split and- delay techniques even open the door for cinematography on unprecedented nanometer length and femtosecond time scales. A key to real space ultrafast motion pictures is fast and reliable inversion of the recorded reciprocal space scattering patterns. Here we for the first time demonstrate in the x-ray regime the power of a novel technique for lensless high resolution imaging, previously suggested by Guizar-Sicairos and Fienup termed holography with extended reference by autocorrelation linear differential operation, HERALD0. We have achieved superior resolution over conventional x-ray Fourier transform holography (FTH) without sacrifices in SNR or significant increase in algorithmic complexity. By combining images obtained from individual sharp features on an extended reference, we further show that the resolution can be even extended beyond the reference fabrication limits. Direct comparison to iterative phase retrieval image reconstruction and images recorded with state of-the-art zone plate microscopes is presented. Our results demonstrate the power of HERALDO as a favorable candidate for robust inversion of single-shot coherent scattering patterns.

  4. Combining low level features and visual attributes for VHR remote sensing image classification

    Science.gov (United States)

    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.

  5. Comparison of image features calculated in different dimensions for computer-aided diagnosis of lung nodules

    Science.gov (United States)

    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.

  6. Thin plate spline feature point matching for organ surfaces in minimally invasive surgery imaging

    Science.gov (United States)

    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.

  7. An automated classification system for the differentiation of obstructive lung diseases based on the textural analysis of HRCT images

    International Nuclear Information System (INIS)

    Park, Seong Hoon; Seo, Joon Beom; Kim, Nam Kug; Lee, Young Kyung; Kim, Song Soo; Chae, Eun Jin; Lee, June Goo

    2007-01-01

    To develop an automated classification system for the differentiation of obstructive lung diseases based on the textural analysis of HRCT images, and to evaluate the accuracy and usefulness of the system. For textural analysis, histogram features, gradient features, run length encoding, and a co-occurrence matrix were employed. A Bayesian classifier was used for automated classification. The images (image number n = 256) were selected from the HRCT images obtained from 17 healthy subjects (n = 67), 26 patients with bronchiolitis obliterans (n = 70), 28 patients with mild centrilobular emphysema (n = 65), and 21 patients with panlobular emphysema or severe centrilobular emphysema (n = 63). An five-fold cross-validation method was used to assess the performance of the system. Class-specific sensitivities were analyzed and the overall accuracy of the system was assessed with kappa statistics. The sensitivity of the system for each class was as follows: normal lung 84.9%, bronchiolitis obliterans 83.8%, mild centrilobular emphysema 77.0%, and panlobular emphysema or severe centrilobular emphysema 95.8%. The overall performance for differentiating each disease and the normal lung was satisfactory with a kappa value of 0.779. An automated classification system for the differentiation between obstructive lung diseases based on the textural analysis of HRCT images was developed. The proposed system discriminates well between the various obstructive lung diseases and the normal lung

  8. Stress fractures: pathophysiology, clinical presentation, imaging features, and treatment options.

    Science.gov (United States)

    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.

  9. Featured Image: A Molecular Cloud Outside Our Galaxy

    Science.gov (United States)

    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

  10. Featured Image: A New Dark Vortex on Neptune

    Science.gov (United States)

    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

  11. Automatic brain MR image denoising based on texture feature-based artificial neural networks.

    Science.gov (United States)

    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.

  12. Two-Level Evaluation on Sensor Interoperability of Features in Fingerprint Image Segmentation

    Directory of Open Access Journals (Sweden)

    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.

  13. Unusual magnetic resonance imaging features in Menkes disease

    International Nuclear Information System (INIS)

    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)

  14. Unusual magnetic resonance imaging features in Menkes disease

    Energy Technology Data Exchange (ETDEWEB)

    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)

  15. Differential Features of Cerebral Perfusion in Dementia with Lewy Bodies Compared to Alzheimer's Dementia using SPM Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Do Young; Park, Kyung Won; Kim, Jae Woo [College of Medicine, Univ. of Donga, Busan (Korea, Republic of)

    2003-07-01

    Alzheimer's dementia (AD) and dementia with Lewy bodies (DLB) are most common cause of dementia in elderly people. Clinical distinction in some cases of DLB from AD may be difficult as symptom profiles overlap. Some neuropathologic overlap is also seen as beta-amyloidosis and senile plaques can be found in both disease. Both disease also share severe acetylcholine depletion. We evaluated the differences of brain perfusion between DLB and AD using statistical parametric mapping analysis. Twelve DLB (mean age ; 68.8{+-}8.3 years, K-MMSE ; 17.3{+-}6.1) and 51 AD patients (mean age ; 71.4{+-}7.2 years, K-MMSE ; 16.7{+-}4.5), which were matched for age and severity of dementia, participated in this study. Tc-99m HMPAO SPECT was performed for measuring regional cerebral blood flow. Statistical parametric mapping (SPM99) software was used for automatic and objective approach to analyze SPECT image data. The SPECT data of the patients with DLB were compared to patients with AD. Comparison of the two dementia groups (uncorrected p<0.01) revealed significant hypoperfusion in both occipital (both middle occipital gyrus, Rt B no. 18 and Lt cuneus), both parietal (Lt parietal precuneus, Lt B no. 39, Lt inferior parietal lobule and Rt supramarginal gyrus) lobes in DLB compared with AD. Significant hyperperfusion was noted in Rt frontal (sup. frontal gyrus, B no.10, middle frontal gyrus, B no. 9, B no. 11, inf. frontal gyrus), Rt putamen, Lt ant. cingulate gyrus (B no. 24), both cerebellar post. lobe (Lt tuber, Lt declive, Lt tonsil, Rt declive) in DLB compared with AD. We found a significant differences in the cerebral perfusion pattern between DLB and AD. Differential feature of cerebral perfusion in DLB was both occipital hypoperfusion and preserved Rt frontal perfusion compared to AD. Therefore in difficult case of clinical an neuro pathologic diagnosis, brain perfusion SPECT with SPM analysis may be helpful to differentiate DLB from AD.

  16. An improved feature extraction algorithm based on KAZE for multi-spectral image

    Science.gov (United States)

    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.

  17. Identification of natural images and computer-generated graphics based on statistical and textural features.

    Science.gov (United States)

    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.

  18. Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

    NARCIS (Netherlands)

    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; 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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. 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    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,

  19. Introduction to the feature section on functional imaging of the pelvic floor.

    Science.gov (United States)

    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.

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

    International Nuclear Information System (INIS)

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

    Energy Technology Data Exchange (ETDEWEB)

    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.)

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

    International Nuclear Information System (INIS)

    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.)

  3. Imaging Features of Pediatric Pentastomiasis Infection: a Case Report

    Energy Technology Data Exchange (ETDEWEB)

    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

  4. Imaging Features of Pediatric Pentastomiasis Infection: a Case Report

    International Nuclear Information System (INIS)

    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

  5. Image features of herniation pit of the femoral neck

    International Nuclear Information System (INIS)

    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)

  6. Diagnostic features of quantitative comb-push shear elastography for breast lesion differentiation.

    Science.gov (United States)

    Bayat, Mahdi; Denis, Max; Gregory, Adriana; Mehrmohammadi, Mohammad; Kumar, Viksit; Meixner, Duane; Fazzio, Robert T; Fatemi, Mostafa; Alizad, Azra

    2017-01-01

    Lesion stiffness measured by shear wave elastography has shown to effectively separate benign from malignant breast masses. The aim of this study was to evaluate different aspects of Comb-push Ultrasound Shear Elastography (CUSE) performance in differentiating breast masses. With written signed informed consent, this HIPAA- compliant, IRB approved prospective study included patients from April 2014 through August 2016 with breast masses identified on conventional imaging. Data from 223 patients (19-85 years, mean 59.93±14.96 years) with 227 suspicious breast masses identifiable by ultrasound (mean size 1.83±2.45cm) were analyzed. CUSE was performed on all patients. Three regions of interest (ROI), 3 mm in diameter each, were selected inside the lesion on the B-mode ultrasound which also appeared in the corresponding shear wave map. Lesion elasticity values were measured in terms of the Young's modulus. In correlation to pathology results, statistical analyses were performed. Pathology revealed 108 lesions as malignant and 115 lesions as benign. Additionally, 4 lesions (BI-RADS 2 and 3) were considered benign and were not biopsied. Average lesion stiffness measured by CUSE resulted in 84.26% sensitivity (91 of 108), 89.92% specificity (107 of 119), 85.6% positive predictive value, 89% negative predictive value and 0.91 area under the curve (P 0.21). CUSE was able to distinguish between benign and malignant breast masses with high sensitivity and specificity. Continuity of stiffness maps allowed for choosing multiple quantification ROIs which covered large areas of lesions and resulted in similar diagnostic performance based on average and maximum elasticity. The ove