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Sample records for bright feature image

  1. Bright Retinal Lesions Detection using Colour Fundus Images Containing Reflective Features

    Energy Technology Data Exchange (ETDEWEB)

    Giancardo, Luca [ORNL; Karnowski, Thomas Paul [ORNL; Chaum, Edward [ORNL; Meriaudeau, Fabrice [ORNL; Tobin Jr, Kenneth William [ORNL; Li, Yaquin [University of Tennessee, Knoxville (UTK)

    2009-01-01

    In the last years the research community has developed many techniques to detect and diagnose diabetic retinopathy with retinal fundus images. This is a necessary step for the implementation of a large scale screening effort in rural areas where ophthalmologists are not available. In the United States of America, the incidence of diabetes is worryingly increasing among the young population. Retina fundus images of patients younger than 20 years old present a high amount of reflection due to the Nerve Fibre Layer (NFL), the younger the patient the more these reflections are visible. To our knowledge we are not aware of algorithms able to explicitly deal with this type of reflection artefact. This paper presents a technique to detect bright lesions also in patients with a high degree of reflective NFL. First, the candidate bright lesions are detected using image equalization and relatively simple histogram analysis. Then, a classifier is trained using texture descriptor (Multi-scale Local Binary Patterns) and other features in order to remove the false positives in the lesion detection. Finally, the area of the lesions is used to diagnose diabetic retinopathy. Our database consists of 33 images from a telemedicine network currently developed. When determining moderate to high diabetic retinopathy using the bright lesions detected the algorithm achieves a sensitivity of 100% at a specificity of 100% using hold-one-out testing.

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

    International Nuclear Information System (INIS)

    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. Facial Expression Recognition using Entropy and Brightness Features

    OpenAIRE

    Khan, Rizwan Ahmed; Meyer, Alexandre; Konik, Hubert; Bouakaz, Saïda

    2011-01-01

    International audience This paper proposes a novel framework for universal facial expression recognition. The framework is based on two sets of features extracted from the face image: entropy and brightness. First, saliency maps are obtained by state-of-the-art saliency detection algorithm i.e. "frequencytuned salient region detection". Then only localized salient facial regions from saliency maps are processed to extract entropy and brightness features. To validate the performance of sali...

  5. Study of Three-Dimensional Image Brightness Loss in Stereoscopy

    Directory of Open Access Journals (Sweden)

    Hsing-Cheng Yu

    2015-10-01

    Full Text Available When viewing three-dimensional (3D images, whether in cinemas or on stereoscopic televisions, viewers experience the same problem of image brightness loss. This study aims to investigate image brightness loss in 3D displays, with the primary aim being to quantify the image brightness degradation in the 3D mode. A further aim is to determine the image brightness relationship to the corresponding two-dimensional (2D images in order to adjust the 3D-image brightness values. In addition, the photographic principle is used in this study to measure metering values by capturing 2D and 3D images on television screens. By analyzing these images with statistical product and service solutions (SPSS software, the image brightness values can be estimated using the statistical regression model, which can also indicate the impact of various environmental factors or hardware on the image brightness. In analysis of the experimental results, comparison of the image brightness between 2D and 3D images indicates 60.8% degradation in the 3D image brightness amplitude. The experimental values, from 52.4% to 69.2%, are within the 95% confidence interval

  6. Annular bright and dark field imaging of soft materials

    International Nuclear Information System (INIS)

    Here polyethylene, as an example of an important soft material, was studied by STEM annular bright and dark field. The contrast as function of the probe size/shape and the detector collection angle are discussed. The results are compared to conventional bright field transmission electron microscopy, electron energy filtered imaging and energy dispersive spectroscopy mapping. Annular bright and dark field gave a higher contrast than conventional transmission and analytical mapping techniques

  7. Graphical Methods for Quantifying Macromolecules through Bright Field Imaging

    Energy Technology Data Exchange (ETDEWEB)

    Chang, Hang; DeFilippis, Rosa Anna; Tlsty, Thea D.; Parvin, Bahram

    2008-08-14

    Bright ?eld imaging of biological samples stained with antibodies and/or special stains provides a rapid protocol for visualizing various macromolecules. However, this method of sample staining and imaging is rarely employed for direct quantitative analysis due to variations in sample fixations, ambiguities introduced by color composition, and the limited dynamic range of imaging instruments. We demonstrate that, through the decomposition of color signals, staining can be scored on a cell-by-cell basis. We have applied our method to Flbroblasts grown from histologically normal breast tissue biopsies obtained from two distinct populations. Initially, nuclear regions are segmented through conversion of color images into gray scale, and detection of dark elliptic features. Subsequently, the strength of staining is quanti?ed by a color decomposition model that is optimized by a graph cut algorithm. In rare cases where nuclear signal is significantly altered as a result of samplepreparation, nuclear segmentation can be validated and corrected. Finally, segmented stained patterns are associated with each nuclear region following region-based tessellation. Compared to classical non-negative matrix factorization, proposed method (i) improves color decomposition, (ii) has a better noise immunity, (iii) is more invariant to initial conditions, and (iv) has a superior computing performance

  8. Abdominal tuberculosis: Imaging features

    International Nuclear Information System (INIS)

    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

  9. Segmentation and classification of bright lesions to diagnose diabetic retinopathy in retinal images.

    Science.gov (United States)

    Santhi, D; Manimegalai, D; Parvathi, S; Karkuzhali, S

    2016-08-01

    In view of predicting bright lesions such as hard exudates, cotton wool spots, and drusen in retinal images, three different segmentation techniques have been proposed and their effectiveness is compared with existing segmentation techniques. The benchmark images with annotations present in the structured analysis of the retina (STARE) database is considered for testing the proposed techniques. The proposed segmentation techniques such as region growing (RG), region growing with background correction (RGWBC), and adaptive region growing with background correction (ARGWBC) have been used, and the effectiveness of the algorithms is compared with existing fuzzy-based techniques. Images of eight categories of various annotations and 10 images in each category have been used to test the consistency of the proposed algorithms. Among the proposed techniques, ARGWBC has been identified to be the best method for segmenting the bright lesions based on its sensitivity, specificity, and accuracy. Fifteen different features are extracted from retinal images for the purpose of identification and classification of bright lesions. Feedforward backpropagation neural network (FFBPNN) and pattern recognition neural network (PRNN) are used for the classification of normal/abnormal images. Probabilistic neural network (PNN), radial basis exact fit (RBE), radial basis fewer neurons (RB), and FFBPNN are used for further bright lesion classification and achieve 100% accuracy. PMID:27060730

  10. Microwave brightness temperature imaging and dielectric properties of lunar soil

    Indian Academy of Sciences (India)

    Wu Ji; Li Dihui; Zhang Xiaohui; Jiang Jingshan; A T Altyntsev; B I Lubyshev

    2005-12-01

    Among many scientific objectives of lunar exploration, investigations on lunar soil become attractive due to the existence of He3 and ilmenite in the lunar soil and their possible utilization as nuclear fuel for power generation.Although the composition of the lunar surface soil can be determined by optical and /X-ray spectrometers, etc., the evaluation of the total reserves of He3 and ilmenite within the regolith and in the lunar interior are still not available.In this paper,we give a rough analysis of the microwave brightness temperature images of the lunar disc observed using the NRAO 12 meter Telescope and Siberian Solar Radio Telescope.We also present the results of the microwave dielectric properties of terrestrial analogues of lunar soil and,discuss some basic relations between the microwave brightness temperature and lunar soil properties.

  11. Bright Ray-like Features in the Aftermath of CMEs: White Light vs UV Spectra

    CERN Document Server

    Ciaravella, A; Giordano, S; Raymond, J C

    2013-01-01

    Current sheets are important signatures of magnetic reconnection in the eruption of confined solar magnetic structures. Models of Coronal Mass Ejections (CMEs) involve formation of a current sheet connecting the ejected flux rope with the post eruption magnetic loops. Current sheets have been identified in white light images of CMEs as narrow rays trailing the outward moving CME core, and in ultraviolet spectra as narrow bright features emitting the Fe XVIII line. In this work samples of rays detected in white light images or in ultraviolet spectra have been analyzed. Temperatures, widths, and line intensities of the rays have been measured, and their correlation to the CME properties has been studied. The samples show a wide range of temperatures with hot, coronal and cool rays. In some cases, the UV spectra support the identification of rays as current sheets, but they show that some white light rays are cool material from the CME core. In many cases, both hot and cool material are present, but offset from ...

  12. Ultra Low Surface Brightness Imaging with the Dragonfly Telephoto Array

    CERN Document Server

    Abraham, Roberto G

    2014-01-01

    We describe the Dragonfly Telephoto Array, a robotic imaging system optimized for the detection of extended ultra low surface brightness structures. The array consists of eight Canon 400mm f/2.8 telephoto lenses coupled to eight science-grade commercial CCD cameras. The lenses are mounted on a common framework and are co-aligned to image simultaneously the same position on the sky. The system provides an imaging capability equivalent to a 0.4m aperture f/1.0 refractor with a 2.6 deg X 1.9 deg field of view. The system has no obstructions in the light path, optimized baffling, and internal optical surfaces coated with a new generation of anti-reflection coatings based on sub-wavelength nanostructures. As a result, the array's point spread function has a factor of ~10 less scattered light at large radii than well-baffled reflecting telescopes. The Dragonfly Telephoto Array is capable of imaging extended structures to surface brightness levels below 30 mag/arcsec^2 in 10h integrations (without binning or foregro...

  13. Direct imaging of phase objects enables conventional deconvolution in bright field light microscopy.

    Directory of Open Access Journals (Sweden)

    Carmen Noemí Hernández Candia

    Full Text Available In transmitted optical microscopy, absorption structure and phase structure of the specimen determine the three-dimensional intensity distribution of the image. The elementary impulse responses of the bright field microscope therefore consist of separate absorptive and phase components, precluding general application of linear, conventional deconvolution processing methods to improve image contrast and resolution. However, conventional deconvolution can be applied in the case of pure phase (or pure absorptive objects if the corresponding phase (or absorptive impulse responses of the microscope are known. In this work, we present direct measurements of the phase point- and line-spread functions of a high-aperture microscope operating in transmitted bright field. Polystyrene nanoparticles and microtubules (biological polymer filaments serve as the pure phase point and line objects, respectively, that are imaged with high contrast and low noise using standard microscopy plus digital image processing. Our experimental results agree with a proposed model for the response functions, and confirm previous theoretical predictions. Finally, we use the measured phase point-spread function to apply conventional deconvolution on the bright field images of living, unstained bacteria, resulting in improved definition of cell boundaries and sub-cellular features. These developments demonstrate practical application of standard restoration methods to improve imaging of phase objects such as cells in transmitted light microscopy.

  14. Imaging features of aggressive angiomyxoma

    Energy Technology Data Exchange (ETDEWEB)

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

    2003-02-01

    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.

  15. Imaging features of aggressive angiomyxoma

    International Nuclear Information System (INIS)

    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

  16. Featured Image: Solar Prominence Eruptions

    Science.gov (United States)

    Kohler, Susanna

    2016-02-01

    In these images from the Solar Dynamics Observatorys AIA instrument (click for the full resolution!), two solar prominence eruptions (one from June 2011 and one from August 2012) are shown in pre- and post-eruption states. The images at the top are taken in the Fe XII 193 bandpass and the images at the bottom are taken in the He II 304 bandpass. When a team of scientists searched through seven years of solar images taken by the STEREO (Solar Terrestrial Relations Observatory) spacecraft, these two eruptions were found to extend all the way out to a distance of 1 AU. They were the only two examples of clear, bright, and compact prominence eruptions found to do so. The scientists, led by Brian Wood (Naval Research Laboratory), used these observations to reconstruct the motion of the eruption and model how prominences expand as they travel away from the Sun. Theimage to the rightshowsa STEREO observation compared to the teams 3D model of theprominences shape and expansion. To learn more about theresults from this study, check out the paper below.CitationBrian E. Wood et al 2016 ApJ 816 67. doi:10.3847/0004-637X/816/2/67

  17. Magnetic resonance imaging features of allografts

    International Nuclear Information System (INIS)

    Objective. To investigate the magnetic resonance imaging (MRI) features of allografts at various time intervals after surgery in patients with osteoarticular allografts.Design and patients. Sixteen patients who were treated with osteoarticular allografts and who were followed over time with MRI studies as part of their long-term follow-up were retrospectively selected for this study. T1-weighted images were obtained both before and after gadolinium administration along with T2-weighted images. All images were reviewed by an experienced musculoseletal radiologist, with two other experienced radiologists used for consultation. Imaging studies were organized into three groups for ease of discussion: early postoperative period (2 days to 2 months), intermediate postoperative period (3 months to 2 years), and late postoperative period (greater than 2 years).Results. In the early postoperative period, no gadolinium enhancement of the allograft was visible in any of the MR images. A linear, thin layer of periosteal and endosteal tissue enhancement along the margin of the allograft was visible in images obtained at 3-4 months. This enhancement apeared gradually to increase in images from later periods, and appears to have stabilized in the images obtained approximately 2-3 years after allograft placement. The endosteal enhancement diminished after several years, with examinations conducted between 6 and 8 years following surgery showing minimal endosteal enhancement. However, focal enhancement was noted adjacent to areas of pressure erosion or degenerative cysts. All the cases showed inhomogeneity in the marrow signal (scattered low signal foci on T1 with corresponding bright signal on T2), and a diffuse, inhomogeneous marrow enhancement later on.Conclusion. We have characterized the basic MRI features of osteoarticular allografts in 16 patients who underwent imaging studies at various time points as part of routine follow-up. We believe that the endosteal and periosteal

  18. The Altitude of an Infrared Bright Cloud Feature on Neptune from Near-Infrared Spectroscopy

    CERN Document Server

    Roe, H G; McLean, I S; De Pater, I; Becklin, E E; Figer, D F; Gilbert, A M; Larkin, J E; Levenson, N A; Teplitz, H I; Wilcox, M K; Roe, Henry G.; Graham, James R.; Lean, Ian S. Mc; Pater, Imke de; Figer, Donald F.; Gilbert, Andrea M.; Larkin, James E.; Teplitz, Harry I.; Wilcox, Mavourneen K.

    2001-01-01

    We present 2.03-2.30 micron near-infrared spectroscopy of Neptune taken 1999 June 2 (UT) with the W.M. Keck Observatory's near-infrared spectrometer (NIRSPEC) during the commissioning of the instrument. The spectrum is dominated by a bright cloud feature, possibly a storm or upwelling, in the southern hemisphere at approximately 50 degrees S latitude. The spectrum also includes light from a dimmer northern feature at approximately 30 degrees N latitude. We compare our spectra (R ~ 2000) of these two features with a simple model of Neptune's atmosphere. Given our model assumption that the clouds are flat reflecting layers, we find that the top of the bright southern cloud feature sat at a pressure level of 0.14 (+0.05, -0.03) bar, and thus this cloud did not extend into the stratosphere (P < 0.1 bar). A similar analysis of the dimmer northern feature gives a cloud-top pressure of 0.084 +/- 0.026 bar. This suggests that the features we observed efficiently transport methane to the base of the stratosphere, b...

  19. Imaging features of musculoskeletal tuberculosis

    International Nuclear Information System (INIS)

    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.)

  20. 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.

  1. An Ultraviolet imager to study bright UV sources

    CERN Document Server

    Mathew, Joice; Sarpotdar, Mayuresh; Sreejith, A G; Safonova, Margarita; Murthy, Jayant

    2016-01-01

    We have designed and developed a compact ultraviolet imaging payload to fly on a range of possible platforms such as high altitude balloon experiments, cubesats, space missions, etc. The primary science goals are to study the bright UV sources (mag < 10) and also to look for transients in the Near UV (200 - 300 nm) domain. Our first choice is to place this instrument on a spacecraft going to the Moon as part of the Indian entry into Google lunar X-Prize competition. The major constraints for the instrument are, it should be lightweight (< 2Kg), compact (length < 50cm) and cost effective. The instrument is an 80 mm diameter Cassegrain telescope with a field of view of around half a degree designated for UV imaging. In this paper we will discuss about the various science cases that can be performed by having observations with the instrument on different platforms. We will also describe the design, development and the current state of implementation of the instrument. This includes opto-mechanical and e...

  2. Automated Adaptive Brightness in Wireless Capsule Endoscopy Using Image Segmentation and Sigmoid Function.

    Science.gov (United States)

    Shrestha, Ravi; Mohammed, Shahed K; Hasan, Md Mehedi; Zhang, Xuechao; Wahid, Khan A

    2016-08-01

    Wireless capsule endoscopy (WCE) plays an important role in the diagnosis of gastrointestinal (GI) diseases by capturing images of human small intestine. Accurate diagnosis of endoscopic images depends heavily on the quality of captured images. Along with image and frame rate, brightness of the image is an important parameter that influences the image quality which leads to the design of an efficient illumination system. Such design involves the choice and placement of proper light source and its ability to illuminate GI surface with proper brightness. Light emitting diodes (LEDs) are normally used as sources where modulated pulses are used to control LED's brightness. In practice, instances like under- and over-illumination are very common in WCE, where the former provides dark images and the later provides bright images with high power consumption. In this paper, we propose a low-power and efficient illumination system that is based on an automated brightness algorithm. The scheme is adaptive in nature, i.e., the brightness level is controlled automatically in real-time while the images are being captured. The captured images are segmented into four equal regions and the brightness level of each region is calculated. Then an adaptive sigmoid function is used to find the optimized brightness level and accordingly a new value of duty cycle of the modulated pulse is generated to capture future images. The algorithm is fully implemented in a capsule prototype and tested with endoscopic images. Commercial capsules like Pillcam and Mirocam were also used in the experiment. The results show that the proposed algorithm works well in controlling the brightness level accordingly to the environmental condition, and as a result, good quality images are captured with an average of 40% brightness level that saves power consumption of the capsule. PMID:27333609

  3. Relation between the Sunrise photospheric magnetic field and the Ca II H bright features

    Science.gov (United States)

    Jafarzadeh, Shahin; Hirzberger, J.; Feller, A.; Lagg, A.; Solanki, S. K.; Pietarila, A.; Danilovic, S.; Riethmueller, T.; Barthol, P.; Berkefeld, T.; Gandorfer, A.; Knülker, M.; Martínez Pillet, V.; Schmidt, W.; Schüssler, M.; Title, A.

    Recent observations from the Sunrise balloon-borne solar telescope have enabled us to reach an unprecedented high spatial resolution on the solar surface with the near-ultraviolet photo-spheric and chromospheric images as well as the magnetograms. We use these high resolution observations to investigate the structure of the solar upper photosphere and lower chromosphere as well as their temporal evolutions. We study the relation between the inter-granular Ca II 397 nm bright structures in images obtained by the Sunrise Filter Imager (SuFI) and their corresponding photospheric vector magnetic field computed from the Imaging Magnetogram eXperiment (IMaX) observations. The targets under study are in a quiet Sun region and close to disc-centre.

  4. Visible and infrared image registration based on visual salient features

    Science.gov (United States)

    Wu, Feihong; Wang, Bingjian; Yi, Xiang; Li, Min; Hao, Jingya; Qin, Hanlin; Zhou, Huixin

    2015-09-01

    In order to improve the precision of visible and infrared (VIS/IR) image registration, an image registration method based on visual salient (VS) features is presented. First, a VS feature detector based on the modified visual attention model is presented to extract VS points. Because the iterative, within-feature competition method used in visual attention models is time consuming, an alternative fast visual salient (FVS) feature detector is proposed to make VS features more efficient. Then, a descriptor-rearranging (DR) strategy is adopted to describe feature points. This strategy combines information of both IR image and its negative image to overcome the contrast reverse problem between VIS and IR images, making it easier to find the corresponding points on VIS/IR images. Experiments show that both VS and FVS detectors have higher repeatability scores than scale invariant feature transform in the cases of blurring, brightness change, JPEG compression, noise, and viewpoint, except big scale change. The combination of VS detector and DR registration strategy can achieve precise image registration, but it is time-consuming. The combination of FVS detector and DR registration strategy can also reach a good registration of VIS/IR images but in a shorter time.

  5. Extramedullary haematopoiesis: radiological imaging features.

    Science.gov (United States)

    Roberts, A S; Shetty, A S; Mellnick, V M; Pickhardt, P J; Bhalla, S; Menias, C O

    2016-09-01

    Extramedullary haematopoiesis (EMH) is defined as the production of blood cells outside of the bone marrow, which occurs when there is inadequate production of blood cells. The most common causes of EMH are myelofibrosis, diffuse osseous metastatic disease replacing the bone marrow, leukaemia, sickle cell disease, and thalassemia. The purpose of this article is to review the common and uncommon imaging appearances of EMH by anatomical compartment. In the thorax, EMH most commonly presents as paravertebral fat-containing masses, and typically does not present a diagnostic dilemma; however, EMH in the abdomen most commonly manifests as hepatosplenomegaly with or without focal soft-tissue masses in the liver, spleen, perirenal space, and in the peritoneum. Hepatosplenomegaly, a non-specific feature, most often occurs without an associated focal mass, which makes suggestion of EMH difficult. EMH manifesting as visceral soft-tissue masses often requires biopsy as the differential diagnosis can include lymphoma, metastatic disease, and sarcoma. Many of these soft-tissue masses do not contain adipose elements, making the diagnosis of EMH difficult. Clinical history is crucial, as EMH would likely not otherwise be in the differential in patients with non-specific abdominal masses. Careful biopsy planning is necessary when EMH is a diagnostic consideration, given the propensity for haemorrhage. Understanding the typical imaging appearances of EMH based on its site of manifestation can help the radiologist when encountered with a finding that is diagnostic for EMH, and can help the radiologist suggest the need and plan appropriately for image-guided biopsy. PMID:27377325

  6. Feature-based Image Sequence Compression Coding

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    A novel compressing method for video teleconference applications is presented. Semantic-based coding based on human image feature is realized, where human features are adopted as parameters. Model-based coding and the concept of vector coding are combined with the work on image feature extraction to obtain the result.

  7. Surface Brightness Profiles of Galactic Globular Clusters from Hubble Space Telescope Images

    CERN Document Server

    Noyola, E

    2006-01-01

    Hubble Space Telescope allows us to study the central surface brightness profiles for globular clusters at unprecedented detail. We have mined the HST archives to obtain 38 WFPC2 images of galactic globular clusters with adequate exposure times and filters, which we use to measure their central structure. We outline a reliable method to obtain surface brightness profiles from integrated light that we test on an extensive set of simulated images. Most clusters have central surface brightness about 0.5 mag brighter than previous measurements made from ground-based data, with the largest differences around 2 magnitudes. Including the uncertainties in the slope estimates, the surface brightness slope distribution is consistent with half of the sample having flat cores and the remaining half showing a gradual decline from 0 to -0.8 (dlog(Sigma)/dlogr). We deproject the surface brightness profiles in a non-parametric way to obtain luminosity density profiles. The distribution of luminosity density logarithmic slope...

  8. Imaging features of cardiac myxoma

    International Nuclear Information System (INIS)

    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 T1- and T2-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)

  9. Color features for dating historical color images

    OpenAIRE

    Fernando, Basura; Muselet, Damien; Khan, Rahat; Tuytelaars, Tinne

    2014-01-01

    Fernando B., Muselet D., Khan R., Tuytelaars T., ''Color features for dating historical color image'', IEEE international conference on image processing - ICIP 2014, 5 pp., October 27-30, 2014, Paris, France.

  10. Image fusion using sparse overcomplete feature dictionaries

    Energy Technology Data Exchange (ETDEWEB)

    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.

  11. 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.)

  12. Imaging features of iliopsoas bursitis

    International Nuclear Information System (INIS)

    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.)

  13. Deep Bottleneck Feature for Image Classification

    OpenAIRE

    Song, Yan; McLoughlin, Ian Vince; Dai, Lirong

    2015-01-01

    Effective image representation plays an important role for image classification and retrieval. Bag-of-Features (BoF) is well known as an effective and robust visual representation. However, on large datasets, convolutional neural networks (CNN) tend to perform much better, aided by the availability of large amounts of training data. In this paper, we propose a bag of Deep Bottleneck Features (DBF) for image classification, effectively combining the strengths of a CNN within a BoF framework. T...

  14. Bright features in Neptune on 2013-2015 from ground-based observations with small (40 cm) and large telescopes (10 m)

    Science.gov (United States)

    Hueso, Ricardo; Delcroix, Marc; Baranec, Christoph; Sánchez-Lavega, Agustín; María Gómez-Forrellad, Josep; Félix Rojas, Jose; Luszcz-Cook, Statia; de Pater, Imke; de Kleer, Katherine; Colas, François; Guarro, Joan; Goczynski, Peter; Jones, Paul; Kivits, Willem; Maxson, Paul; Phillips, Michael; Sussenbach, John; Wesley, Anthony; Hammel, Heidi B.; Pérez-Hoyos, Santiago; Mendikoa, Iñigo; Riddle, Reed; Law, Nicholas M.; Sayanagi, Kunio

    2015-11-01

    Observations of Neptune over the last few years obtained with small telescopes (30-50 cm) have resulted in several detections of bright features on the planet. In 2013, 2014 and 2015, different observers have repeatedly observed features of high contrast at Neptune’s mid-latitudes using long-pass red filters. This success at observing Neptune clouds with such small telescopes is due to the presence of strong methane absorption bands in Neptune’s spectra at red and near infrared wavelengths; these bands provide good contrast for elevated cloud structures. In each case, the atmospheric features identified in the images survived at least a few weeks, but were essentially much more variable and apparently shorter-lived, than the large convective system recently reported on Uranus [de Pater et al. 2015]. The latest and brightest spot on Neptune was first detected on July 13th 2015 with the 2.2m telescope at Calar Alto observatory with the PlanetCam UPV/EHU instrument. The range of wavelengths covered by PlanetCam (from 350 nm to the H band including narrow-band and wide-band filters in and out of methane bands) allows the study of the vertical cloud structure of this bright spot. In particular, the spot is particularly well contrasted at the H band where it accounted to a 40% of the total planet brightness. Observations obtained with small telescopes a few days later provide a good comparison that can be used to scale similar structures in 2013 and 2014 that were observed with 30-50 cm telescopes and the Robo-AO instrument at Palomar observatory. Further high-resolution observations of the 2015 event were obtained in July 25th with the NIRC2 camera in the Keck 2 10-m telescope. These images show the bright spot as a compact bright feature in H band with a longitudinal size of 8,300 km and a latitudinal extension of 5,300 km, well separated from a nearby bright band. The ensemble of observations locate the structure at -41º latitude drifting at about +24.27º/day or

  15. Bright pituitary stalk on MR T1-weighted image. Damming up phenomenon of the neurosecretory granules

    Energy Technology Data Exchange (ETDEWEB)

    Fujisawa, Ichiro; Uokawa, Kyosuke; Horii, Naotoshi; Murakami, Norihiko; Azuma, Nobuyuki; Furuto-Kato, Sumiko; Yamashita, Kohsuke; Nakao, Satoshi; Kageyama, Naoki [Kishiwada City Hospital, Osaka (Japan)

    2002-04-01

    Characteristic findings of the pituitary stalk on magnetic resonance (MR) imaging, which suggest a damming-up phenomenon of neurosecretory granules, were reported. Neurosecretory granules containing vasopressin influence the signal intensity on MR T1-weighted image (T1WI). The normal posterior lobe of the pituitary gland appears as a bright signal on T1WI. The bright signal of the posterior lobe represents the normal content of neurosecretory granules and disappears in patients with central diabetes insipidus. The normal pituitary stalk appears as a low-intermediate intensity signal on sagittal and coronal T1WIs with 3 mm-slice thickness. The pituitary stalk appeared as a bright signal in 20 patients; 13 with pituitary adenoma, 4 with an intrasellar cystic lesion, one with cavernous sinus mass, and 2 with no abnormal MR findings. The pituitary stalk was not severed in any of the cases. The normal bright signal of the posterior lobe disappeared in 17 patients. No patients suffered from symptoms of central diabetes insipidus when the bright pituitary stalk appeared. It is suggested that the origin of the bright signal in the pituitary stalk is the damming up and accumulation of neurosecretory granules in the nerve fibers of the hypothalamohypophyseal tract obstructed by adenoma, postoperative scarring, cystic mass and so on. Probably, the damming-up phenomenon on MR imaging represents the functional integrity of the hypothalamo-neurohypophyseal system, and should be distinguished from an ectopic posterior lobe formation which is caused by stalk transection. (author)

  16. Multi Feature Content Based Image Retrieval

    Directory of Open Access Journals (Sweden)

    Rajshree S. Dubey,

    2010-09-01

    Full Text Available There are numbers of methods prevailing for Image Mining Techniques. This Paper includes the features of four techniques I,e Color Histogram, Color moment, Texture, and Edge Histogram Descriptor. The nature of the Image is basically based on the Human Perception of the Image. The Machine interpretation of the Image is based on the Contours and surfaces of the Images. The study of the Image Mining is a very challenging task because it involves the Pattern Recognition which is a very important tool for the Machine Vision system. A combination of four feature extraction methods namely color istogram, Color Moment, texture, and Edge Histogram Descriptor. There is a provision to add new features in future for better retrievalefficiency. In this paper the combination of the four techniques are used and the Euclidian distances are calculated of the every features are added and the averages are made .The user interface is provided by the Mat lab. The image properties analyzed in this work are by using computer vision and image processing algorithms. For colorthe histogram of images are computed, for texture co occurrence matrix based entropy, energy, etc, are calculated and for edge density it is Edge Histogram Descriptor (EHD that is found. For retrieval of images, the averages of the four techniques are made and the resultant Image is retrieved.

  17. Content Based Image Retrieval by Multi Features using Image Blocks

    Directory of Open Access Journals (Sweden)

    Arpita Mathur

    2013-12-01

    Full Text Available Content based image retrieval (CBIR is an effective method of retrieving images from large image resources. CBIR is a technique in which images are indexed by extracting their low level features like, color, texture, shape, and spatial location, etc. Effective and efficient feature extraction mechanisms are required to improve existing CBIR performance. This paper presents a novel approach of CBIR system in which higher retrieval efficiency is achieved by combining the information of image features color, shape and texture. The color feature is extracted using color histogram for image blocks, for shape feature Canny edge detection algorithm is used and the HSB extraction in blocks is used for texture feature extraction. The feature set of the query image are compared with the feature set of each image in the database. The experiments show that the fusion of multiple features retrieval gives better retrieval results than another approach used by Rao et al. This paper presents comparative study of performance of the two different approaches of CBIR system in which the image features color, shape and texture are used.

  18. Brightness preserving image enhancement based on a gradient and intensity histogram

    Science.gov (United States)

    Sun, Zebin; Feng, Wenquan; Zhao, Qi; Huang, Lidong

    2015-09-01

    We present a straightforward brightness preserving image enhancement technique. The proposed method is based on an original gradient and intensity histogram (GIH) which contains both gradient and intensity information of the image. This character enables GIH to avoid high peaks in the traditional intensity histogram and, thus alleviate overenhancement in our enhancement method, i.e., gradient and intensity histogram equalization (GIHE). GIHE can also enhance the gradient strength of an image, which is good for improving the subjective quality since the human vision system is more sensitive to the gradient than the absolute intensity of image. Considering that brightness preservation and dynamic range compression are highly demanded in consumer electronics, we manipulate the intensity of the enhanced image appropriately by amplifying the small intensities and attenuating the large intensities, respectively, using a brightness preserving function (BPF). The BPF is straightforward and universal and can be used in other image enhancement techniques. We demonstrate that the proposed method can effectively improve the subjective quality as well as preserve the brightness of the input image.

  19. Retinal image quality assessment using generic features

    Science.gov (United States)

    Fasih, Mahnaz; Langlois, J. M. Pierre; Ben Tahar, Houssem; Cheriet, Farida

    2014-03-01

    Retinal image quality assessment is an important step in automated eye disease diagnosis. Diagnosis accuracy is highly dependent on the quality of retinal images, because poor image quality might prevent the observation of significant eye features and disease manifestations. A robust algorithm is therefore required in order to evaluate the quality of images in a large database. We developed an algorithm for retinal image quality assessment based on generic features that is independent from segmentation methods. It exploits the local sharpness and texture features by applying the cumulative probability of blur detection metric and run-length encoding algorithm, respectively. The quality features are combined to evaluate the image's suitability for diagnosis purposes. Based on the recommendations of medical experts and our experience, we compared a global and a local approach. A support vector machine with radial basis functions was used as a nonlinear classifier in order to classify images to gradable and ungradable groups. We applied our methodology to 65 images of size 2592×1944 pixels that had been graded by a medical expert. The expert evaluated 38 images as gradable and 27 as ungradable. The results indicate very good agreement between the proposed algorithm's predictions and the medical expert's judgment: the sensitivity and specificity for the local approach are respectively 92% and 94%. The algorithm demonstrates sufficient robustness to identify relevant images for automated diagnosis.

  20. Extraction of Facial Features from Color Images

    Directory of Open Access Journals (Sweden)

    J. Pavlovicova

    2008-09-01

    Full Text Available In this paper, a method for localization and extraction of faces and characteristic facial features such as eyes, mouth and face boundaries from color image data is proposed. This approach exploits color properties of human skin to localize image regions – face candidates. The facial features extraction is performed only on preselected face-candidate regions. Likewise, for eyes and mouth localization color information and local contrast around eyes are used. The ellipse of face boundary is determined using gradient image and Hough transform. Algorithm was tested on image database Feret.

  1. 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.

  2. Featured Image: Modeling Supernova Remnants

    Science.gov (United States)

    Kohler, Susanna

    2016-05-01

    This image shows a computer simulation of the hydrodynamics within a supernova remnant. The mixing between the outer layers (where color represents the log of density) is caused by turbulence from the Rayleigh-Taylor instability, an effect that arises when the expanding core gas of the supernova is accelerated into denser shell gas. The past standard for supernova-evolution simulations was to perform them in one dimension and then, in post-processing, manually smooth out regions that undergo Rayleigh-Taylor turbulence (an intrinsically multidimensional effect). But in a recent study, Paul Duffell (University of California, Berkeley) has explored how a 1D model could be used to reproduce the multidimensional dynamics that occur in turbulence from this instability. For more information, check out the paper below!CitationPaul C. Duffell 2016 ApJ 821 76. doi:10.3847/0004-637X/821/2/76

  3. Automatic optic disc segmentation based on image brightness and contrast

    Science.gov (United States)

    Lu, Shijian; Liu, Jiang; Lim, Joo Hwee; Zhang, Zhuo; Tan, Ngan Meng; Wong, Wing Kee; Li, Huiqi; Wong, Tien Yin

    2010-03-01

    Untreated glaucoma leads to permanent damage of the optic nerve and resultant visual field loss, which can progress to blindness. As glaucoma often produces additional pathological cupping of the optic disc (OD), cupdisc- ratio is one measure that is widely used for glaucoma diagnosis. This paper presents an OD localization method that automatically segments the OD and so can be applied for the cup-disc-ratio based glaucoma diagnosis. The proposed OD segmentation method is based on the observations that the OD is normally much brighter and at the same time have a smoother texture characteristics compared with other regions within retinal images. Given a retinal image we first capture the ODs smooth texture characteristic by a contrast image that is constructed based on the local maximum and minimum pixel lightness within a small neighborhood window. The centre of the OD can then be determined according to the density of the candidate OD pixels that are detected by retinal image pixels of the lowest contrast. After that, an OD region is approximately determined by a pair of morphological operations and the OD boundary is finally determined by an ellipse that is fitted by the convex hull of the detected OD region. Experiments over 71 retinal images of different qualities show that the OD region overlapping reaches up to 90.37% according to the OD boundary ellipses determined by our proposed method and the one manually plotted by an ophthalmologist.

  4. Terrain Classification using Multiple Image Features

    Directory of Open Access Journals (Sweden)

    Jharna Majumdar

    2008-05-01

    Full Text Available A wide variety of image processing applications require segmentation and classification ofimages. The problem becomes complex when the images are obtained in an uncontrolledenvironment with a non-uniform illumination. The selection of suitable features is a critical partof an image segmentation and classification process, where the basic objective is to identify theimage regions that are homogeneous but dissimilar to all spatially adjacent regions. This paperproposes an automatic method for the classification of a terrain using image features such asintensity, texture, and edge. The textural features are calculated using statistics of geometricalattributes of connected regions in a sequence of binary images obtained from a texture image.A pixel-wise image segmentation scheme using a multi-resolution pyramid is used to correct thesegmentation process so as to get homogeneous image regions. Localisation of texture boundariesis done using a refined-edge map obtained by convolution, thinning, thresholding, and linking.The individual regions are classified using a database generated from the features extracted fromknown samples of the actual terrain. The algorithm is used to classify airborne images of a terrainobtained from the sensor mounted on an aerial reconnaissance platform and the results arepresented.

  5. Automatic Extraction of Planetary Image Features

    Science.gov (United States)

    Troglio, G.; LeMoigne, J.; Moser, G.; Serpico, S. B.; Benediktsson, J. A.

    2009-01-01

    With the launch of several Lunar missions such as the Lunar Reconnaissance Orbiter (LRO) and Chandrayaan-1, a large amount of Lunar images will be acquired and will need to be analyzed. Although many automatic feature extraction methods have been proposed and utilized for Earth remote sensing images, these methods are not always applicable to Lunar data that often present low contrast and uneven illumination characteristics. In this paper, we propose a new method for the extraction of Lunar features (that can be generalized to other planetary images), based on the combination of several image processing techniques, a watershed segmentation and the generalized Hough Transform. This feature extraction has many applications, among which image registration.

  6. MULTI-FEATURE MUTUAL INFORMATION IMAGE REGISTRATION

    Directory of Open Access Journals (Sweden)

    Dejan Tomaževič

    2012-03-01

    Full Text Available Nowadays, information-theoretic similarity measures, especially the mutual information and its derivatives, are one of the most frequently used measures of global intensity feature correspondence in image registration. Because the traditional mutual information similarity measure ignores the dependency of intensity values of neighboring image elements, registration based on mutual information is not robust in cases of low global intensity correspondence. Robustness can be improved by adding spatial information in the form of local intensity changes to the global intensity correspondence. This paper presents a novel method, by which intensities, together with spatial information, i.e., relations between neighboring image elements in the form of intensity gradients, are included in information-theoretic similarity measures. In contrast to a number of heuristic methods that include additional features into the generic mutual information measure, the proposed method strictly follows information theory under certain assumptions on feature probability distribution. The novel approach solves the problem of efficient estimation of multifeature mutual information from sparse high-dimensional feature space. The proposed measure was tested on magnetic resonance (MR and computed tomography (CT images. In addition, the measure was tested on positron emission tomography (PET and MR images from the widely used Retrospective Image Registration Evaluation project image database. The results indicate that multi-feature mutual information, which combines image intensities and intensity gradients, is more robust than the standard single-feature intensity based mutual information, especially in cases of low global intensity correspondences, such as in PET/MR images or significant intensity inhomogeneity.

  7. A new method for imaging faint objects nearby a bright source

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    In astronomical observation, it is difficult to obtain the image of faint objects in the peripheral area around a bright celestial body. In order to solve the problem, a new method is designed and experimented, which is called the separation readout technique (SRT). SRT is different from either the traditional coronagraphy or the newly-developed anti-blooming CCD technique, and allows an enough-long exposure to the faint objects in the area around a bright celestial body with the well-preserved bright body's image in one frame. This paper describes in detail the principle of SRT, the computer simulation, the experimental devising and result of SRT observation on a telescope.

  8. 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.)

  9. Exact feature probabilities in images with occlusion

    CERN Document Server

    Pitkow, Xaq

    2010-01-01

    To understand the computations of our visual system, it is important to understand also the natural environment it evolved to interpret. Unfortunately, existing models of the visual environment are either unrealistic or too complex for mathematical description. Here we describe a naturalistic image model and present a mathematical solution for the statistical relationships between the image features and model variables. The world described by this model is composed of independent, opaque, textured objects which occlude each other. This simple structure allows us to calculate the joint probability distribution of image values sampled at multiple arbitrarily located points, without approximation. This result can be converted into probabilistic relationships between observable image features as well as between the unobservable properties that caused these features, including object boundaries and relative depth. Using these results we explain the causes of a wide range of natural scene properties, including high...

  10. 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 is...... used in a general puzzle solving method which is based on a greedy algorithm previously proved successful. We have been able to solve computer generated puzzles of 320 pieces as well as a real puzzle of 54 pieces by exclusively using image information. Additionally, we investigate a new scalable...... algorithm which exploits the divide and conquer paradigm to reduce the combinatorially complex problem by classifying the puzzle pieces and comparing pieces drawn from the same group. The paper includes a brief preliminary investigation of some image features used in the classification....

  11. Automatic extraction of planetary image features

    Science.gov (United States)

    LeMoigne-Stewart, Jacqueline J. (Inventor); Troglio, Giulia (Inventor); Benediktsson, Jon A. (Inventor); Serpico, Sebastiano B. (Inventor); Moser, Gabriele (Inventor)

    2013-01-01

    A method for the extraction of Lunar data and/or planetary features is provided. The feature extraction method can include one or more image processing techniques, including, but not limited to, a watershed segmentation and/or the generalized Hough Transform. According to some embodiments, the feature extraction method can include extracting features, such as, small rocks. According to some embodiments, small rocks can be extracted by applying a watershed segmentation algorithm to the Canny gradient. According to some embodiments, applying a watershed segmentation algorithm to the Canny gradient can allow regions that appear as close contours in the gradient to be segmented.

  12. Field application of feature-enhanced imaging

    International Nuclear Information System (INIS)

    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

  13. High-brightness electron beams for ultrafast electron microdiffraction and imaging

    Science.gov (United States)

    Sun, Tianyin; Zhou, Faran; Chang, Kiseok; Tao, Zhensheng; Williams, Joe; Ruan, Chong-Yu; MSU UEM Collaboration

    Currently the ultrafast electron diffraction has achieved sub-picosecond temporal resolution and atomic resolution. However, direct ultrafast imaging of a nanometer scale specimen through coherent single-particle diffraction has not been achieved largely due to insufficient intensity when tuned to a coherence length that matches the size of the specimen under the projected phase space density. Utilizing a recently implemented high-brightness electron source with flexible optical design, we test the performance of ultrafast electron microdiffraction and coherence imaging. We demonstrate the feasibilities of single-shot microdiffraction on a single micrometer-sized domain in Highly Ordered Pyrolytic Graphite (HOPG) and coherent diffractive imaging of 10 nm scale charge-ordered domain structures in single-crystal complex materials, as validated by the measured brightness at the sample plane. These initial results show that source-limited performance even from a sub-relativistic electron beamline can drastically improve the current performance of ultrafast electron imaging and diffraction.

  14. Approximating tasseled cap values to evaluate brightness, greenness, and wetness for the Advanced Land Imager (ALI)

    Science.gov (United States)

    Yamamoto, Kristina H.; Finn, Michael P.

    2012-01-01

    The Tasseled Cap transformation is a method of image band conversion to enhance spectral information. It primarily is used to detect vegetation using the derived brightness, greenness, and wetness bands. An approximation of Tasseled Cap values for the Advanced Land Imager was investigated and compared to the Landsat Thematic Mapper Tasseled Cap values. Despite sharing similar spectral, temporal, and spatial resolution, the two systems are not interchangeable with regard to Tasseled Cap matrices.

  15. Edge detection and reduction of brightness of students' bubble form images

    Science.gov (United States)

    Ilkin, Sümeyya; Şahin, Suhap

    2015-03-01

    Optical Mark Recognition (OMR) is a traditional data input technique and an important human computer interaction technique which is widely used in education testing. This paper proposes a new idea for grading multiple-choice test which is based on a camera on smartphone. The system key techniques and relevant implementations, which include the image scan, edge detection and reduction of brightness on colorful bubble form images, are presented.

  16. Automatic Feature Extraction from Planetary Images

    Science.gov (United States)

    Troglio, Giulia; Le Moigne, Jacqueline; Benediktsson, Jon A.; Moser, Gabriele; Serpico, Sebastiano B.

    2010-01-01

    With the launch of several planetary missions in the last decade, a large amount of planetary images has already been acquired and much more will be available for analysis in the coming years. The image data need to be analyzed, preferably by automatic processing techniques because of the huge amount of data. Although many automatic feature extraction methods have been proposed and utilized for Earth remote sensing images, these methods are not always applicable to planetary data that often present low contrast and uneven illumination characteristics. Different methods have already been presented for crater extraction from planetary images, but the detection of other types of planetary features has not been addressed yet. Here, we propose a new unsupervised method for the extraction of different features from the surface of the analyzed planet, based on the combination of several image processing techniques, including a watershed segmentation and the generalized Hough Transform. The method has many applications, among which image registration and can be applied to arbitrary planetary images.

  17. Secret data embedding scheme modifying the frequency of occurrence of image brightness values

    Indian Academy of Sciences (India)

    Yildiray Yalman; Ismail Erturk

    2014-08-01

    The main purpose of this presented work is to develop a data embedding method based on a new digital image histogram modification approach. The proposed scheme fundamentally is concerned about the frequency of occurrence of the image brightness values of the cover image for the data embedding procedures. The proposed scheme effectively realizes both perceptual invisibility and statistical invisibility so that obtained covered images are highly robust against common perceptual and statistical steganalysis techniques. The scheme provides reasonably higher payload values than its counterparts, as well as providing comparatively improved PSNR results.

  18. Near-Infrared Imaging of Barred Halo Dominated Low Surface Brightness Galaxies

    OpenAIRE

    Honey, M.; Das, M.; Ninan, J. P.; Purvankara, M.

    2016-01-01

    We present a near-infrared (NIR) imaging study of barred low surface brightness (LSB) galaxies using the TIFR near-infrared Spectrometer and Imager (TIRSPEC). LSB galaxies are dark matter dominated, late type spirals that have low luminosity stellar disks but large neutral hydrogen (HI) gas disks. Using SDSS images of a very large sample of LSB galaxies derived from the literature, we found that the barred fraction is only 8.3%. We imaged twenty five barred LSB galaxies in the J, H, K$_S$ wav...

  19. Sunspot Bright Points

    CERN Document Server

    Choudhary, Debi Prasad

    2010-01-01

    We used the flux calibrated images through the Broad Band Filter Imager and Stokes Polarimeter data obtained with the Solar Optical Telescope onboard the Hinode spacecraft to study the properties of bright points in and around the sunspots. The well isolated bright points were selected and classified as umbral dot, peripheral umbral dot, penumbral grains and G-band bright point depending on their location. Most of the bright points are smaller than about 150 km. The larger points are mostly associated with the penumbral features. The bright points are not uniformly distributed over the umbra but preferentially located around the penumbral boundary and in the fast decaying parts of umbra. The color temperature of the bright points, derived using the continuum irradiance, are in the range of 4600 K to 6600 K with cooler ones located in the umbra. The temperature increases as a function of distance from the center to outside. The G-band, CN-band and CaII H flux of the bright points as a function of their blue ba...

  20. Featured Image: A New Look at Malin 1

    Science.gov (United States)

    Kohler, Susanna

    2016-01-01

    Monochrome, inverted version of Malin 1. [Adapted from Galaz et al. 2015]The above image of Malin 1, the faintest and largest low-surface-brightness galaxy ever observed, was obtained with an instrument called Megacam on the 6.5m Magellan/Clay telescope. Gaspar Galaz (Pontifical Catholic University of Chile) and collaborators used Megacam to obtain deep optical observations of Malin 1. They then used novel noise-reduction and image-processing techniques to create this spectacular image of the spiral galaxy located roughly 1.2 billion light-years away. This new view of Malin 1 reveals details weve never before seen, including a stream within the disk that may have been caused by a past interaction between Malin 1 and another galaxy near it. Check outthe image to the rightfor a monochrome, inverted version thatmakes it a little easier to see some of Malin 1s features. To see the full original images and to learn more about what the images reveal about Malin 1, see the paper below.CitationGaspar Galaz et al 2015 ApJ 815 L29. doi:10.1088/2041-8205/815/2/L29

  1. Onboard Image Registration from Invariant Features

    Science.gov (United States)

    Wang, Yi; Ng, Justin; Garay, Michael J.; Burl, Michael C

    2008-01-01

    This paper describes a feature-based image registration technique that is potentially well-suited for onboard deployment. The overall goal is to provide a fast, robust method for dynamically combining observations from multiple platforms into sensors webs that respond quickly to short-lived events and provide rich observations of objects that evolve in space and time. The approach, which has enjoyed considerable success in mainstream computer vision applications, uses invariant SIFT descriptors extracted at image interest points together with the RANSAC algorithm to robustly estimate transformation parameters that relate one image to another. Experimental results for two satellite image registration tasks are presented: (1) automatic registration of images from the MODIS instrument on Terra to the MODIS instrument on Aqua and (2) automatic stabilization of a multi-day sequence of GOES-West images collected during the October 2007 Southern California wildfires.

  2. Bright-Field Imaging and Optical Coherence Tomography of the Mouse Posterior Eye.

    Science.gov (United States)

    Krebs, Mark P; Xiao, Mei; Sheppard, Keith; Hicks, Wanda; Nishina, Patsy M

    2016-01-01

    Noninvasive live imaging has been used extensively for ocular phenotyping in mouse vision research. Bright-field imaging and optical coherence tomography (OCT) are two methods that are particularly useful for assessing the posterior mouse eye (fundus), including the retina, retinal pigment epithelium, and choroid, and are widely applied due to the commercial availability of sophisticated instruments and software. Here, we provide a guide to using these approaches with an emphasis on post-acquisition image processing using Fiji, a bundled version of the Java-based public domain software ImageJ. A bright-field fundus imaging protocol is described for acquisition of multi-frame videos, followed by image registration to reduce motion artifacts, averaging to reduce noise, shading correction to compensate for uneven illumination, filtering to improve image detail, and rotation to adjust orientation. An OCT imaging protocol is described for acquiring replicate volume scans, with subsequent registration and averaging to yield three-dimensional datasets that show reduced motion artifacts and enhanced detail. The Fiji algorithms used in these protocols are designed for batch processing and are freely available. The image acquisition and processing approaches described here may facilitate quantitative phenotyping of the mouse eye in drug discovery, mutagenesis screening, and the functional cataloging of mouse genes by individual laboratories and large-scale projects, such as the Knockout Mouse Phenotyping Project and International Mouse Phenotyping Consortium. PMID:27150100

  3. Image Mining Using Texture and Shape Feature

    Directory of Open Access Journals (Sweden)

    Prof.Rupali Sawant

    2010-12-01

    Full Text Available Discovering knowledge from data stored in typical alphanumeric databases, such as relational databases, has been the focal point of most of the work in database mining. However, with advances in secondary and tertiary storage capacity, coupled with a relatively low storage cost, more and more non standard data (in the form of images is being accumulated. This vast collection of image data can also be mined to discover new and valuable knowledge. During theprocess of image mining, the concepts in different hierarchiesand their relationships are extracted from different hierarchies and granularities, and association rule mining and concept clustering are consequently implemented. The generalization and specialization of concepts are realized in different hierarchies, lower layer concepts can be upgraded to upper layer concepts, and upper layer concepts guide the extraction of lower layer concepts. It is a process from image data to image information, from image information to imageknowledge, from lower layer concepts to upper layer concept lattice and cloud model theory is proposed. The methods of image mining from image texture and shape features are introduced here, which include the following basic steps: firstly pre-process images secondly use cloud model to extract concepts, lastly use concept lattice to extracta series of image knowledge.

  4. Imaging features of retrorectal masses in adult

    International Nuclear Information System (INIS)

    Retrorectal masses have several etiologies. They could be of congenital origin owing to the complexity of the embryogenesis in this area. This report concerns a semiological analysis based on a series of 46 cases with a review of literature. The different pathological features are described. The actual imaging technics have much improved diagnostic criterias, thus providing a better therapeutic choice. (19 figs)

  5. Image processing and feature extraction of microscopic

    Directory of Open Access Journals (Sweden)

    Shi Chun Hua

    2016-01-01

    Full Text Available This paper analyzes the characteristics of white blood cells, diseased cells during feature extraction, the introduction of anti-corrosion factor for microscopic image processing, experiments show that the method of classification and extraction of diseased cells have better results.

  6. Ultra-fast bright field and fluorescence imaging of the dynamics of micrometer-sized objects

    Science.gov (United States)

    Chen, Xucai; Wang, Jianjun; Versluis, Michel; de Jong, Nico; Villanueva, Flordeliza S.

    2013-06-01

    High speed imaging has application in a wide area of industry and scientific research. In medical research, high speed imaging has the potential to reveal insight into mechanisms of action of various therapeutic interventions. Examples include ultrasound assisted thrombolysis, drug delivery, and gene therapy. Visual observation of the ultrasound, microbubble, and biological cell interaction may help the understanding of the dynamic behavior of microbubbles and may eventually lead to better design of such delivery systems. We present the development of a high speed bright field and fluorescence imaging system that incorporates external mechanical waves such as ultrasound. Through collaborative design and contract manufacturing, a high speed imaging system has been successfully developed at the University of Pittsburgh Medical Center. We named the system "UPMC Cam," to refer to the integrated imaging system that includes the multi-frame camera and its unique software control, the customized modular microscope, the customized laser delivery system, its auxiliary ultrasound generator, and the combined ultrasound and optical imaging chamber for in vitro and in vivo observations. This system is capable of imaging microscopic bright field and fluorescence movies at 25 × 106 frames per second for 128 frames, with a frame size of 920 × 616 pixels. Example images of microbubble under ultrasound are shown to demonstrate the potential application of the system.

  7. Robustness of the Digital Image Watermarking Techniques against Brightness and Rotation Attack

    Directory of Open Access Journals (Sweden)

    Raman Kumar, Singh

    2009-09-01

    Full Text Available The recent advent in the field of multimedia proposed a many facilities in transport, transmission and manipulation of data. Along with this advancement of facilities there are larger threats in authentication of data, its licensed use and protection against illegal use of data. A lot of digital image watermarking techniques have been designed and implemented to stop the illegal use of the digital multimedia images. This paper compares the robustness of three different watermarking schemes against brightness and rotation attacks. The robustness of the watermarked images has been verified on the parameters of PSNR (Peak Signal to Noise Ratio, RMSE (Root Mean Square Error and MAE (Mean Absolute Error.

  8. Vector quantizer based on brightness maps for image compression with the polynomial transform

    Science.gov (United States)

    Escalante-Ramirez, Boris; Moreno-Gutierrez, Mauricio; Silvan-Cardenas, Jose L.

    2002-11-01

    We present a vector quantization scheme acting on brightness fields based on distance/distortion criteria correspondent with psycho-visual aspects. These criteria quantify sensorial distortion between vectors that represent either portions of a digital image or alternatively, coefficients of a transform-based coding system. In the latter case, we use an image representation model, namely the Hermite transform, that is based on some of the main perceptual characteristics of the human vision system (HVS) and in their response to light stimulus. Energy coding in the brightness domain, determination of local structure, code-book training and local orientation analysis are all obtained by means of the Hermite transform. This paper, for thematic reasons, is divided in four sections. The first one will shortly highlight the importance of having newer and better compression algorithms. This section will also serve to explain briefly the most relevant characteristics of the HVS, advantages and disadvantages related with the behavior of our vision in front of ocular stimulus. The second section shall go through a quick review of vector quantization techniques, focusing their performance on image treatment, as a preview for the image vector quantizer compressor actually constructed in section 5. Third chapter was chosen to concentrate the most important data gathered on brightness models. The building of this so-called brightness maps (quantification of the human perception on the visible objects reflectance), in a bi-dimensional model, will be addressed here. The Hermite transform, a special case of polynomial transforms, and its usefulness, will be treated, in an applicable discrete form, in the fourth chapter. As we have learned from previous works 1, Hermite transform has showed to be a useful and practical solution to efficiently code the energy within an image block, deciding which kind of quantization is to be used upon them (whether scalar or vector). It will also be

  9. MR imaging features of adrenal rest tumor

    International Nuclear Information System (INIS)

    Objective: To investigate the imaging features of adrenal rest tumor. Methods: Twelve patients of adrenal rest tumor proved by surgery or clinical diagnosis were retrospectively analyzed. Among these 12 patients, 12 were examined with ultrasound, 11 with MR and 1 with CT. MR and CT were performed without and with intravenous injection of contrast material. The imaging features of adrenal rest tumor were retrospectively summarized and the relevant literatures reviewed. Results: The adrenal rest tumors were found in testis in 10 of the 12 patients, and in ovaries and broad ligament in the remaining two. The imaging features of the testicular adrenal rest tumor were summarized as following: all patients had bilateral testicular masses without change of the testicular contour. On ultrasonography, the lesions were hypoechoic, with some hyperechoic areas and appeared highly vascularized on Colour Doppler ultrasonography. The masses showed iso-density on plain CT, and avid enhancement on post-contrast CT images. The masses ranging in size from 0.7 cm×1.0 cm×2.2 cm to 2.3 cm ×2.7 cm ×2.9 cm with uniform signal intensity, lobulated margin on MRI. They exhibited iso- or slight hyperintensity on T1WI and hypointensity on T2WI relative to normal testicular parenchyma. The tumors showed intense enhancement on post-contrast MR images. No abnormality was detected with Colour Doppler ultrasonography and MR in 2 patients of adrenal rest tumor in ovaries and broad ligament. Conclusion: Combining imaging features with the typical clinical history,the diagnosis of adrenal rest tumor could be suggested pre-operatively. (authors)

  10. Hyperspectral image feature extraction accelerated by GPU

    Science.gov (United States)

    Qu, HaiCheng; Zhang, Ye; Lin, Zhouhan; Chen, Hao

    2012-10-01

    PCA (principal components analysis) algorithm is the most basic method of dimension reduction for high-dimensional data1, which plays a significant role in hyperspectral data compression, decorrelation, denoising and feature extraction. With the development of imaging technology, the number of spectral bands in a hyperspectral image is getting larger and larger, and the data cube becomes bigger in these years. As a consequence, operation of dimension reduction is more and more time-consuming nowadays. Fortunately, GPU-based high-performance computing has opened up a novel approach for hyperspectral data processing6. This paper is concerning on the two main processes in hyperspectral image feature extraction: (1) calculation of transformation matrix; (2) transformation in spectrum dimension. These two processes belong to computationally intensive and data-intensive data processing respectively. Through the introduction of GPU parallel computing technology, an algorithm containing PCA transformation based on eigenvalue decomposition 8(EVD) and feature matching identification is implemented, which is aimed to explore the characteristics of the GPU parallel computing and the prospects of GPU application in hyperspectral image processing by analysing thread invoking and speedup of the algorithm. At last, the result of the experiment shows that the algorithm has reached a 12x speedup in total, in which some certain step reaches higher speedups up to 270 times.

  11. Multispectral image fusion based on fractal features

    Science.gov (United States)

    Tian, Jie; Chen, Jie; Zhang, Chunhua

    2004-01-01

    Imagery sensors have been one indispensable part of the detection and recognition systems. They are widely used to the field of surveillance, navigation, control and guide, et. However, different imagery sensors depend on diverse imaging mechanisms, and work within diverse range of spectrum. They also perform diverse functions and have diverse circumstance requires. So it is unpractical to accomplish the task of detection or recognition with a single imagery sensor under the conditions of different circumstances, different backgrounds and different targets. Fortunately, the multi-sensor image fusion technique emerged as important route to solve this problem. So image fusion has been one of the main technical routines used to detect and recognize objects from images. While, loss of information is unavoidable during fusion process, so it is always a very important content of image fusion how to preserve the useful information to the utmost. That is to say, it should be taken into account before designing the fusion schemes how to avoid the loss of useful information or how to preserve the features helpful to the detection. In consideration of these issues and the fact that most detection problems are actually to distinguish man-made objects from natural background, a fractal-based multi-spectral fusion algorithm has been proposed in this paper aiming at the recognition of battlefield targets in the complicated backgrounds. According to this algorithm, source images are firstly orthogonally decomposed according to wavelet transform theories, and then fractal-based detection is held to each decomposed image. At this step, natural background and man-made targets are distinguished by use of fractal models that can well imitate natural objects. Special fusion operators are employed during the fusion of area that contains man-made targets so that useful information could be preserved and features of targets could be extruded. The final fused image is reconstructed from the

  12. 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.

  13. 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

  14. Microburst applications of brightness temperature difference between GOES Imager channels 3 and 4

    CERN Document Server

    Pryor, Kenneth L

    2010-01-01

    This paper presents a new application of brightness temperature difference (BTD) between Geostationary Operational Environmental Satellite (GOES) imager channels 3 and 4. It has been found recently that the BTD between GOES infrared channel 3 (water vapor) and channel 4 (thermal infrared) can highlight regions where severe outflow wind generation (i.e. downbursts, microbursts) is likely due to the channeling of dry mid-tropospheric air into the precipitation core of a deep, moist convective storm. Case studies demonstrating effective operational use of this image product are presented for two significant marine transportation accidents as well as a severe downburst event over the Washington, DC metropolitan area in April 2010.

  15. Availability of color calibration for consistent color display in medical images and optimization of reference brightness for clinical use

    Science.gov (United States)

    Iwai, Daiki; Suganami, Haruka; Hosoba, Minoru; Ohno, Kazuko; Emoto, Yutaka; Tabata, Yoshito; Matsui, Norihisa

    2013-03-01

    Color image consistency has not been accomplished yet except the Digital Imaging and Communication in Medicine (DICOM) Supplement 100 for implementing a color reproduction pipeline and device independent color spaces. Thus, most healthcare enterprises could not check monitor degradation routinely. To ensure color consistency in medical color imaging, monitor color calibration should be introduced. Using simple color calibration device . chromaticity of colors including typical color (Red, Green, Blue, Green and White) are measured as device independent profile connection space value called u'v' before and after calibration. In addition, clinical color images are displayed and visual differences are observed. In color calibration, monitor brightness level has to be set to quite lower value 80 cd/m2 according to sRGB standard. As Maximum brightness of most color monitors available currently for medical use have much higher brightness than 80 cd/m2, it is not seemed to be appropriate to use 80 cd/m2 level for calibration. Therefore, we propose that new brightness standard should be introduced while maintaining the color representation in clinical use. To evaluate effects of brightness to chromaticity experimentally, brightness level is changed in two monitors from 80 to 270cd/m2 and chromaticity value are compared with each brightness levels. As a result, there are no significant differences in chromaticity diagram when brightness levels are changed. In conclusion, chromaticity is close to theoretical value after color calibration. Moreover, chromaticity isn't moved when brightness is changed. The results indicate optimized reference brightness level for clinical use could be set at high brightness in current monitors .

  16. 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.

  17. Near-Infrared Imaging of Barred Halo Dominated Low Surface Brightness Galaxies

    CERN Document Server

    Honey, M; Ninan, J P; Purvankara, M

    2016-01-01

    We present a near-infrared (NIR) imaging study of barred low surface brightness (LSB) galaxies using the TIFR near-infrared Spectrometer and Imager (TIRSPEC). LSB galaxies are dark matter dominated, late type spirals that have low luminosity stellar disks but large neutral hydrogen (HI) gas disks. Using SDSS images of a very large sample of LSB galaxies derived from the literature, we found that the barred fraction is only 8.3%. We imaged twenty five barred LSB galaxies in the J, H, K$_S$ wavebands and twenty nine in the K$_S$ band. Most of the bars are much brighter than their stellar disks, which appear to be very diffuse. Our image analysis gives deprojected mean bar sizes of $R_{b}/R_{25}$ = 0.40 and ellipticities $e$ $\\approx$ 0.45, which are similar to bars in high surface brightness galaxies. Thus, although bars are rare in LSB galaxies, they appear to be just as strong as bars found in normal galaxies. There is no correlation of $R_{b}/R_{25}$ or $e$ with the relative HI or stellar masses of the galax...

  18. Image Denoising with Modified Wavelets Feature Restoration

    Directory of Open Access Journals (Sweden)

    Sachin D Ruikar

    2012-03-01

    Full Text Available Image Denoising is the principle problem of image restoration and many scholars have been devoted to this area and proposed lots of methods. In this paper we propose modified feature restoration algorithm based on threshold and neighbor technique which gives better result for all types of noise. Because of some limits of conventional methods in image denoising, several drawbacks are seen in the conventional methods such as introduction of blur and edges degradation. Those can be removed by using the new technique which is based on the wavelet transforms. The shrinkage algorithms like Universal shrink, Visue shrink, bays shrink; have strengths in Gaussian noise removal. Our proposed method gives noise removal for all types of noise, in wavelet domain. It gives a better peak signal to noise ratio as compared to traditional methods.

  19. 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.)

  20. Bright-field imaging of compound semiconductors using aberration-corrected scanning transmission electron microscopy

    Science.gov (United States)

    Aoki, Toshihiro; Lu, Jing; McCartney, Martha R.; Smith, David J.

    2016-09-01

    This study reports the observation of six different zincblende compound semiconductors in [110] projection using large-collection-angle bright-field (LABF) imaging with an aberration-corrected scanning transmission electron microscope. Phase contrast is completely suppressed when the collection semi-angle is set equal to the convergence semi-angle and there are no reversals in image contrast with changes in defocus or thickness. The optimum focus for imaging closely separated pairs of atomic columns (‘dumbbells’) is unique and easily recognized, and the positions of atomic columns occupied by heavier atoms always have darker intensity than those occupied by lighter atoms. Thus, the crystal polarity of compound semiconductors can be determined unambiguously. Moreover, it is concluded that the LABF imaging mode will be highly beneficial for studying other more complicated heterostructures at the atomic scale.

  1. A hybrid features based image matching algorithm

    Science.gov (United States)

    Tu, Zhenbiao; Lin, Tao; Sun, Xiao; Dou, Hao; Ming, Delie

    2015-12-01

    In this paper, we present a novel image matching method to find the correspondences between two sets of image interest points. The proposed method is based on a revised third-order tensor graph matching method, and introduces an energy function that takes four kinds of energy term into account. The third-order tensor method can hardly deal with the situation that the number of interest points is huge. To deal with this problem, we use a potential matching set and a vote mechanism to decompose the matching task into several sub-tasks. Moreover, the third-order tensor method sometimes could only find a local optimum solution. Thus we use a cluster method to divide the feature points into some groups and only sample feature triangles between different groups, which could make the algorithm to find the global optimum solution much easier. Experiments on different image databases could prove that our new method would obtain correct matching results with relatively high efficiency.

  2. Integrated Feature Extraction for Image Retrieval

    OpenAIRE

    Poorani M; Prathiba T; Ravindran G

    2013-01-01

    To retrieve the images from large database that are highly related to the query image where query image is given by user. Three features are used for retrieving the images, which are color, shape and texture. These features are extracted by different techniques. Color feature is extracted by Color Histogram and Color Descriptor. Shape feature is extracted by Hu Moment and Edge detection Method. Texture feature is extracted by Gray Level co-occurrence matrix and texture descriptor. We Compare ...

  3. 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.)

  4. 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

  5. Image Processing Based Customized Image Editor and Gesture Controlled Embedded Robot Coupled with Voice Control Features

    Directory of Open Access Journals (Sweden)

    Somnath Kar

    2015-11-01

    Full Text Available In modern sciences and technologies, images gain much broader scopes due to the ever growing importance of scientific visualization (of often large-scale complex scientific/experimental data like microarray data in genetic research, or real-time multi-asset portfolio trading in finance etc. In this paper, a proposal has been presented to implement a Graphical User Interface (GUI consisting of various MATLAB functions related to image processing and using the same to create a basic image processing editor having different features like, viewing the red, green and blue components of a color image separately, color detection and various other features like noise addition and removal, edge detection, cropping, resizing, rotation, histogram adjust, brightness control that is used in a basic image editor along with object detection and tracking. This has been further extended to provide reliable and a more natural technique for the user to navigate a robot in the natural environment using gestures based on color tracking. Additionally, Voice control technique has been employed to navigate the robot in various directions in the Cartesian plane employing normal Speech recognition techniques available in Microsoft Visual Basic.

  6. Augmented microscopy: real-time overlay of bright-field and near-infrared fluorescence images

    Science.gov (United States)

    Watson, Jeffrey R.; Gainer, Christian F.; Martirosyan, Nikolay; Skoch, Jesse; Lemole, G. Michael, Jr.; Anton, Rein; Romanowski, Marek

    2015-10-01

    Intraoperative applications of near-infrared (NIR) fluorescent contrast agents can be aided by instrumentation capable of merging the view of surgical field with that of NIR fluorescence. We demonstrate augmented microscopy, an intraoperative imaging technique in which bright-field (real) and electronically processed NIR fluorescence (synthetic) images are merged within the optical path of a stereomicroscope. Under luminance of 100,000 lx, representing typical illumination of the surgical field, the augmented microscope detects 189 nM concentration of indocyanine green and produces a composite of the real and synthetic images within the eyepiece of the microscope at 20 fps. Augmentation described here can be implemented as an add-on module to visualize NIR contrast agents, laser beams, or various types of electronic data within the surgical microscopes commonly used in neurosurgical, cerebrovascular, otolaryngological, and ophthalmic procedures.

  7. Augmented microscopy: real-time overlay of bright-field and near-infrared fluorescence images.

    Science.gov (United States)

    Watson, Jeffrey R; Gainer, Christian F; Martirosyan, Nikolay; Skoch, Jesse; Lemole, G Michael; Anton, Rein; Romanowski, Marek

    2015-10-01

    Intraoperative applications of near-infrared (NIR) fluorescent contrast agents can be aided by instrumentation capable of merging the view of surgical field with that of NIR fluorescence. We demonstrate augmented microscopy, an intraoperative imaging technique in which bright-field (real) and electronically processed NIR fluorescence (synthetic) images are merged within the optical path of a stereomicroscope. Under luminance of 100,000 lx, representing typical illumination of the surgical field, the augmented microscope detects 189 nM concentration of indocyanine green and produces a composite of the real and synthetic images within the eyepiece of the microscope at 20 fps. Augmentation described here can be implemented as an add-on module to visualize NIR contrast agents, laser beams, or various types of electronic data within the surgical microscopes commonly used in neurosurgical, cerebrovascular, otolaryngological, and ophthalmic procedures. PMID:26440760

  8. Magnetic Resonance Imaging Features of Neuromyelitis Optica

    International Nuclear Information System (INIS)

    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.

  9. 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.

  10. Color image retrieval using edge and edge-spatial features

    Institute of Scientific and Technical Information of China (English)

    Chaobing Huang; Quan Liu

    2006-01-01

    @@ A novel methodology to integrate edge feature and edge-spatial feature of an image is proposed. The edge feature is described by edge histogram of image, the edge-spatial feature is described by spatial distribution of pixels of identical edge value in the image. Experimental results show that the method can achieve better retrieval performance, especially for color natural images with more complex spatial layout.

  11. Targeted imaging of EGFR overexpressed cancer cells by brightly fluorescent nanoparticles conjugated with cetuximab.

    Science.gov (United States)

    Gao, Meng; Su, Huifang; Lin, Gengwei; Li, Shiwu; Yu, Xingsu; Qin, Anjun; Zhao, Zujin; Zhang, Zhenfeng; Tang, Ben Zhong

    2016-08-11

    To improve the treatment efficiency and reduce side effects in cancer therapy, accurate diagnosis of cancer cell types at a molecular level is highly desirable. Fluorescent nanoparticles (NPs) are especially suitable for detecting molecular biomarkers of cancer with advantages of superior brightness, easy decoration and high resolution. However, the conventional organic fluorophores, conjugated polymers, and inorganic quantum dots suffer from the drawbacks of aggregation-caused quenching (ACQ), low photostability, and heavy metal toxicity, respectively, which severely restrict their applications in NPs-based fluorescence imaging. To overcome these limitations, herein, we have developed fluorescent nanoparticles based on a t-BuPITBT-TPE fluorophore derived from aggregation-induced emission (AIE)-active tetraphenylethene. Through encapsulating t-BuPITBT-TPE within biocompatible DSPE-PEG and further decorating with a monoclonal antibody cetuximab (C225), the obtained t-BuPITBT-TPE-C225 NPs can be used for targeted imaging of non-small cell lung cancer cells with an overexpressed epidermal growth factor receptor (EGFR). The specific targeting ability of t-BuPITBT-TPE-C225 NPs has been well verified by confocal microscopy and flow cytometry experiments. The t-BuPITBT-TPE-C225 NPs have shown significant advantages in terms of highly efficient red emission, good bio-compatibility, and excellent photostability. This work provides a promising method for precise diagnosis of cancer cells by antibody-functionalized fluorescent NPs with high brightness. PMID:27468980

  12. Bright and black blood imaging of the carotid bifurcation at 3.0 T

    International Nuclear Information System (INIS)

    Purpose: The aim of this study was to evaluate our preliminary experience at 3.0 T with imaging of the carotid bifurcation in healthy and atherosclerotic subjects. Application at 3.0 T is motivated by the signal-to-noise gain for improving spatial resolution and reducing signal averaging requirements. Materials and methods: We utilized a dual phased array coil and applied 2D, 3D time of flight (TOF) and turbo spin echo (TSE) sequences with comparison of two lumen signal suppression methods for black blood (BB) TSE imaging including double inversion preparation (DIR) and spatial presaturation pulses. The signal-to-noise ratios (SNR) of healthy carotid vessel walls were compared in 2D and 3D BB TSE acquisitions. The bright and black blood multi-contrast exam was demonstrated for a complex carotid plaque. Results: Contrast-to-noise (CNR) greater than 150 was achieved between the lumen and suppressed background for 3D TOF. For BB, both methods provided sufficient lumen signal suppression but slight residual flow artifacts remained at the bifurcation level. As expected 3D TSE images had higher SNR compared to 2D, but increased motion sensitivity is a significant issue for 3D at high field. For multi-contrast imaging of atherosclerotic plaque, fibrous, calcified and lipid components were resolved. The CNR ratio of fibrous (bright on PDW, T2W) and calcified (dark in T1W, T2W, PDW) plaque components was maximal in the T2W images. The 3D TOF angiogram indicating a 40% stenosis was complemented by 3D multi-planar reformat of BB images that displayed plaque extent. Detection of intimal thickening, the earliest change associated with atherosclerotic progression was observed in BB PDW images at 3.0 T. Conclusions: High SNR and CNR images have been demonstrated for the healthy and diseased carotid. Improvements in RF coils along with pulse sequence optimization, and evaluation of endogenous and exogenous contrast mechanisms will further enhance carotid imaging at 3.0 T

  13. Image Retrieval Based on Content Using Color Feature

    OpenAIRE

    Afifi, Ahmed J.; Wesam M. Ashour

    2012-01-01

    Content-based image retrieval from large resources has become an area of wide interest in many applications. In this paper we present a CBIR system that uses Ranklet Transform and the color feature as a visual feature to represent the images. Ranklet Transform is proposed as a preprocessing step to make the image invariant to rotation and any image enhancement operations. To speed up the retrieval time, images are clustered according to their features using k-means clustering algorithm.

  14. 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

  15. Digital Dental X-Ray Image Segmentation and Feature Extraction

    OpenAIRE

    Abdolvahab Ehsani Rad; Mohd. Shafry Mohd. Rahim; Alireza Norouzi

    2013-01-01

    The process of analysis of such images is important in order to improve quantify medical imaging systems. It is significant to analysis the dental x-ray images we need features of image. In this paper we present a method for segmentation and feature extraction of dental x-ray images. The proposed method has been implemented by using level-set method for segmentation after image enhancement and illustrate contour for teeth to complete the segmentation step. Furthermore, we extracted multiple f...

  16. Accurate Image Retrieval Algorithm Based on Color and Texture Feature

    Directory of Open Access Journals (Sweden)

    Chunlai Yan

    2013-06-01

    Full Text Available Content-Based Image Retrieval (CBIR is one of the most active hot spots in the current research field of multimedia retrieval. According to the description and extraction of visual content (feature of the image, CBIR aims to find images that contain specified content (feature in the image database. In this paper, several key technologies of CBIR, e. g. the extraction of the color and texture features of the image, as well as the similarity measures are investigated. On the basis of the theoretical research, an image retrieval system based on color and texture features is designed. In this system, the Weighted Color Feature based on HSV space is adopted as a color feature vector, four features of the Co-occurrence Matrix, saying Energy, Entropy, Inertia Quadrature and Correlation, are used to construct texture vectors, and the Euclidean distance for similarity measure is employed as well. Experimental results show that this CBIR system is efficient in image retrieval.

  17. Image retrieval using both color and texture features

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    In order to improve the retrieval performance of images, this paper proposes an efficient approach for extracting and retrieving color images. The block diagram of our proposed approach to content-based image retrieval (CBIR) is given firstly, and then we introduce three image feature extracting arithmetic including color histogram, edge histogram and edge direction histogram, the histogram Euclidean distance, cosine distance and histogram intersection are used to measure the image level similarity. On the basis of using color and texture features separately, a new method for image retrieval using combined features is proposed. With the test for an image database including 766 general-purpose images and comparison and analysis of performance evaluation for features and similarity measures, our proposed retrieval approach demonstrates a promising performance. Experiment shows that combined features are superior to every single one of the three features in retrieval.

  18. Retrieval of Ocean Surface Windspeed and Rainrate from the Hurricane Imaging Radiometer (HIRAD) Brightness Temperature Observations

    Science.gov (United States)

    Biswas, Sayak K.; Jones, Linwood; Roberts, Jason; Ruf, Christopher; Ulhorn, Eric; Miller, Timothy

    2012-01-01

    The Hurricane Imaging Radiometer (HIRAD) is a new airborne synthetic aperture passive microwave radiometer capable of wide swath imaging of the ocean surface wind speed under heavy precipitation e.g. in tropical cyclones. It uses interferometric signal processing to produce upwelling brightness temperature (Tb) images at its four operating frequencies 4, 5, 6 and 6.6 GHz [1,2]. HIRAD participated in NASA s Genesis and Rapid Intensification Processes (GRIP) mission during 2010 as its first science field campaign. It produced Tb images with 70 km swath width and 3 km resolution from a 20 km altitude. From this, ocean surface wind speed and column averaged atmospheric liquid water content can be retrieved across the swath. The column averaged liquid water then could be related to an average rain rate. The retrieval algorithm (and the HIRAD instrument itself) is a direct descendant of the nadir-only Stepped Frequency Microwave Radiometer that is used operationally by the NOAA Hurricane Research Division to monitor tropical cyclones [3,4]. However, due to HIRAD s slant viewing geometry (compared to nadir viewing SFMR) a major modification is required in the algorithm. Results based on the modified algorithm from the GRIP campaign will be presented in the paper.

  19. Content-Based Image Retrieval Using Multiple Features

    OpenAIRE

    Zhang, Chi; Huang, Lei

    2014-01-01

    Algorithms of Content-Based Image Retrieval (CBIR) have been well developed along with the explosion of information. These algorithms are mainly distinguished based on feature used to describe the image content. In this paper, the algorithms that are based on color feature and texture feature for image retrieval will be presented. Color Coherence Vector based image retrieval algorithm is also attempted during the implementation process, but the best result is generated from the algorithms tha...

  20. Color Image Segmentation Based on Statistics of Location and Feature Similarity

    Science.gov (United States)

    Mori, Fumihiko; Yamada, Hiromitsu; Mizuno, Makoto; Sugano, Naotoshi

    The process of “image segmentation and extracting remarkable regions” is an important research subject for the image understanding. However, an algorithm based on the global features is hardly found. The requisite of such an image segmentation algorism is to reduce as much as possible the over segmentation and over unification. We developed an algorithm using the multidimensional convex hull based on the density as the global feature. In the concrete, we propose a new algorithm in which regions are expanded according to the statistics of the region such as the mean value, standard deviation, maximum value and minimum value of pixel location, brightness and color elements and the statistics are updated. We also introduced a new concept of conspicuity degree and applied it to the various 21 images to examine the effectiveness. The remarkable object regions, which were extracted by the presented system, highly coincided with those which were pointed by the sixty four subjects who attended the psychological experiment.

  1. 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

  2. Imaging features of extraaxial musculoskeletal tuberculosis

    International Nuclear Information System (INIS)

    Tuberculosis (TB) continues to be a public health problem in both developing and industrialized countries. TB can involve pulmonary as well as extrapulmonary sites. The musculoskeletal system is involved in 1–3% of patients with tuberculosis. Although musculoskeletal TB has become uncommon in the Western world, it remains a huge problem in Asia, Africa, and many developing countries. Tuberculous spondylitis is the most common form of musculoskeletal TB and accounts for approximately 50% of cases. Extraspinal musculoskeletal TB shows a predilection for large joints (hip and knee) and para-articular areas; isolated soft tissue TB is extremely rare. Early diagnosis and prompt treatment are mandatory to prevent serious destruction of joints and skeletal deformity. However, due to the nonspecific and often indolent clinical presentation, the diagnosis may be delayed. Radiological assessment is often the first step in the diagnostic workup of patients with musculoskeletal TB and further investigations are decided by the findings on radiography. Both the radiologist and the clinician should be aware of the possibility of this diagnosis. In this manuscript we review the imaging features of extraspinal bone, joint, and soft tissue TB

  3. Image feature extraction based multiple ant colonies cooperation

    Science.gov (United States)

    Zhang, Zhilong; Yang, Weiping; Li, Jicheng

    2015-05-01

    This paper presents a novel image feature extraction algorithm based on multiple ant colonies cooperation. Firstly, a low resolution version of the input image is created using Gaussian pyramid algorithm, and two ant colonies are spread on the source image and low resolution image respectively. The ant colony on the low resolution image uses phase congruency as its inspiration information, while the ant colony on the source image uses gradient magnitude as its inspiration information. These two ant colonies cooperate to extract salient image features through sharing a same pheromone matrix. After the optimization process, image features are detected based on thresholding the pheromone matrix. Since gradient magnitude and phase congruency of the input image are used as inspiration information of the ant colonies, our algorithm shows higher intelligence and is capable of acquiring more complete and meaningful image features than other simpler edge detectors.

  4. 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. .

  5. Registration of Standardized Histological Images in Feature Space

    OpenAIRE

    Bagci, Ulas; Bai, Li

    2009-01-01

    In this paper, we propose three novel and important methods for the registration of histological images for 3D reconstruction. First, possible intensity variations and nonstandardness in images are corrected by an intensity standardization process which maps the image scale into a standard scale where the similar intensities correspond to similar tissues meaning. Second, 2D histological images are mapped into a feature space where continuous variables are used as high confidence image feature...

  6. THE IDENTIFICATION OF PILL USING FEATURE EXTRACTION IN IMAGE MINING

    OpenAIRE

    Hema, A.; E. Anna Saro

    2015-01-01

    With the help of image mining techniques, an automatic pill identification system was investigated in this study for matching the images of the pills based on its several features like imprint, color, size and shape. Image mining is an inter-disciplinary task requiring expertise from various fields such as computer vision, image retrieval, image matching and pattern recognition. Image mining is the method in which the unusual patterns are detected so that both hidden and useful data images ca...

  7. Inter- and Intra-Observer Variability in Prostate Definition With Tissue Harmonic and Brightness Mode Imaging

    International Nuclear Information System (INIS)

    Purpose: The objective of this study was to compare the relative utility of tissue harmonic (H) and brightness (B) transrectal ultrasound (TRUS) images of the prostate by studying interobserver and intraobserver variation in prostate delineation. Methods and Materials: Ten patients with early-stage disease were randomly selected. TRUS images of prostates were acquired using B and H modes. The prostates on all images were contoured by an experienced radiation oncologist (RO) and five equally trained observers. The observers were blinded to information regarding patient and imaging mode. The volumes of prostate glands and areas of midgland slices were calculated. Volumes contoured were compared among the observers and between observer group and RO. Contours on one patient were repeated five times by four observers to evaluate the intraobserver variability. Results: A one-sample Student t-test showed the volumes outlined by five observers are in agreement (p > 0.05) with the RO. Paired Student t-test showed prostate volumes (p = 0.008) and midgland areas (p = 0.006) with H mode were significantly smaller than that with B mode. Two-factor analysis of variances showed significant interobserver variability (p < 0.001) in prostate volumes and areas. Inter- and intraobserver consistency was quantified as the standard deviation of mean volumes and areas, and concordance indices. It was found that for small glands (≤35 cc) H mode provided greater interobserver consistency; however, for large glands (≥35 cc), B mode provided more consistent estimates. Conclusions: H mode provided superior inter- and intraobserver agreement in prostate volume definition for small to medium prostates. In large glands, H mode does not exhibit any additional advantage. Although harmonic imaging has not proven advantageous for all cases, its utilization seems to be judicious for small prostates.

  8. 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

  9. A NOVEL REGION FEATURE USED IN MULTISENSOR IMAGE FUSION

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A new region feature which emphasized the salience of target region and its neighbors is proposed.In region segmentation-based multisensor image fusion scheme, the presented feature can be extracted from each segmented region to determine the fusion weight. Experimental results demonstrate that the proposed feature has extensive application scope and it provides much more information for each region. It can not only be used in image fusion but also be used in other image processing applications.

  10. Gender Classification Based on Geometry Features of Palm Image

    OpenAIRE

    Ming Wu; Yubo Yuan

    2014-01-01

    This paper presents a novel gender classification method based on geometry features of palm image which is simple, fast, and easy to handle. This gender classification method based on geometry features comprises two main attributes. The first one is feature extraction by image processing. The other one is classification system with polynomial smooth support vector machine (PSSVM). A total of 180 palm images were collected from 30 persons to verify the validity of the proposed gender classi...

  11. New synthesizing feature parameter of wear particles image

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    This paper outlines the application of wavelet analysis method to computering wear par-ticles image processing and introduces the concept of grain parameter for wear particle imagebased on statistical feature parameters. The feature of wear particles image can be obtained fromthe wavelet decomposition and the statistics analysis. Test results showed that grain parametercan be used as a synthesizing feature parameter for wear particle image.

  12. Assessing image features for vision-based robot positioning

    OpenAIRE

    Wells, Gordon; Torras, Carme

    2001-01-01

    The development of any robotics application relying on visual information always raises the key question of what image features would be most informative about the motion to be performed. In this paper, we address this question in the context of visual robot positioning, where a neural network is used to learn the mapping between image features and robot movements, and global image descriptors are preferred to local geometric features. Using a statistical measure of variable interdependence c...

  13. Feature fusion method for edge detection of color images

    Institute of Scientific and Technical Information of China (English)

    Ma Yu; Gu Xiaodong; Wang Yuanyuan

    2009-01-01

    A novel feature fusion method is proposed for the edge detection of color images. Except for the typical features used in edge detection, the color contrast similarity and the orientation consistency are also selected as the features. The four features are combined together as a parameter to detect the edges of color images. Experimental results show that the method can inhibit noisy edges and facilitate the detection for weak edges. It has a better performance than conventional methods in noisy environments.

  14. Retinal image analysis: preprocessing and feature extraction

    International Nuclear Information System (INIS)

    Image processing, analysis and computer vision techniques are found today in all fields of medical science. These techniques are especially relevant to modern ophthalmology, a field heavily dependent on visual data. Retinal images are widely used for diagnostic purposes by ophthalmologists. However, these images often need visual enhancement prior to apply a digital analysis for pathological risk or damage detection. In this work we propose the use of an image enhancement technique for the compensation of non-uniform contrast and luminosity distribution in retinal images. We also explore optic nerve head segmentation by means of color mathematical morphology and the use of active contours.

  15. 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 images...... utilizes depth information only to extract local features, without considering it to improve robustness and discriminability of the feature representation by merging depth cues into feature pooling. Spatial pyramid model (SPM) has become the standard protocol to split a 2D image plane into sub-regions for...... feature pooling of RGB-D images. We argue that SPM may not be the optimal pooling scheme for RGB-D images, as it only pools features spatially and completely discards their depth topological structures. Instead, we propose a novel joint spatial-depth pooling (JSDP) scheme which further partitions SPM...

  16. Indexing of CNN Features for Large Scale Image Search

    OpenAIRE

    Liu, Ruoyu; Zhao, Yao; Wei, Shikui; Zhu, Zhenfeng; Liao, Lixin; Qiu, Shuang

    2015-01-01

    Convolutional neural network (CNN) feature that represents an image with a global and high-dimensional vector has shown highly discriminative capability in image search. Although CNN features are more compact than most of local representation schemes, it still cannot efficiently deal with large-scale image search issues due to its non-negligible computational cost and storage usage. In this paper, we propose a simple but effective image indexing framework to improve the computational and stor...

  17. Measure of image clarity using image features extracted by the multiscale top-hat transform

    International Nuclear Information System (INIS)

    To correctly quantify the clarity of an image and achieve good discrimination, an effective measure of image clarity using the image features extracted by the multiscale top-hat transform is presented in this paper. Firstly, multiscale image features are extracted by the top-hat transform using multiscale structuring elements. Then, the final extracted image features for constructing the measure of image clarity are obtained from the extracted multiscale image features. Finally, the mean value of the final extracted image features is calculated as the proposed measure of image clarity. Comparison experiments and application to image clarity enhancement of mineral images show that the proposed measure is effective for measuring image clarity and has good discrimination ability compared with some other measures. Therefore, the proposed image clarity measure may be used for different applications such as automatic focusing in microscopy, image enhancement, image fusion and so on. (paper)

  18. Introduction: feature issue on In Vivo Microcirculation Imaging

    OpenAIRE

    Dunn, Andrew K.; Leitgeb, Rainer; Wang, Ruikang K.; Zhang, Hao F.

    2011-01-01

    The editors introduce the Biomedical Optics Express feature issue, “In Vivo Microcirculation Imaging,” which includes 14 contributions from the biomedical optics community, covering such imaging techniques as optical coherence tomography, photoacoustic microscopy, laser Doppler /speckle imaging, and near infrared spectroscopy and fluorescence imaging.

  19. Remote Sensing Image Feature Extracting Based Multiple Ant Colonies Cooperation

    Directory of Open Access Journals (Sweden)

    Zhang Zhi-long

    2014-02-01

    Full Text Available This paper presents a novel feature extraction method for remote sensing imagery based on the cooperation of multiple ant colonies. First, multiresolution expression of the input remote sensing imagery is created, and two different ant colonies are spread on different resolution images. The ant colony in the low-resolution image uses phase congruency as the inspiration information, whereas that in the high-resolution image uses gradient magnitude. The two ant colonies cooperate to detect features in the image by sharing the same pheromone matrix. Finally, the image features are extracted on the basis of the pheromone matrix threshold. Because a substantial amount of information in the input image is used as inspiration information of the ant colonies, the proposed method shows higher intelligence and acquires more complete and meaningful image features than those of other simple edge detectors.

  20. Improving SMOS retrieved salinity: characterization of systematic errors in reconstructed and modelled brightness temperature images

    Science.gov (United States)

    Gourrion, J.; Guimbard, S.; Sabia, R.; Portabella, M.; Gonzalez, V.; Turiel, A.; Ballabrera, J.; Gabarro, C.; Perez, F.; Martinez, J.

    2012-04-01

    The Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument onboard the Soil Moisture and Ocean Salinity (SMOS) mission was launched on November 2nd, 2009 with the aim of providing, over the oceans, synoptic sea surface salinity (SSS) measurements with spatial and temporal coverage adequate for large-scale oceanographic studies. For each single satellite overpass, SSS is retrieved after collecting, at fixed ground locations, a series of brightness temperature from successive scenes corresponding to various geometrical and polarization conditions. SSS is inversed through minimization of the difference between reconstructed and modeled brightness temperatures. To meet the challenging mission requirements, retrieved SSS needs to accomplish an accuracy of 0.1 psu after averaging in a 10- or 30-day period and 2°x2° or 1°x1° spatial boxes, respectively. It is expected that, at such scales, the high radiometric noise can be reduced to a level such that remaining errors and inconsistencies in the retrieved salinity fields can essentially be related to (1) systematic brightness temperature errors in the antenna reference frame, (2) systematic errors in the Geophysical Model Function - GMF, used to model the observations and retrieve salinity - for specific environmental conditions and/or particular auxiliary parameter values and (3) errors in the auxiliary datasets used as input to the GMF. The present communication primarily aims at adressing above point 1 and possibly point 2 for the whole polarimetric information i.e. issued from both co-polar and cross-polar measurements. Several factors may potentially produce systematic errors in the antenna reference frame: the unavoidable fact that all antenna are not perfectly identical, the imperfect characterization of the instrument response e.g. antenna patterns, account for receiver temperatures in the reconstruction, calibration using flat sky scenes, implementation of ripple reduction algorithms at sharp

  1. Digital Dental X-Ray Image Segmentation and Feature Extraction

    Directory of Open Access Journals (Sweden)

    Abdolvahab Ehsani Rad

    2013-06-01

    Full Text Available The process of analysis of such images is important in order to improve quantify medical imaging systems. It is significant to analysis the dental x-ray images we need features of image. In this paper we present a method for segmentation and feature extraction of dental x-ray images. The proposed method has been implemented by using level-set method for segmentation after image enhancement and illustrate contour for teeth to complete the segmentation step. Furthermore, we extracted multiple features of dental x-ray images using texture statistics techniques by gray-level co-occurrence matrix. Extracted data can perform to obtain the teeth measurements for automatic dental systems such human identification or dental diagnosis systems. Preparatory experiments show the significance of the proposed method to extract teeth from an x-ray image.

  2. Hubble Space Telescope Imaging of Globular Cluster Candidates in Low Surface Brightness Dwarf Galaxies

    CERN Document Server

    Sharina, M E; Makarov, D I; Sharina, Margarita E.; Puzia, Thomas H.; Makarov, Dmitry I.

    2005-01-01

    Fifty-seven nearby low surface brightness dwarf galaxies were searched for globular cluster candidates (GCCs) using Hubble Space Telescope WFPC2 imaging in V and I. The sample consists of 18 dwarf spheroidal (dSph), 36 irregular (dIrr), and 3 "transition" type (dIrr/dSph) galaxies with angular sizes less than 3.7 kpc situated at distances 2-6 Mpc in the field and in the nearby groups: M81, Centaurus A, Sculptor, Canes Venatici I cloud. We find that ~50% of dSph, dIrr/dSph, and dIrr galaxies contain GCCs. The fraction of GCCs located near the center of dwarf spheroidal galaxies is >2 times higher than that for dIrrs. The mean integral color of GCCs in dSphs, V-I = 1.04+/-0.16 mag, coincides with the corresponding value for Galactic globular clusters and is similar to the blue globular cluster sub-populations in massive early-type galaxies. The color distribution for GCCs in dIrrs shows a clear bimodality with peaks near V-I = 0.5 and 1.0 mag. Blue GCCs are presumably young with ages t -6.5 mag in both dSph an...

  3. Powder-phosphor screens combined with interference filters for X-ray imaging with increased brightness

    CERN Document Server

    Koch, A

    1999-01-01

    Powder-phosphor screens are frequently used in X-ray imaging devices. They have an angular light emission characteristic which is close to a cosine distribution (Lambertian) of photometric intensity. If interference filters are combined with these screens, the angular-emission characteristic changes. We have developed interference filters for powder-phosphor screens with increased brightness perpendicular to the screen. This is particularly advantageous for screens viewed by lens-optic or fiber-optic systems. Measurements on powder-phosphor screens (Gd sub 2 O sub 2 S:Tb screens, thickness 50 mu m) with interference filters were carried out at X-ray photon energies of 18 keV. For an optical system with a numerical aperture of 0.25, the transmitted signal power increased by 70%. However, the spatial resolution was worse compared to the same screen without a filter; 31 mu m fwhm was measured without a filter and 43 mu m fwhm with a filter. (author)

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

    International Nuclear Information System (INIS)

    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

  5. Caroli's disease: magnetic resonance imaging features

    International Nuclear Information System (INIS)

    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.)

  6. Identification of Image Operations Based on Steganalytic Features

    OpenAIRE

    Li, Haodong; Luo, Weiqi; Qiu, Xiaoqing; Huang, Jiwu

    2015-01-01

    Image forensics have attracted wide attention during the past decade. Though many forensic methods have been proposed to identify image forgeries, most of them are targeted ones, since their proposed features are highly dependent on the image operation under investigation. The performance of the well-designed features for detecting the targeted operation usually degrades significantly for other operations. On the other hand, a wise attacker can perform anti-forensics to fool the existing fore...

  7. 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...

  8. Segmentation-Based PolSAR Image Classification Using Visual Features: RHLBP and Color Features

    Directory of Open Access Journals (Sweden)

    Jian Cheng

    2015-05-01

    Full Text Available A segmentation-based fully-polarimetric synthetic aperture radar (PolSAR image classification method that incorporates texture features and color features is designed and implemented. This method is based on the framework that conjunctively uses statistical region merging (SRM for segmentation and support vector machine (SVM for classification. In the segmentation step, we propose an improved local binary pattern (LBP operator named the regional homogeneity local binary pattern (RHLBP to guarantee the regional homogeneity in PolSAR images. In the classification step, the color features extracted from false color images are applied to improve the classification accuracy. The RHLBP operator and color features can provide discriminative information to separate those pixels and regions with similar polarimetric features, which are from different classes. Extensive experimental comparison results with conventional methods on L-band PolSAR data demonstrate the effectiveness of our proposed method for PolSAR image classification.

  9. A Hybrid Approach for DICOM Image Feature Extraction, Feature Selection Using Fuzzy Rough set and Genetic Algorithm

    OpenAIRE

    J. Umamaheswari; DR. G. RADHAMANI

    2011-01-01

    The proposed hybrid approach for feature extraction, feature reduction and feature selection of Medical images based on Rough set and Genetic Algorithm (GA). A Gray Level Co-occurrence Matrix (GLCM) and Histogram based texture feature set is derived. The optimal texture features are extracted from normal and infected Digital Imaging and Communications in Medicine (DICOM) images by using GLCM and histogram based features. The inputs of these features are taken for the feature selection process...

  10. Automated Recognition of 3D Features in GPIR Images

    Science.gov (United States)

    Park, Han; Stough, Timothy; Fijany, Amir

    2007-01-01

    A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a

  11. Textural Feature Extraction of Natural Objects for Image Classification

    Directory of Open Access Journals (Sweden)

    Vishal Krishna

    2015-12-01

    Full Text Available The field of digital image processing has been growing in scope in the recent years. A digital image is represented as a two-dimensional array of pixels, where each pixel has the intensity and location information. Analysis of digital images involves extraction of meaningful information from them, based on certain requirements. Digital Image Analysis requires the extraction of features, transforms the data in the high-dimensional space to a space of fewer dimensions. Feature vectors are n-dimensional vectors of numerical features used to represent an object. We have used Haralick features to classify various images using different classification algorithms like Support Vector Machines (SVM, Logistic Classifier, Random Forests Multi Layer Perception and Naïve Bayes Classifier. Then we used cross validation to assess how well a classifier works for a generalized data set, as compared to the classifications obtained during training.

  12. Imaging in osteomyelitis: Special features in childhood

    International Nuclear Information System (INIS)

    The prognosis of acute hematogenous osteomyelitis in children ist mainly influenced by early diagnosis and prompt initiation of antibiotic and surgical therapy. In this age group, two forms of manifestation are differentiated: Osteomyelitis in infants up to 18 months and juvenile osteomyelitis until the closure of the epiphyseal plate. Osteomyelitis in infants is often accompanied by septic arthritis of the adjacent joint. In juvenile osteomyelitis, the disease is mostly confined to the metaphysis. Plain films and ultrasonography represent the basic imaging modalities. Depending on the age of the child, the clinical course of the disease and the availability of the various methods, MRI and multiphase bone scintigraphy can be performed for further imaging. CT is of only limited value and should only be used for special cases concerning chronic osteomyelitis. (orig.)

  13. Supratentorial cystic intracranial lesions: MR imaging features

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Young Joo; Son, Young Bo; Choi, Kyu Ho; Chun, Kyung Ah; Kim, Sung Hoon; Park, Seog Hee; Shinn, Kyung Sub [The Catholic University of Korea College of Medicine, Seoul (Korea, Republic of)

    1997-01-01

    To describe MR findings and differential points of supratentorial cystic intracranial lesions. We retrospectively reviewed and analyzed the MR findings of 59 patients with supratentorial cystic intracranial lesions, and classified them as follows : tumor-associated cyst, infectious cyst, ex-vacuo type cyst, and congentital/developmental cyst. Among 59 patients, 47 tumor-associated cysts were seen in 17, 42 infectious cysts in 13, 17 ex-vacuo type cysts in 10, and 19 congenital/developmental cysts in 19. In 44 of 47 tumor-associate cysts, increased or inhomogeneous internal signal intensity was seen on T1-weighted image, 37 of 47 showed thick uneven walls ; 37 of 47 had enhancing solid components and there was variable perifocal edema and mass effect. Infectious cysts were multiple (11 of 13). In cases of brain abscess, increased internal signal intensity on T1-weighted image, low signal intensity of abscess wall on T2-weighted image, thick even enhancing wall, and marked perifocal edema (4 of 4) were seen in all four cases. Cysts in cysticercosis were variable in appearance depending on the stage, but were smaller than other cystic lesions. Ex vacuo type cysts were of uniform CSF signal intensity in all pulse sequences and there was no identifiable wall or enhancement associated with enlarged adjacent ventricle and encephalomalacia (17 of 17). Congenital/developmental cysts showed a single lesion (19 of 19), a signal intensity similar to CSF in all pulse sequences (15 of 19), no identifiable wall (16 of 19), no enhancement (17 of 19), and no perifocal edema (19 of 19). MR was used to categorize supratentorial cystic intracranial lesions into four groups on the basis of their number, size, internal homogeneity of signal intensity on T1-weighted image, enhancing pattern, perifocal edema and mass effect, thereby improving diagnostic specificity and patient management.

  14. Image Representation Using EPANECHNIKOV Density Feature Points Estimator

    Directory of Open Access Journals (Sweden)

    Tranos Zuva

    2013-02-01

    Full Text Available In image retrieval most of the existing visual content based representation methods are usually application dependent or non robust, making them not suitable for generic applications. These representation methods use visual contents such as colour, texture, shape, size etc. Human image recognition is largely based on shape, thus making it very appealing for image repr esentation algorithms in computer vision. In this paper we propose a generic image representation algorithm using Epanechnikov Density Feature Points Estimator (EDFPE. It is invariant to rotation, scale and translation. The image density feature points within defined rectangular rings around the gravitational centre of the image are obtained in the form of a vector. The EDFPE is applied to the vecto r representation of the image. The Cosine Angle Distance (CAD algorithm is used to measure similarity of the images in the database. Quantitative evaluation of the performance of the system and comparison with other algorithms was done.

  15. Diffuse pancreatic ductal adenocarcinoma: Characteristic imaging features

    International Nuclear Information System (INIS)

    Purpose: To evaluate imaging findings of diffuse pancreatic ductal adenocarcinoma. Materials and methods: We included 14 patients (4 men and 10 women; mean age, 64.5 years) with diffuse pancreatic ductal adenocarcinoma on the basis of retrospective radiological review. Two radiologists retrospectively reviewed 14 CT scans in consensus with respect to the following: tumor site, peripheral capsule-like structure, dilatation of intratumoral pancreatic duct, parenchymal atrophy, and ancillary findings. Eight magnetic resonance (MR) examinations with MR cholangiopancreatography (MRCP) and seven endoscopic retrograde cholangiopancreatography (ERCP) were also reviewed, focusing on peripheral capsule-like structure and dilatation of intratumoral pancreatic duct. Results: CT revealed tumor localization to the body and tail in 11 (79%) patients and peripheral capsule-like structure in 13 (93%). The intratumoral pancreatic duct was not visible in 13 (93%). Pancreatic parenchymal atrophy was not present in all 14 patients. Tumor invasion of vessels was observed in all 14 patients and of neighbor organs in 8 (57%). On contrast-enhanced T1-weighted MR images, peripheral capsule-like structure showed higher signal intensity in five patients (71%). In all 11 patients with MRCP and/or ERCP, the intratumoral pancreatic duct was not dilated. Conclusion: Diffuse pancreatic ductal adenocarcinoma has characteristic imaging findings, including peripheral capsule-like structure, local invasiveness, and absence of both dilatation of intratumoral pancreatic duct and parenchymal atrophy

  16. Simple Low Level Features for Image Analysis

    Science.gov (United States)

    Falcoz, Paolo

    As human beings, we perceive the world around us mainly through our eyes, and give what we see the status of “reality”; as such we historically tried to create ways of recording this reality so we could augment or extend our memory. From early attempts in photography like the image produced in 1826 by the French inventor Nicéphore Niépce (Figure 2.1) to the latest high definition camcorders, the number of recorded pieces of reality increased exponentially, posing the problem of managing all that information. Most of the raw video material produced today has lost its memory augmentation function, as it will hardly ever be viewed by any human; pervasive CCTVs are an example. They generate an enormous amount of data each day, but there is not enough “human processing power” to view them. Therefore the need for effective automatic image analysis tools is great, and a lot effort has been put in it, both from the academia and the industry. In this chapter, a review of some of the most important image analysis tools are presented.

  17. Registration of Standardized Histological Images in Feature Space

    CERN Document Server

    Bagci, Ulas; 10.1117/12.770219

    2009-01-01

    In this paper, we propose three novel and important methods for the registration of histological images for 3D reconstruction. First, possible intensity variations and nonstandardness in images are corrected by an intensity standardization process which maps the image scale into a standard scale where the similar intensities correspond to similar tissues meaning. Second, 2D histological images are mapped into a feature space where continuous variables are used as high confidence image features for accurate registration. Third, we propose an automatic best reference slice selection algorithm that improves reconstruction quality based on both image entropy and mean square error of the registration process. We demonstrate that the choice of reference slice has a significant impact on registration error, standardization, feature space and entropy information. After 2D histological slices are registered through an affine transformation with respect to an automatically chosen reference, the 3D volume is reconstruct...

  18. Neonatal nasopharyngeal teratomas: cross sectional imaging features

    Energy Technology Data Exchange (ETDEWEB)

    Andronikou, S. [Radiology Dept., Royal Children' s Hospital, Parkville, Melbourne (Australia); Dept. of Radiology, Royal Children' s Hospital, Univ. of Cape Town, Rondebosch (South Africa); Kumbla, S.; Fink, A.M. [Radiology Dept., Royal Children' s Hospital, Parkville, Melbourne (Australia)

    2003-04-01

    Background: Neonatal nasopharyngeal teratomas are extremely rare and there are few reports describing both CT and MRI features of these lesions. Objective: To describe the CT and MRI appearances of neonatal nasopharyngeal teratoma. Materials and methods: Three neonates with nasopharyngeal teratomas and severe respiratory distress were reviewed. Results: The nasopharyngeal mass resulted in severe respiratory compromise requiring urgent intervention. Characteristic mandibular and pterygoid plate abnormalities demonstrated by CT and MRI are described. Conclusions: Prenatal MRI enables the diagnosis, delineates tumour extent and allows planned delivery. CT and MRI play a key role in differentiating neonatal nasopharyngeal teratomas from other causes of a neonatal neck mass, thus optimising management. (orig.)

  19. Untangling the contributions of image charge and laser profile for optimal photoemission of high-brightness electron beams

    Science.gov (United States)

    Portman, J.; Zhang, H.; Makino, K.; Ruan, C. Y.; Berz, M.; Duxbury, P. M.

    2014-11-01

    Using our model for the simulation of photoemission of high brightness electron beams, we investigate the virtual cathode physics and the limits to spatio-temporal and spectroscopic resolution originating from the image charge on the surface and from the profile of the exciting laser pulse. By contrasting the effect of varying surface properties (leading to expanding or pinned image charge), laser profiles (Gaussian, uniform, and elliptical), and aspect ratios (pancake- and cigar-like) under different extraction field strengths and numbers of generated electrons, we quantify the effect of these experimental parameters on macroscopic pulse properties such as emittance, brightness (4D and 6D), coherence length, and energy spread. Based on our results, we outline optimal conditions of pulse generation for ultrafast electron microscope systems that take into account constraints on the number of generated electrons and on the required time resolution.

  20. Performance Analysis of Texture Image Classification Using Wavelet Feature

    Directory of Open Access Journals (Sweden)

    Dolly Choudhary

    2013-01-01

    Full Text Available This paper compares the performance of various classifiers for multi class image classification. Where the features are extracted by the proposed algorithm in using Haar wavelet coefficient. The wavelet features are extracted from original texture images and corresponding complementary images. As it is really very difficult to decide which classifier would show better performance for multi class image classification. Hence, this work is an analytical study of performance of various classifiers for the single multiclass classification problem. In this work fifteen textures are taken for classification using Feed Forward Neural Network, Naïve Bays Classifier, K-nearest neighbor Classifier and Cascaded Neural Network.

  1. Featured Image: A Bubble Triggering Star Formation

    Science.gov (United States)

    Kohler, Susanna

    2016-05-01

    This remarkable false-color, mid-infrared image (click for the full view!) was produced by the Wide-field Infrared Survey Explorer (WISE). It captures a tantalizing view of Sh 2-207 and Sh 2-208, the latter of which is one of the lowest-metallicity star-forming regions in the Galaxy. In a recent study led by Chikako Yasui (University of Tokyo and the Koyama Astronomical Observatory), a team of scientists has examined this region to better understand how star formation in low-metallicity environments differs from that in the solar neighborhood. The authors analysis suggests that sequential star formation is taking place in these low-metallicity regions, triggered by an expanding bubble (the large dashed oval indicated in the image) with a ~30 pc radius. You can find out more about their study by checking out the paper below!CitationChikako Yasui et al 2016 AJ 151 115. doi:10.3847/0004-6256/151/5/115

  2. THE IDENTIFICATION OF PILL USING FEATURE EXTRACTION IN IMAGE MINING

    Directory of Open Access Journals (Sweden)

    A. Hema

    2015-02-01

    Full Text Available With the help of image mining techniques, an automatic pill identification system was investigated in this study for matching the images of the pills based on its several features like imprint, color, size and shape. Image mining is an inter-disciplinary task requiring expertise from various fields such as computer vision, image retrieval, image matching and pattern recognition. Image mining is the method in which the unusual patterns are detected so that both hidden and useful data images can only be stored in large database. It involves two different approaches for image matching. This research presents a drug identification, registration, detection and matching, Text, color and shape extraction of the image with image mining concept to identify the legal and illegal pills with more accuracy. Initially, the preprocessing process is carried out using novel interpolation algorithm. The main aim of this interpolation algorithm is to reduce the artifacts, blurring and jagged edges introduced during up-sampling. Then the registration process is proposed with two modules they are, feature extraction and corner detection. In feature extraction the noisy high frequency edges are discarded and relevant high frequency edges are selected. The corner detection approach detects the high frequency pixels in the intersection points. Through the overall performance gets improved. There is a need of segregate the dataset into groups based on the query image’s size, shape, color, text, etc. That process of segregating required information is called as feature extraction. The feature extraction is done using Geometrical Gradient feature transformation. Finally, color and shape feature extraction were performed using color histogram and geometrical gradient vector. Simulation results shows that the proposed techniques provide accurate retrieval results both in terms of time and accuracy when compared to conventional approaches.

  3. Texture features from Chaos Game Representation Images of Genomes

    Directory of Open Access Journals (Sweden)

    Vrinda V. Nair

    2013-04-01

    Full Text Available The proposed work investigates the effectiveness of coarse measures of the Chaos Game Representation (CGR images in differentiating genomes of various organisms. Major work in this area is seen to focus on feature extraction using Frequency Chaos Game Representation (FCGR matrices. Although it is biologically significant, FCGR matrix has an inherent error which is associated with the insufficient computing as well as the screen resolutions. Hence the CGR image is converted to a texture image and corresponding feature vectors extracted. Features such as the texture properties and the subsequent wavelet coefficients of the texture image are used. Our work suggests that texture features characterize genomes well further; their wavelet coefficients yield better distinguishing capabilities.

  4. Featured Image: Star Clusters in M51

    Science.gov (United States)

    Kohler, Susanna

    2016-06-01

    This beautiful mosaic of images of the Whirlpool galaxy (M51) and its companion was taken with the Advanced Camera for Surveys on the Hubble Space Telescope. This nearby, grand-design spiral galaxy has a rich population of star clusters, making it both a stunning target for imagery and an excellent resource for learning about stellar formation and evolution. In a recent study, Rupali Chandar (University of Toledo) and collaborators cataloged over 3,800 compact star clusters within this galaxy. They then used this catalog to determine the distributions for the clusters ages, masses, and sizes, which can provide important clues as to how star clusters form, evolve, and are eventually disrupted. You can read more about their study and what they discovered in the paper below.CitationRupali Chandar et al 2016 ApJ 824 71. doi:10.3847/0004-637X/824/2/71

  5. 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.

  6. An adaptive multi-feature segmentation model for infrared image

    Science.gov (United States)

    Zhang, Tingting; Han, Jin; Zhang, Yi; Bai, Lianfa

    2016-04-01

    Active contour models (ACM) have been extensively applied to image segmentation, conventional region-based active contour models only utilize global or local single feature information to minimize the energy functional to drive the contour evolution. Considering the limitations of original ACMs, an adaptive multi-feature segmentation model is proposed to handle infrared images with blurred boundaries and low contrast. In the proposed model, several essential local statistic features are introduced to construct a multi-feature signed pressure function (MFSPF). In addition, we draw upon the adaptive weight coefficient to modify the level set formulation, which is formed by integrating MFSPF with local statistic features and signed pressure function with global information. Experimental results demonstrate that the proposed method can make up for the inadequacy of the original method and get desirable results in segmenting infrared images.

  7. Assist features: placement, impact, and relevance for EUV imaging

    Science.gov (United States)

    Mochi, Iacopo; Philipsen, Vicky; Gallagher, Emily; Hendrickx, Eric; Lyakhova, Kateryna; Wittebrood, Friso; Schiffelers, Guido; Fliervoet, Timon; Wang, Shibing; Hsu, Stephen; Plachecki, Vince; Baron, Stan; Laenens, Bart

    2016-03-01

    Assist features are commonly used in DUV lithography to improve the lithographic process window of isolated features under illumination conditions that enable the printability of dense features. With the introduction of EUV lithography, the interaction between 13.5 nm light and the mask features generates strong mask 3D effects. On wafer, the mask 3D effects manifest as pitch-dependent best focus positions, pattern asymmetries and image contrast loss. To minimize the mask 3D effects, and enhance the lithographic process window, we explore by means of wafer print evaluation the use of assist features with different sizes and placements. The assist features are placed next to isolated features and two bar structures, consistent with theN5 (imec iN7) node dimensions for 0.33NA and we use different types of off-axis illumination . For the generic iN7 structures, wafer imaging will be compared to simulation results and an assessment of optimal assist feature configuration will be made. It is also essential to understand the potential benefit of using assist features and to weigh that benefit against the price of complexity associated with adding sub-resolution features on a production mask. To that end, we include an OPC study that compares a layout treated with assist features, to one without assist features, using full-chip complexity metrics like data size.

  8. Image mosaic method based on SIFT features of line segment.

    Science.gov (United States)

    Zhu, Jun; Ren, Mingwu

    2014-01-01

    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. PMID:24511326

  9. 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.

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

    International Nuclear Information System (INIS)

    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

  11. 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).

  12. Imaging features of communicating bronchopulmonary foregut malformation

    International Nuclear Information System (INIS)

    Objective: To summarize the upper gastrointestinal (UGI) series and CT features of communicating bronchopulmonary foregut malformation (CBPFM) and to improve the ability for the diagnosis. Methods: Three cases of CBPFM proved by surgery and pathology were reviewed retrospectively. All the cases performed the UGI series, plain and contrast enhanced CT scan. Results: The UGI series showed abnormal fistulous tracts arising from the esophagus and extending into the mass in the lung in 2 cases, arising from the gastric fundus and extending into the right hemithorax in 1 case. CT demonstrated solid masses in the para-spinal region of the lower lobe in all cases, among them, 1 case showed agenesis of the right lung. Contrast enhanced CT scan showed pulmonary arterial blood supply in 2 cases, systemic blood supply originate from the celiac trunk in 1 case, pulmonary vein drainage in all cases. Reconstruction showed aberrant tracts arise from the esophagus in 2 case, from the gastric fundus in 1 case. Conclusion: CBPFM have various appearance. UGI series can demonstrate the abnormal tract directly, CT can evaluate the lung, the abnormal artery and vein, the communication with the gastrointestinal tract and the associated malformation, so it is the optimal method for the diagnosis of CBPFM. (authors)

  13. Featured Image: Mapping Jupiter with Hubble

    Science.gov (United States)

    Kohler, Susanna

    2016-07-01

    Zonal wind profile for Jupiter, describing the speed and direction of its winds at each latitude. [Simon et al. 2015]This global map of Jupiters surface (click for the full view!) was generated by the Hubble Outer Planet Atmospheres Legacy (OPAL) program, which aims to createnew yearly global maps for each of the outer planets. Presented in a study led by Amy Simon (NASA Goddard Space Flight Center), the map above is the first generated for Jupiter in the first year of the OPAL campaign. It provides a detailed look at Jupiters atmospheric structure including the Great Red Spot and allowed the authors to measure the speed and direction of the wind across Jupiters latitudes, constructing an updated zonal wind profile for Jupiter.In contrast to this study, the Juno mission (which will be captured into Jupiters orbit today after a 5-year journey to Jupiter!) will be focusing more on the features below Jupiters surface, studying its deep atmosphere and winds. Some of Junos primary goals are to learn about Jupiters composition, gravitational field, magnetic field, and polar magnetosphere. You can follow along with the NASATV livestream as Juno arrives at Jupiter tonight; orbit insertion coverage starts at 10:30 EDT.CitationAmy A. Simon et al 2015 ApJ 812 55. doi:10.1088/0004-637X/812/1/55

  14. Image Retrieval Using a Combination of Keywords and Image Features

    OpenAIRE

    Reddy, Vishwanath Reddy Keshi; Bandikolla, Praveen

    2008-01-01

    Information retrieval systems are playing an important role in our day to day life for getting the required information. Many text retrieval systems are available and are working successfully. Even though internet is full of other media like images, audio and video, retrieval systems for these media are rare and have not achieved success as that of text retrieval systems. Image retrieval systems are useful in many applications; there is a high demand for effective and efficient tool for image...

  15. Morphological Feature Extraction for Automatic Registration of Multispectral Images

    Science.gov (United States)

    Plaza, Antonio; LeMoigne, Jacqueline; Netanyahu, Nathan S.

    2007-01-01

    The task of image registration can be divided into two major components, i.e., the extraction of control points or features from images, and the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual extraction of control features can be subjective and extremely time consuming, and often results in few usable points. On the other hand, automated feature extraction allows using invariant target features such as edges, corners, and line intersections as relevant landmarks for registration purposes. In this paper, we present an extension of a recently developed morphological approach for automatic extraction of landmark chips and corresponding windows in a fully unsupervised manner for the registration of multispectral images. Once a set of chip-window pairs is obtained, a (hierarchical) robust feature matching procedure, based on a multiresolution overcomplete wavelet decomposition scheme, is used for registration purposes. The proposed method is validated on a pair of remotely sensed scenes acquired by the Advanced Land Imager (ALI) multispectral instrument and the Hyperion hyperspectral instrument aboard NASA's Earth Observing-1 satellite.

  16. The analysis of image feature robustness using cometcloud

    Science.gov (United States)

    Qi, Xin; Kim, Hyunjoo; Xing, Fuyong; Parashar, Manish; Foran, David J.; Yang, Lin

    2012-01-01

    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. PMID:23248759

  17. Retinal image registration via feature-guided Gaussian mixture model.

    Science.gov (United States)

    Liu, Chengyin; Ma, Jiayi; Ma, Yong; Huang, Jun

    2016-07-01

    Registration of retinal images taken at different times, from different perspectives, or with different modalities is a critical prerequisite for the diagnoses and treatments of various eye diseases. This problem can be formulated as registration of two sets of sparse feature points extracted from the given images, and it is typically solved by first creating a set of putative correspondences and then removing the false matches as well as estimating the spatial transformation between the image pairs or solved by estimating the correspondence and transformation jointly involving an iteration process. However, the former strategy suffers from missing true correspondences, and the latter strategy does not make full use of local appearance information, which may be problematic for low-quality retinal images due to a lack of reliable features. In this paper, we propose a feature-guided Gaussian mixture model (GMM) to address these issues. We formulate point registration as the estimation of a feature-guided mixture of densities: A GMM is fitted to one point set, such that both the centers and local features of the Gaussian densities are constrained to coincide with the other point set. The problem is solved under a unified maximum-likelihood framework together with an iterative expectation-maximization algorithm initialized by the confident feature correspondences, where the image transformation is modeled by an affine function. Extensive experiments on various retinal images show the robustness of our approach, which consistently outperforms other state-of-the-art methods, especially when the data is badly degraded. PMID:27409682

  18. Fingerprint image segmentation based on multi-features histogram analysis

    Science.gov (United States)

    Wang, Peng; Zhang, Youguang

    2007-11-01

    An effective fingerprint image segmentation based on multi-features histogram analysis is presented. We extract a new feature, together with three other features to segment fingerprints. Two of these four features, each of which is related to one of the other two, are reciprocals with each other, so features are divided into two groups. These two features' histograms are calculated respectively to determine which feature group is introduced to segment the aim-fingerprint. The features could also divide fingerprints into two classes with high and low quality. Experimental results show that our algorithm could classify foreground and background effectively with lower computational cost, and it can also reduce pseudo-minutiae detected and improve the performance of AFIS.

  19. Learning Hierarchical Spectral-Spatial Features for Hyperspectral Image Classification.

    Science.gov (United States)

    Zhou, Yicong; Wei, Yantao

    2016-07-01

    This paper proposes a spectral-spatial feature learning (SSFL) method to obtain robust features of hyperspectral images (HSIs). It combines the spectral feature learning and spatial feature learning in a hierarchical fashion. Stacking a set of SSFL units, a deep hierarchical model called the spectral-spatial networks (SSN) is further proposed for HSI classification. SSN can exploit both discriminative spectral and spatial information simultaneously. Specifically, SSN learns useful high-level features by alternating between spectral and spatial feature learning operations. Then, kernel-based extreme learning machine (KELM), a shallow neural network, is embedded in SSN to classify image pixels. Extensive experiments are performed on two benchmark HSI datasets to verify the effectiveness of SSN. Compared with state-of-the-art methods, SSN with a deep hierarchical architecture obtains higher classification accuracy in terms of the overall accuracy, average accuracy, and kappa ( κ ) coefficient of agreement, especially when the number of the training samples is small. PMID:26241988

  20. Featured Image: Fireball After a Temporary Capture?

    Science.gov (United States)

    Kohler, Susanna

    2016-06-01

    This image of a fireball was captured in the Czech Republic by cameras at a digital autonomous observatory in the village of Kunak. This observatory is part of a network of stations known as the European Fireball Network, and this particular meteoroid detection, labeled EN130114, is notable because it has the lowest initial velocity of any natural object ever observed by the network. Led by David Clark (University of Western Ontario), the authors of a recent study speculate that before this meteoroid impacted Earth, it may have been a Temporarily Captured Orbiter (TCO). TCOs are near-Earth objects that make a few orbits of Earth before returning to heliocentric orbits. Only one has ever been observed to date, and though they are thought to make up 0.1% of all meteoroids, EN130114 is the first event ever detected that exhibits conclusive behavior of a TCO. For more information on EN130114 and why TCOs are important to study, check out the paper below!CitationDavid L. Clark et al 2016 AJ 151 135. doi:10.3847/0004-6256/151/6/135

  1. Featured Image: A Gap in TW Hydrae

    Science.gov (United States)

    Kohler, Susanna

    2016-04-01

    This remarkable image (click for the full view!) is a high-resolution map of the 870 m light emitted by the protoplanetary disk surrounding the young solar analog TW Hydrae. A recent study led by Sean Andrews (Harvard-Smithsonian Center for Astrophysics) presents these observations, obtained with the long-baseline configuration of the Atacama Large Millimeter/submillimeter Array (ALMA) at an unprecedented spatial resolution of ~1 AU. The data represent the distribution of millimeter-sized dust grains in this disk, revealing a beautiful concentric ring structure out to a radial distance of 60 AU from the host star. The apparent gaps in the disk could have anyof three origins:Chemical: apparent gaps can becaused by condensation fronts of volatilesMagnetic: apparent gaps can becaused by radial magnetic pressure variationsDynamic: actual gaps can becaused by the clearing of dust by young planets.For more information, check out the paper below!CitationSean M. Andrews et al 2016 ApJ 820 L40. doi:10.3847/2041-8205/820/2/L40

  2. Introduction: Feature Issue on Optical Imaging and Spectroscopy

    OpenAIRE

    Hielscher, Andreas H.; Mycek, Mary-Ann; Perelman, Lev T.

    2010-01-01

    The editors introduce the Biomedical Optics Express feature issue, “Optical Imaging and Spectroscopy,” which was a technical area at the 2010 Optical Society of America (OSA), Biomedical Optics (BIOMED) Topical Meeting held on 11–14 April in Miami, Florida. The feature issue includes 23 contributions from conference attendees.

  3. Feature-Area Optimization: A Novel SAR Image Registration Method

    OpenAIRE

    Liu, Fuqiang; Bi, Fukun; Chen, Liang; Shi, Hao; Liu, Wei

    2016-01-01

    This letter proposes a synthetic aperture radar (SAR) image registration method named Feature-Area Optimization (FAO). First, the traditional area-based optimization model is reconstructed and decomposed into three key but uncertain factors: initialization, slice set and regularization. Next, structural features are extracted by scale invariant feature transform (SIFT) in dual-resolution space (SIFT-DRS), a novel SIFT-Like method dedicated to FAO. Then, the three key factors are determined ba...

  4. Smart Images Search based on Visual Features Fusion

    International Nuclear Information System (INIS)

    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 ycbcr 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 is

  5. 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.)

  6. Disorders of the pediatric pancreas: imaging features

    International Nuclear Information System (INIS)

    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.)

  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

    2016-01-01

    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. PMID:26840313

  9. Multiresolution image fusion scheme based on fuzzy region feature

    Institute of Scientific and Technical Information of China (English)

    LIU Gang; JING Zhong-liang; SUN Shao-yuan

    2006-01-01

    This paper proposes a novel region based image fusion scheme based on multiresolution analysis. The low frequency band of the image multiresolution representation is segmented into important regions, sub-important regions and background regions. Each feature of the regions is used to determine the region's degree of membership in the multiresolution representation,and then to achieve multiresolution representation of the fusion result. The final image fusion result can be obtained by using the inverse multiresolution transform. Experiments showed that the proposed image fusion method can have better performance than existing image fusion methods.

  10. Automated feature extraction and classification from image sources

    Science.gov (United States)

    U.S. Geological Survey

    1995-01-01

    The U.S. Department of the Interior, U.S. Geological Survey (USGS), and Unisys Corporation have completed a cooperative research and development agreement (CRADA) to explore automated feature extraction and classification from image sources. The CRADA helped the USGS define the spectral and spatial resolution characteristics of airborne and satellite imaging sensors necessary to meet base cartographic and land use and land cover feature classification requirements and help develop future automated geographic and cartographic data production capabilities. The USGS is seeking a new commercial partner to continue automated feature extraction and classification research and development.

  11. Magnetic resonance imaging of hypothalamus hypophysis axis lesions; Relationship between posterior pituitary function and posterior bright spot

    Energy Technology Data Exchange (ETDEWEB)

    Shiina, Takeki; Uno, Kimiichi; Arimizu, Noboru; Yoshida, Sho (Chiba Univ. (Japan). School of Medicine); Yamada, Kenichi

    1990-04-01

    Magnetic resonance imaging (MRI) using a 0.5T superconductive machine was performed to the thirty three cases with a variety of the sellar and parasellar tumors and with dysfunction of the hypothalamus-hypophysis axis. Posterior pituitary bright spot (PBS) on T1 weighted image was evaluated with the pituitary hormonal function. These cases were 12 cases of post-treated tumors including pituitary adenoma (9 patients), suprasellar germinoma (2 patients) and craniopharyngioma (one patient), and non-tumorous conditions including 15 cases of central diabetes insipidus (DI), Syndrome of inappropriate secretion of ADH (SIADH) (one patient), Sheehan's syndrome (3 patients) and anorexia nervosa (2 patients). Pituitary bright spot was not seen in all 19 cases with overt DI. On the other hand, PBS was not seen in 9 cases without overt DI. Three cases of these 9 cases showing Sheehan's syndrome with insufficient antidiuretic hormone (ADH) secretion was considered as the state of subclinical DI. Posterior bright spot was not seen in all 13 cases of empty sella including partial empty sella. The results suggested that disappearance of PBS represents abnormality or loss of posterior pituitary function and also it was considered to be closely related to the empty sella. (author).

  12. Exploiting Local Features from Deep Networks for Image Retrieval

    OpenAIRE

    Ng, Joe Yue-Hei; Yang, Fan; Larry S. Davis

    2015-01-01

    Deep convolutional neural networks have been successfully applied to image classification tasks. When these same networks have been applied to image retrieval, the assumption has been made that the last layers would give the best performance, as they do in classification. We show that for instance-level image retrieval, lower layers often perform better than the last layers in convolutional neural networks. We present an approach for extracting convolutional features from different layers of ...

  13. Image Representation Using EPANECHNIKOV Density Feature Points Estimator

    Directory of Open Access Journals (Sweden)

    Tranos Zuva

    2013-03-01

    Full Text Available In image retrieval most of the existing visual content based representation methods are usually applicationdependent or non robust, making them not suitable for generic applications. These representation methodsuse visual contents such as colour, texture, shape,size etc. Human image recognition is largely basedonshape, thus making it very appealing for image representation algorithms in computer vision.In this paper we propose a generic image representation algorithm using Epanechnikov Density FeaturePoints Estimator (EDFPE. It is invariant to rotation, scale and translation. The image density featurepoints within defined rectangular rings around thegravitational centre of the image are obtained in theform of a vector. The EDFPE is applied to the vector representation of the image. The Cosine AngleDistance (CAD algorithm is used to measure similarity of the images in the database. Quantitativeevaluation of the performance of the system and comparison with other algorithms was done

  14. Minimal Feature Set for Unsupervised Classification of Knee MR Images

    Directory of Open Access Journals (Sweden)

    Rajneet Kaur

    2011-11-01

    Full Text Available Knee scans is very useful and effective technique to detect the knee joint defects. Unsupervised Classification is useful in the absence of domain expert. Real Knee Magnetic Resonance Images have been collected from the MRI centres. Segmentation is implemented using Active Contour without Edges. DICOM, Haralick and some Statistical features have been extracted out. A database file of 704 images with 46 features per images has been prepared. Unsupervised Classification is implemented with clustering using EM model and then classification using different classifiers. Learning rate of 5 classifiers (ID3, J48, FID3new, Naive Bayes, and Kstar has been calculated. At the obtained learning rate minimal feature set has been obtained for unsupervised classification of Knee MR Images.

  15. An image segmentation based method for iris feature extraction

    Institute of Scientific and Technical Information of China (English)

    XU Guang-zhu; ZHANG Zai-feng; MA Yi-de

    2008-01-01

    In this article, the local anomalistic blocks such ascrypts, furrows, and so on in the iris are initially used directly asiris features. A novel image segmentation method based onintersecting cortical model (ICM) neural network was introducedto segment these anomalistic blocks. First, the normalized irisimage was put into ICM neural network after enhancement.Second, the iris features were segmented out perfectly and wereoutput in binary image type by the ICM neural network. Finally,the fourth output pulse image produced by ICM neural networkwas chosen as the iris code for the convenience of real timeprocessing. To estimate the performance of the presentedmethod, an iris recognition platform was produced and theHamming Distance between two iris codes was computed tomeasure the dissimilarity between them. The experimentalresults in CASIA vl.0 and Bath iris image databases show thatthe proposed iris feature extraction algorithm has promisingpotential in iris recognition.

  16. Automated Image Registration Using Morphological Region of Interest Feature Extraction

    Science.gov (United States)

    Plaza, Antonio; LeMoigne, Jacqueline; Netanyahu, Nathan S.

    2005-01-01

    With the recent explosion in the amount of remotely sensed imagery and the corresponding interest in temporal change detection and modeling, image registration has become increasingly important as a necessary first step in the integration of multi-temporal and multi-sensor data for applications such as the analysis of seasonal and annual global climate changes, as well as land use/cover changes. The task of image registration can be divided into two major components: (1) the extraction of control points or features from images; and (2) the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual control feature extraction can be subjective and extremely time consuming, and often results in few usable points. Automated feature extraction is a solution to this problem, where desired target features are invariant, and represent evenly distributed landmarks such as edges, corners and line intersections. In this paper, we develop a novel automated registration approach based on the following steps. First, a mathematical morphology (MM)-based method is used to obtain a scale-orientation morphological profile at each image pixel. Next, a spectral dissimilarity metric such as the spectral information divergence is applied for automated extraction of landmark chips, followed by an initial approximate matching. This initial condition is then refined using a hierarchical robust feature matching (RFM) procedure. Experimental results reveal that the proposed registration technique offers a robust solution in the presence of seasonal changes and other interfering factors. Keywords-Automated image registration, multi-temporal imagery, mathematical morphology, robust feature matching.

  17. Dynamics of Coronal Bright Points as Seen by Sun Watcher Using Active Pixel System Detector and Image Processing (SWAP), Atmospheric Imaging Assembly (AIA), and Helioseismic and Magnetic Imager (HMI)

    Science.gov (United States)

    Chandrashekhar, K.; Krishna Prasad, S.; Banerjee, D.; Ravindra, B.; Seaton, Daniel B.

    2013-08-01

    The Sun Watcher using Active Pixel system detector and Image Processing (SWAP) onboard the PRoject for OnBoard Autonomy-2 (PROBA2) spacecraft provides images of the solar corona in EUV channel centered at 174 Å. These data, together with the Atmospheric Imaging Assembly (AIA) and the Helioseismic and Magnetic Imager (HMI) onboard Solar Dynamics Observatory (SDO), are used to study the dynamics of coronal bright points. The evolution of the magnetic polarities and associated changes in morphology are studied using magnetograms and multi-wavelength imaging. The morphology of the bright points seen in low-resolution SWAP images and high-resolution AIA images show different structures, whereas the intensity variations with time show similar trends in both SWAP 174 Å and AIA 171 Å channels. We observe that bright points are seen in EUV channels corresponding to a magnetic flux of the order of 1018 Mx. We find that there exists a good correlation between total emission from the bright point in several UV-EUV channels and total unsigned photospheric magnetic flux above certain thresholds. The bright points also show periodic brightenings, and we have attempted to find the oscillation periods in bright points and their connection to magnetic-flux changes. The observed periods are generally long (10 - 25 minutes) and there is an indication that the intensity oscillations may be generated by repeated magnetic reconnection.

  18. De-Striping for Tdiccd Remote Sensing Image Based on Statistical Features of Histogram

    Science.gov (United States)

    Gao, Hui-ting; Liu, Wei; He, Hong-yan; Zhang, Bing-xian; Jiang, Cheng

    2016-06-01

    Aim to striping noise brought by non-uniform response of remote sensing TDI CCD, a novel de-striping method based on statistical features of image histogram is put forward. By analysing the distribution of histograms,the centroid of histogram is selected to be an eigenvalue representing uniformity of ground objects,histogrammic centroid of whole image and each pixels are calculated first,the differences between them are regard as rough correction coefficients, then in order to avoid the sensitivity caused by single parameter and considering the strong continuity and pertinence of ground objects between two adjacent pixels,correlation coefficient of the histograms is introduces to reflect the similarities between them,fine correction coefficient is obtained by searching around the rough correction coefficient,additionally,in view of the influence of bright cloud on histogram,an automatic cloud detection based on multi-feature including grey level,texture,fractal dimension and edge is used to pre-process image.Two 0-level panchromatic images of SJ-9A satellite with obvious strip noise are processed by proposed method to evaluate the performance, results show that the visual quality of images are improved because the strip noise is entirely removed,we quantitatively analyse the result by calculating the non-uniformity ,which has reached about 1% and is better than histogram matching method.

  19. Effective feature selection for image steganalysis using extreme learning machine

    Science.gov (United States)

    Feng, Guorui; Zhang, Haiyan; Zhang, Xinpeng

    2014-11-01

    Image steganography delivers secret data by slight modifications of the cover. To detect these data, steganalysis tries to create some features to embody the discrepancy between the cover and steganographic images. Therefore, the urgent problem is how to design an effective classification architecture for given feature vectors extracted from the images. We propose an approach to automatically select effective features based on the well-known JPEG steganographic methods. This approach, referred to as extreme learning machine revisited feature selection (ELM-RFS), can tune input weights in terms of the importance of input features. This idea is derived from cross-validation learning and one-dimensional (1-D) search. While updating input weights, we seek the energy decreasing direction using the leave-one-out (LOO) selection. Furthermore, we optimize the 1-D energy function instead of directly discarding the least significant feature. Since recent Liu features can gain considerable low detection errors compared to a previous JPEG steganalysis, the experimental results demonstrate that the new approach results in less classification error than other classifiers such as SVM, Kodovsky ensemble classifier, direct ELM-LOO learning, kernel ELM, and conventional ELM in Liu features. Furthermore, ELM-RFS achieves a similar performance with a deep Boltzmann machine using less training time.

  20. Integration of Image-Derived and Pos-Derived Features for Image Blur Detection

    Science.gov (United States)

    Teo, Tee-Ann; Zhan, Kai-Zhi

    2016-06-01

    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.

  1. Direct observations of cracks and voids in structural materials by X-ray imaging using ultra-bright synchrotron radiation

    International Nuclear Information System (INIS)

    Refraction contrast X-ray imaging experiments were conducted on acrylic resin with an artificial cylindrical hole, A7075 aluminum alloy, A6063 aluminum castings, mild steel with cracks or voids, and low alloy steel with inclusions, using a ultra-bright synchrotron radiation X-ray beam in BL24XU hutch C of SPring-8. Conventional absorption contrast X-ray imaging experiments were also done for the comparison. The X-ray beam was controlled to be monochromatic by Si double-crystals and collimated by a slit. The distance between the sample and the detector was changed from 0 to 3 m, and the X-ray energy was 15 to 25 keV. Photographs were taken by X-ray film and/or X-ray CCD camera. As a result, the refraction imaging method gave a much more distinct image of the artificial cylindrical hole in acrylic resin as compared with the absorption method. The fatigue cracks in aluminum alloy and mild steel were also distinctly observed. The X-ray imaging revealed the presence of MnS nonmetallic inclusions in low alloy steel. Void defects in aluminum castings were clearly detected by the imaging. In addition, in-situ observation of tensile fracture of aluminum alloys using a high resolution X-ray CCD camera system wa successfully conducted. The observations by use of asymmetric reflection technique for X-ray imaging experiment were also well performed. From above, the X-ray imaging method using ultra-bright synchrotron radiation is concluded to be very useful for fracture research of materials. (author)

  2. Featured Image: A Galaxy Plunges Into a Cluster Core

    Science.gov (United States)

    Kohler, Susanna

    2015-10-01

    The galaxy that takes up most of the frame in this stunning image (click for the full view!) is NGC 1427A. This is a dwarf irregular galaxy (unlike the fortuitously-located background spiral galaxy in the lower right corner of the image), and its currently in the process of plunging into the center of the Fornax galaxy cluster. Marcelo Mora (Pontifical Catholic University of Chile) and collaborators have analyzed observations of this galaxy made by both the Very Large Telescope in Chile and the Hubble Advanced Camera for Surveys, which produced the image shown here as a color composite in three channels. The team worked to characterize the clusters of star formation within NGC 1427A identifiable in the image as bright knots within the galaxy and determine how the interactions of this galaxy with its cluster environment affect the star formation within it. For more information and the original image, see the paper below.Citation:Marcelo D. Mora et al 2015 AJ 150 93. doi:10.1088/0004-6256/150/3/93

  3. NSCLC tumor shrinkage prediction using quantitative image features.

    Science.gov (United States)

    Hunter, Luke A; Chen, Yi Pei; Zhang, Lifei; Matney, Jason E; Choi, Haesun; Kry, Stephen F; Martel, Mary K; Stingo, Francesco; Liao, Zhongxing; Gomez, Daniel; Yang, Jinzhong; Court, Laurence E

    2016-04-01

    The objective of this study was to develop a quantitative image feature model to predict non-small cell lung cancer (NSCLC) volume shrinkage from pre-treatment CT images. 64 stage II-IIIB NSCLC patients with similar treatments were all imaged using the same CT scanner and protocol. For each patient, the planning gross tumor volume (GTV) was deformed onto the week 6 treatment image, and tumor shrinkage was quantified as the deformed GTV volume divided by the planning GTV volume. Geometric, intensity histogram, absolute gradient image, co-occurrence matrix, and run-length matrix image features were extracted from each planning GTV. Prediction models were generated using principal component regression with simulated annealing subset selection. Performance was quantified using the mean squared error (MSE) between the predicted and observed tumor shrinkages. Permutation tests were used to validate the results. The optimal prediction model gave a strong correlation between the observed and predicted tumor shrinkages with r=0.81 and MSE=8.60×10(-3). Compared to predictions based on the mean population shrinkage this resulted in a 2.92 fold reduction in MSE. In conclusion, this study indicated that quantitative image features extracted from existing pre-treatment CT images can successfully predict tumor shrinkage and provide additional information for clinical decisions regarding patient risk stratification, treatment, and prognosis. PMID:26878137

  4. 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.

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

    International Nuclear Information System (INIS)

    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 T1-weighted imaging, T2-weighted imaging and fat-suppressed T2-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 T1-weighted and T2-weighted images in bone marrow, the other ten presented high signal intensity mixed in low signal intensity areas on T2- weighted and fat-suppressed T2-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)

  6. Feature maps driven no-reference image quality prediction of authentically distorted images

    Science.gov (United States)

    Ghadiyaram, Deepti; Bovik, Alan C.

    2015-03-01

    Current blind image quality prediction models rely on benchmark databases comprised of singly and synthetically distorted images, thereby learning image features that are only adequate to predict human perceived visual quality on such inauthentic distortions. However, real world images often contain complex mixtures of multiple distortions. Rather than a) discounting the effect of these mixtures of distortions on an image's perceptual quality and considering only the dominant distortion or b) using features that are only proven to be efficient for singly distorted images, we deeply study the natural scene statistics of authentically distorted images, in different color spaces and transform domains. We propose a feature-maps-driven statistical approach which avoids any latent assumptions about the type of distortion(s) contained in an image, and focuses instead on modeling the remarkable consistencies in the scene statistics of real world images in the absence of distortions. We design a deep belief network that takes model-based statistical image features derived from a very large database of authentically distorted images as input and discovers good feature representations by generalizing over different distortion types, mixtures, and severities, which are later used to learn a regressor for quality prediction. We demonstrate the remarkable competence of our features for improving automatic perceptual quality prediction on a benchmark database and on the newly designed LIVE Authentic Image Quality Challenge Database and show that our approach of combining robust statistical features and the deep belief network dramatically outperforms the state-of-the-art.

  7. Modeling the statistics of image features and associated text

    Science.gov (United States)

    Barnard, Kobus; Duygulu, Pinar; Forsyth, David A.

    2001-12-01

    We present a methodology for modeling the statistics of image features and associated text in large datasets. The models used also serve to cluster the images, as images are modeled as being produced by sampling from a limited number of combinations of mixing components. Furthermore, because our approach models the joint occurrence image features and associated text, it can be used to predict the occurrence of either, based on observations or queries. This supports an attractive approach to image search as well as novel applications such a suggesting illustrations for blocks of text (auto-illustrate) and generating words for images outside the training set (auto-annotate). In this paper we illustrate the approach on 10,000 images of work from the Fine Arts Museum of San Francisco. The images include line drawings, paintings, and pictures of sculpture and ceramics. Many of the images have associated free text whose nature varies greatly, from physical description to interpretation and mood. We incorporate statistical natural language processing in order to deal with free text. We use WordNet to provide semantic grouping information and to help disambiguate word senses, as well as emphasize the hierarchical nature of semantic relationships.

  8. Identification of Image Spam by Using Low Level & Metadata Features

    Directory of Open Access Journals (Sweden)

    Anand Gupta,

    2012-04-01

    Full Text Available Spammers are constantly evolving new spam technologies, the latest of which is image spam. Till now research in spam image identification has been addressed by considering properties like colour, size, compressibility, entropy, content etc. However, we feel the methods of identification so evolved have certain limitations due to embedded obfuscation like complex backgrounds, compression artifacts and wide variety of fonts and formats .To overcome these limitations, we have proposed 2 methodologies(however there can be more. Each methodology has 4 stages. Both the methodologies are almost similar except in the second stage where methodology I extracts low level features while the other extracts metadata features. Also a comparison between both the methodologies is shown. The method works on images with and without noise separately. Colour properties of the images are altered so that OCR (Optical Character Recognition can easily read the text embedded in the image. The proposed methods are tested on a dataset of 1984 spam images and are found to be effective in identifying all types of spam images having (1 only text, (2 only images or (3 both text and images. The encouraging experimental results show that the methodology I achieves an accuracy of 92% while the other achieves an accuracy of 93.3%

  9. 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.

  10. Automated Classification of Glaucoma Images by Wavelet Energy Features

    Directory of Open Access Journals (Sweden)

    N.Annu

    2013-04-01

    Full Text Available Glaucoma is the second leading cause of blindness worldwide. As glaucoma progresses, more optic nerve tissue is lost and the optic cup grows which leads to vision loss. This paper compiles a systemthat could be used by non-experts to filtrate cases of patients not affected by the disease. This work proposes glaucomatous image classification using texture features within images and efficient glaucoma classification based on Probabilistic Neural Network (PNN. Energy distribution over wavelet sub bands is applied to compute these texture features. Wavelet features were obtained from the daubechies (db3, symlets (sym3, and biorthogonal (bio3.3, bio3.5, and bio3.7 wavelet filters. It uses a technique to extract energy signatures obtained using 2-D discrete wavelet transform and the energy obtained from the detailed coefficients can be used to distinguish between normal and glaucomatous images. We observedan accuracy of around 95%, this demonstrates the effectiveness of these methods.

  11. ROI Segmentation for Feature Extraction from Human Facial Images

    Directory of Open Access Journals (Sweden)

    Surbhi

    2012-04-01

    Full Text Available Human Computer Interaction (HCI is the biggest goal of computer vision researchers. Features form the different facial images are able to provide a very deep knowledge about the activities performed by the different facial movements. In this paper we presented a technique for feature extraction from various regions of interest with the help of Skin color segmentation technique, Thresholding, knowledge based technique for face recognition.

  12. Imaging features of maxillary osteoblastoma and its malignant transformation

    International Nuclear Information System (INIS)

    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. Deep optical images of malin 1 reveal new features

    OpenAIRE

    Galaz, Gaspar; Milovic, Carlos; Suc, Vincent; Busta, Luis; Lizana, Guadalupe; Infante, Leopoldo; Royo Royo, Santiago

    2015-01-01

    We present Megacam deep optical images (g and r) of Malin 1 obtained with the 6.5m Magellan/Clay telescope, detecting structures down to ~ 28 B mag arcsec-2. In order to enhance galaxy features buried in the noise, we use a noise reduction filter based on the total generalized variation regularizator. This method allows us to detect and resolve very faint morphological features, including spiral arms, with a high visual contrast. For the first time, we can appreciate an optical image of Malin...

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

    International Nuclear Information System (INIS)

    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 complex sclerosing lesions of the breast

    Energy Technology Data Exchange (ETDEWEB)

    Myong, Joo Hwa; Choi, Byung Gil; Kim, Sung Hun; Kang, Bong Joo; Lee, Ah Won; Song, Byung Joo [Seoul St. Mary' s Hospital, The Catholic University of Korea College of Medicine, Seoul (Korea, Republic of)

    2014-03-15

    The purpose of this study was to evaluate the imaging features of complex sclerosing lesions of the breast and to assess the rate of upgrade to breast cancer. From March 2008 to May 2012, seven lesions were confirmed as complex sclerosing lesions by ultrasonography-guided core needle biopsy. Final results by either surgical excision or follow-up imaging studies were reviewed to assess the rate of upgrade to breast cancer. Two radiologists retrospectively analyzed the imaging findings according to the Breast Imaging Reporting and Data System classification. Five lesions underwent subsequent surgical excision and two of them revealed ductal carcinoma in situ (n=1) and invasive ductal carcinoma (n=1). Our study showed a breast cancer upgrade rate of 28.6% (2 of 7 lesions). Two lesions were stable on imaging follow-up beyond 1 year. The mammographic features included masses (n=4, 57.1%), architectural distortion (n=2, 28.6%), and focal asymmetry (n=1, 14.3%). Common B-mode ultrasonographic features were irregular shape (n=6, 85.7%), spiculated margin (n=5, 71.4 %), and hypoechogenicity (n=7, 100%). The final assessment categories were category 4 (n=6, 85.7%) and category 5 (n=1, 14.3%). The complex sclerosing lesions were commonly mass-like on mammography and showed the suspicious ultrasonographic features of category 4. Due to a high underestimation rate, all complex sclerosing lesions by core needle biopsy should be excised.

  16. Hyperspectral image classifier based on beach spectral feature

    International Nuclear Information System (INIS)

    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. Imaging Features of Extra Cranial Parapharyngeal Space Meningioma: Case Report

    Directory of Open Access Journals (Sweden)

    Kishor Taori

    2011-11-01

    Full Text Available Parapharyngeal tumors are less common in clinical practice and are often difficult to diagnose upon clinical examination due to the anatomic complexity of the region. We report a rare case of extracranial parapharyngeal space meningioma presenting as a cervical mass with encasement of cranial nerves giving tram track appearance and features on various imaging modalities [Radiographs, Ultrasound, Computed tomography (CT scan and Magnetic resonance imaging (MRI].

  19. Imaging Features of Extra Cranial Parapharyngeal Space Meningioma: Case Report

    OpenAIRE

    Kishor Taori; Kundaragi, Nischal G; Amit Disawal; Chetan Jathar; Prajwalit P. Gaur; Jawahar Rathod; Virendra Patil

    2011-01-01

    Parapharyngeal tumors are less common in clinical practice and are often difficult to diagnose upon clinical examination due to the anatomic complexity of the region. We report a rare case of extracranial parapharyngeal space meningioma presenting as a cervical mass with encasement of cranial nerves giving tram track appearance and features on various imaging modalities [Radiographs, Ultrasound, Computed tomography (CT) scan and Magnetic resonance imaging (MRI)].

  20. Measurement of Vocal Fold Features in Videokymography Images

    Czech Academy of Sciences Publication Activity Database

    Sedlář, Jiří; Novozámský, Adam; Švec, Jan G.; Zitová, Barbara; Flusser, Jan

    Dresden : Max Planck Institute, CBG, 2012. s. 53. [Bioimage Informatics. 16.09.2012-19.09.2012, Dresden] R&D Projects: GA ČR GAP103/11/1552 Keywords : videokymography * vocal folds measurement * image processing Subject RIV: JD - Computer Applications, Robotics http://library.utia.cas.cz/separaty/2013/ZOI/sedlar-measurement of vocal fold features in videokymography images.pdf

  1. Texture Features based Blur Classification in Barcode Images

    OpenAIRE

    Shamik Tiwari; Vidya Prasad Shukla; Sangappa Birada; Ajay Singh

    2013-01-01

    Blur is an undesirable phenomenon which appears as image degradation. Blur classification is extremely desirable before application of any blur parameters estimation approach in case of blind restoration of barcode image. A novel approach to classify blur in motion, defocus, and co-existence of both blur categories is presented in this paper. The key idea involves statistical features extraction of blur pattern in frequency domain and designing of blur classification system with feed forward ...

  2. Imaging features of primary malignant rhabdoid tumour of the brain

    International Nuclear Information System (INIS)

    Primary malignant rhabdoid tumour of the central nervous system is a rare neoplasm affecting children. We present a pathologically proven case, which was initially referred to the paediatric surgeons as a sebaceous cyst, and highlights the importance of imaging prior to surgery of potentially innocuous scalp lesions. Imaging features on CT and MRI are presented, which show bony involvement not previously reported in the literature. (orig.)

  3. Image Retrieval via Relevance Vector Machine with Multiple Features

    Directory of Open Access Journals (Sweden)

    Zemin Liu

    2014-05-01

    Full Text Available With the fast development of computer network technique, there is large amount of image information every day. Researchers have paid more and more attention to the problem of how users quickly retrieving and identifying the images that they may interest. Meanwhile, with the rapid development of artificial intelligence and pattern recognition techniques, it provides people with new thought on the study on complex image retrieval while it’s very difficult for traditional machine learning method to get ideal retrieval results. For this reason, we in this paper propose a new approach for image retrieval based on multiple types of image features and relevance vector machine (RVM. The proposed method, termed as MF-RVM, integrates the informative cures of features and the discrimination ability of RVM. The retrieval experiment is conducted on COREL image library which is collected from internet. The experimental results show that the proposed method can significantly improve the performance for image retrieval, so MF-RVM presented in this paper has very high practicability in image retrieval.

  4. Geometrically invariant color image watermarking scheme using feature points

    Institute of Scientific and Technical Information of China (English)

    WANG XiangYang; MENG Lan; YANG HongYing

    2009-01-01

    Geometric distortion is known as one of the most difficult attacks to resist.Geometric distortion desynchronizes the location of the watermark and hence causes incorrect watermark detection.In this paper,we propose a geometrically invariant digital watermarking method for color images.In order to synchronize the location for watermark insertion and detection,we use a multi-scale Harris-Laplace detector,by which feature points of a color image can be extracted that are invariant to geometric distortions.Then,the self-adaptive local image region (LIR) detection based on the feature scale theory was considered for watermarking.At each local image region,the watermark is embedded after image normalization.By binding digital watermark with invariant image regions,resilience against geometric distortion can be readily obtained.Our method belongs to the category of blind watermarking techniques,because we do not need the original image during detection.Experimental results show that the proposed color image watermarking is not only invisible and robust against common signal processing such as sharpening,noise adding,and JPEG compression,but also robust against the geometric distortions such as rotation,translation,scaling,row or column removal,shearing,and local random bend.

  5. Photoacoustic Imaging: Semiconducting Oligomer Nanoparticles as an Activatable Photoacoustic Probe with Amplified Brightness for In Vivo Imaging of pH (Adv. Mater. 19/2016).

    Science.gov (United States)

    Miao, Qingqing; Lyu, Yan; Ding, Dan; Pu, Kanyi

    2016-05-01

    Despite the great potential of photoacoustic imaging in the life sciences, the development of smart activatable photoacoustic probes remains elusive. On page 3662, K. Pu and co-workers report a facile nanoengineering approach based on semiconducting oligomer nano-particles to develop ratiometric photoacoustic probes with amplified brightness and enhanced sensing capability for accurate photoacoustic mapping of pH in the tumors of living mice. PMID:27167028

  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. Detection of fungal damaged popcorn using image property covariance features

    Science.gov (United States)

    Covariance-matrix-based features were applied to the detection of popcorn infected by a fungus that cause a symptom called “blue-eye.” This infection of popcorn kernels causes economic losses because of their poor appearance and the frequently disagreeable flavor of the popped kernels. Images of ker...

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

    International Nuclear Information System (INIS)

    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

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

    Energy Technology Data Exchange (ETDEWEB)

    Stacy, G.S. [Department of Radiology, University of Chicago Hospitals, Chicago, Illinois (United States)], E-mail: sstacy@radiology.bsd.uchicago.edu; Nair, L. [Department of Radiology, University of Chicago Hospitals, Chicago, Illinois (United States)

    2007-10-15

    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.

  10. Identification and Quantification Soil Redoximorphic Features by Digital Image Processing

    Science.gov (United States)

    Soil redoximorphic features (SRFs) have provided scientists and land managers with insight into relative soil moisture for approximately 60 years. The overall objective of this study was to develop a new method of SRF identification and quantification from soil cores using a digital camera and imag...

  11. Deep optical images of Malin 1 reveal new features

    CERN Document Server

    Galaz, Gaspar; Suc, Vincent; Busta, Luis; Lizana, Guadalupe; Infante, Leopoldo; Royo, Santiago

    2015-01-01

    We present Megacam deep optical images (g and r) of Malin 1 obtained with the 6.5m Magellan/Clay telescope, detecting structures down to ~ 28 B mag arcsec-2. In order to enhance galaxy features buried in the noise, we use a noise reduction filter based on the total generalized variation regularizator. This method allows us to detect and resolve very faint morphological features, including spiral arms, with a high visual contrast. For the first time, we can appreciate an optical image of Malin 1 and its morphology in full view. The images provide unprecedented detail, compared to those obtained in the past with photographic plates and CCD, including HST imaging. We detect two peculiar features in the disk/spiral arms. The analysis suggests that the first one is possibly a background galaxy, and the second is an apparent stream without a clear nature, but could be related to the claimed past interaction between Malin 1 and the galaxy SDSSJ123708.91 + 142253.2. Malin 1 exhibits features suggesting the presence o...

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

    International Nuclear Information System (INIS)

    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

  13. Diffusion tensor image registration using tensor geometry and orientation features.

    Science.gov (United States)

    Yang, Jinzhong; Shen, Dinggang; Davatzikos, Christos; Verma, Ragini

    2008-01-01

    This paper presents a method for deformable registration of diffusion tensor (DT) images that integrates geometry and orientation features into a hierarchical matching framework. The geometric feature is derived from the structural geometry of diffusion and characterizes the shape of the tensor in terms of prolateness, oblateness, and sphericity of the tensor. Local spatial distributions of the prolate, oblate, and spherical geometry are used to create an attribute vector of geometric feature for matching. The orientation feature improves the matching of the WM fiber tracts by taking into account the statistical information of underlying fiber orientations. These features are incorporated into a hierarchical deformable registration framework to develop a diffusion tensor image registration algorithm. Extensive experiments on simulated and real brain DT data establish the superiority of this algorithm for deformable matching of diffusion tensors, thereby aiding in atlas creation. The robustness of the method makes it potentially useful for group-based analysis of DT images acquired in large studies to identify disease-induced and developmental changes. PMID:18982691

  14. Spitzer/IRAC Imaging of Exceptionally Bright Cluster-Lensed Submillimeter Galaxies Discovered by the Herschel Lensing Survey

    Science.gov (United States)

    Egami, Eiichi; Ebeling, Harald; Rawle, Timothy; Clement, Benjamin; Walth, Gregory; Pereira, Maria; Richard, Johan; Kneib, Jean-Paul

    2012-12-01

    Over the last few years, discoveries of exceptionally bright (e.g., observed S_peak > 100 mJy in the Herschel/SPIRE bands) gravitationally lensed submillimeter galaxies (SMGs) have generated great excitement. This is because these gravitationally lensed SMGs are so bright that they enable us to perform a variety of follow-up observations using a suite of observing facilities in the submillimeter, millimeter, and radio now available on the ground. Using Herschel, our team has been conducting a survey of such bright lensed galaxies in the fields of massive galaxy clusters: ``The Herschel Lensing Survey (HLS)'' (PI: Egami; 419 hours). This large Herschel program targets a total of 581 X-ray/SZ-selected massive clusters, and is currently 80% complete. Cluster lenses are often more powerful than galaxy lenses, producing larger magnifications. For example, typical magnification factors for galaxy-lensed Herschel sources are x10 or less while cluster-lensed systems can often produce magnification factors of x20-30 and even above x100. Cluster lenses will therefore allow us to detect and study intrinsically less-luminous and/or more distant sources with the ability to provide a view of finer-scale (i.e., sub-kpc) structures. Here, we propose to conduct Spitzer/IRAC imaging of 56 bright lensed SMG candidates we have identified in the ~470 HLS cluster fields observed so far. The main scientific goal is twofold: (1) to locate the underlying stellar component, and (2) to study its properties (e.g., stellar mass, specific star-formation rate) by constraining the rest-frame near-infrared SED and comparing with the Herschel and other submillimeter/millimeter data (e.g., SMA, PdB, ALMA, etc.). These rare bright lensed SMGs will allow us to probe the population of heavily dust-obscured vigorously star-forming galaxies at high redshift (z>1), which is thought to play an important role in the cosmic star-formation history of the Universe and yet has been difficult to study due to the

  15. Ovarian malignant germ cell tumors: cellular classification and clinical and imaging features.

    Science.gov (United States)

    Shaaban, Akram M; Rezvani, Maryam; Elsayes, Khaled M; Baskin, Henry; Mourad, Amr; Foster, Bryan R; Jarboe, Elke A; Menias, Christine O

    2014-01-01

    Ovarian malignant germ cell tumors (OMGCTs) are heterogeneous tumors that are derived from the primitive germ cells of the embryonic gonad. OMGCTs are rare, accounting for about 2.6% of all ovarian malignancies, and typically manifest in adolescence, usually with abdominal pain, a palpable mass, and elevated serum tumor marker levels, which may serve as an adjunct in the initial diagnosis, monitoring during therapy, and posttreatment surveillance. Dysgerminoma, the most common malignant germ cell tumor, usually manifests as a solid mass. Immature teratomas manifest as a solid mass with scattered foci of fat and calcifications. Yolk sac tumors usually manifest as a mixed solid and cystic mass. Capsular rupture or the bright dot sign, a result of increased vascularity and the formation of small vascular aneurysms, may be present. Embryonal carcinomas and polyembryomas rarely manifest in a pure form and are more commonly part of a mixed germ cell tumor. Some OMGCTs have characteristic features that allow a diagnosis to be confidently made, whereas others have nonspecific features, which make them difficult to diagnose. However, imaging features, the patient's age at presentation, and tumor markers may help establish a reasonable differential diagnosis. Malignant ovarian germ cell tumors spread in the same manner as epithelial ovarian neoplasms but are more likely to involve regional lymph nodes. Preoperative imaging may depict local extension, peritoneal disease, and distant metastases. Suspicious areas may be sampled during surgery. Because OMGCTs are almost always unilateral and are chemosensitive, fertility-sparing surgery is the standard of care. PMID:24819795

  16. New learning subspace method for image feature extraction

    Institute of Scientific and Technical Information of China (English)

    CAO Jian-hai; LI Long; LU Chang-hou

    2006-01-01

    A new method of Windows Minimum/Maximum Module Learning Subspace Algorithm(WMMLSA) for image feature extraction is presented. The WMMLSM is insensitive to the order of the training samples and can regulate effectively the radical vectors of an image feature subspace through selecting the study samples for subspace iterative learning algorithm,so it can improve the robustness and generalization capacity of a pattern subspace and enhance the recognition rate of a classifier. At the same time,a pattern subspace is built by the PCA method. The classifier based on WMMLSM is successfully applied to recognize the pressed characters on the gray-scale images. The results indicate that the correct recognition rate on WMMLSM is higher than that on Average Learning Subspace Method,and that the training speed and the classification speed are both improved. The new method is more applicable and efficient.

  17. EFFICIENT IMAGE COMPRESSION TECHNIQUE USING SELF ORGANIZING FEATURE MAPS

    Directory of Open Access Journals (Sweden)

    G. MOHIUDDIN BHAT

    2010-12-01

    Full Text Available Due to the widespread use of Multimedia applications, the need for image compression is increasing day-by-day. The image compression schemes are aimed to reduce the transmission rates for still images without sacrificing much of the image quality. In this paper, an Artificial Neural Network (ANN approach for image compression ispresented. The Codebook for Linear Vector Quantization (LVQ is designed using Self Organized Feature Maps (SOFM. Arithmetic Coding is then used to remove redundancies between indexes of vectors corresponding to the neighboring blocks in the original image, which then leads to further compression. The simulation results demonstrate the improved coding efficiency of the proposed method, when compared with JPEG. The proposed scheme allows achieving a compression ratio upto approximately 40:1 with reasonable image quality. Further, thesimulation results demonstrate that an additional bit-rate reduction of upto approximately 30-50% can be achieved using Arithmetic Coding, without any further degradation of the image quality. When compared with JPEG, the proposed coder results reconstructed images having 0.1-0.25 dB better quality in terms of PSNR than that of JPEGcoder.

  18. Uranus' Persistent Patterns and Features from High-SNR Imaging in 2012-2014

    Science.gov (United States)

    Fry, Patrick M.; Sromovsky, Lawrence A.; de Pater, Imke; Hammel, Heidi B.; Marcus, Phillip

    2015-11-01

    Since 2012, Uranus has been the subject of an observing campaign utilizing high signal-to-noise imaging techniques at Keck Observatory (Fry et al. 2012, Astron. J. 143, 150-161). High quality observing conditions on four observing runs of consecutive nights allowed longitudinally-complete coverage of the atmosphere over a period of two years (Sromovsky et al. 2015, Icarus 258, 192-223). Global mosaic maps made from images acquired on successive nights in August 2012, November 2012, August 2013, and August 2014, show persistent patterns, and six easily distinguished long-lived cloud features, which we were able to track for long periods that ranged from 5 months to over two years. Two at similar latitudes are associated with dark spots, and move with the atmospheric zonal flow close to the location of their associated dark spot instead of following the flow at the latitude of the bright features. These features retained their morphologies and drift rates in spite of several close interactions. A second pair of features at similar latitudes also survived several close approaches. Several of the long-lived features also exhibited equatorward drifts and latitudinal oscillations. Also persistent are a remarkable near-equatorial wave feature and global zonal band structure. We will present imagery, maps, and analyses of these phenomena.PMF and LAS acknowledge support from NASA Planetary Astronomy Program; PMF and LAS acknowledge funding and technical support from W. M. Keck Observatory. We thank those of Hawaiian ancestry on whose sacred mountain we are privileged to be guests. Without their generous hospitality none of our groundbased observations would have been possible.

  19. Image Recognition and Feature Detection in Solar Physics

    Science.gov (United States)

    Martens, Petrus C.

    2012-05-01

    The Solar Dynamics Observatory (SDO) data repository will dwarf the archives of all previous solar physics missions put together. NASA recognized early on that the traditional methods of analyzing the data -- solar scientists and grad students in particular analyzing the images by hand -- would simply not work and tasked our Feature Finding Team (FFT) with developing automated feature recognition modules for solar events and phenomena likely to be observed by SDO. Having these metadata available on-line will enable solar scientist to conduct statistical studies involving large sets of events that would be impossible now with traditional means. We have followed a two-track approach in our project: we have been developing some existing task-specific solar feature finding modules to be "pipe-line" ready for the stream of SDO data, plus we are designing a few new modules. Secondly, we took it upon us to develop an entirely new "trainable" module that would be capable of identifying different types of solar phenomena starting from a limited number of user-provided examples. Both approaches are now reaching fruition, and I will show examples and movies with results from several of our feature finding modules. In the second part of my presentation I will focus on our “trainable” module, which is the most innovative in character. First, there is the strong similarity between solar and medical X-ray images with regard to their texture, which has allowed us to apply some advances made in medical image recognition. Second, we have found that there is a strong similarity between the way our trainable module works and the way our brain recognizes images. The brain can quickly recognize similar images from key characteristics, just as our code does. We conclude from that that our approach represents the beginning of a more human-like procedure for computer image recognition.

  20. Document image retrieval based on multi-density features

    Institute of Scientific and Technical Information of China (English)

    HU Zhilan; LIN Xinggang; YAN Hong

    2007-01-01

    The development of document image databases is becoming a challenge for document image retrieval techniques.Traditional layout-reconstructed-based methods rely on high quality document images as well as an optical character recognition (OCR) precision,and can only deal with several widely used languages.The complexity of document layouts greatly hinders layout analysis-based approaches.This paper describes a multi-density feature based algorithm for binary document images,which is independent of OCR or layout analyses.The text area was extracted after preprocessing such as skew correction and marginal noise removal.Then the aspect ratio and multi-density features were extracted from the text area to select the best candidates from the document image database.Experimental results show that this approach is simple with loss rates less than 3% and can efficiently analyze images with different resolutions and different input systems.The system is also robust to noise due to its notes and complex layouts,etc.

  1. Evaluation of Selected Features for CAR Detection in Aerial Images

    Science.gov (United States)

    Tuermer, S.; Leitloff, J.; Reinartz, P.; Stilla, U.

    2011-09-01

    The extraction of vehicles from aerial images provides a wide area traffic situation within a short time. Applications for the gathered data are various and reach from smart routing in the case of congestions to usability validation of roads in the case of disasters. The challenge of the vehicle detection task is finding adequate features which are capable to separate cars from other objects; especially those that look similar. We present an experiment where selected features show their ability of car detection. Precisely, Haar-like and HoG features are utilized and passed to the AdaBoost algorithm for calculating the final detector. Afterwards the classifying power of the features is accurately analyzed and evaluated. The tests a carried out on aerial data from the inner city of Munich, Germany and include small inner city roads with rooftops close by which raise the complexity factor.

  2. Angular Variation of Solar Feature Contrast in Full-Disk G-Band Images

    Science.gov (United States)

    Blunt, Sarah Caroline; Criscuoli, Serena; Ermolli, Ilaria; Giorgi, Fabrizio

    2015-01-01

    We investigate the center-to-limb variation (CLV) of the contrasts of four types of solar surface features observed in the G-Band (430.6 nm, FWHM 1.2 nm) by analyzing 12 high quality full-disk images obtained from the Rome Precision Solar Photometric Telescope. The studied features, specifically network, enhanced network, plage, and bright plage, were singled out based on their brightness signatures in mean simultaneous Ca II K images using an intensity threshold technique. We compared our results with those obtained from high-resolution (HR) observations, and with the outputs of the spectral synthesis performed on semi-empirical models and magneto hydrodynamic (MHD) simulations. We find that the measured contrasts are systematically lower than those of HR observational results, as was expected due to the lower resolution of the analyzed observations. We also find that our observations best reflect the CLV derived from the recent one-dimensional atmospheric models described in Fontenla et al 2011 with respect to results obtained from earlier similar models. The measured CLV also agrees with those derived from the syntheses of MHD simulations and HR observations, if spatial resolution effects are properly taken into account. This work was carried out through the National Solar Observatory Summer Research Assistantship (SRA) Program. The National Solar Observatory is operated by the Association of Universities for Research in Astronomy, Inc. (AURA) under cooperative agreement with the National Science Foundation. This work was also partially supported by the European Union's Seventh Programme for Research, Technological Development and Demonstration under the grant agreements in 312495 (SOLARNET) and 313188 (SOLID).

  3. Image recognition of diseased rice seeds based on color feature

    Science.gov (United States)

    Cheng, Fang; Ying, Yibin

    2004-11-01

    The objective of this research is to develop a digital image analysis algorithm for detection of diseased rice seeds based on color features. The rice seeds used for this study involved five varieties of Jinyou402, Shanyou10, Zhongyou207, Jiayou99 and IIyou3207. Images of rice seeds were acquired with a color machine vision system. Each original RGB image was converted to HSV color space and preprocessed to show, as hue in the seed region while the pixels value of background was zero. The hue values were scaled so that they varied from 0.0 to 1.0. Then six color features were extracted and evaluated for their contributions to seed classification. Determined using Blocks method, the mean hue value shows the strongest classification ability. Parzen windowing function method was used to estimate probability density distribution and a threshold of mean hue was drawn to classify normal seeds and diseased seeds. The average accuracy of test data set is 95% for Jinyou402. Then the feature of hue histogram was extracted for diseased seeds and partitioned into two clusters of spot diseased seeds and severe diseased seeds. Desired results were achieved when the two cancroids locations were used to discriminate the disease degree. Combined with the two features of mean hue and histogram, all seeds could be classified as normal seeds, spot diseased seeds and severe diseased seeds. Finally, the algorithm was implemented for all the five varieties to test the adaptability.

  4. A flower image retrieval method based on ROI feature

    Institute of Scientific and Technical Information of China (English)

    洪安祥; 陈刚; 李均利; 池哲儒; 张亶

    2004-01-01

    Flower image retrieval is a very important step for computer-aided plant species recognition. In this paper, we propose an efficient segmentation method based on color clustering and domain knowledge to extract flower regions from flower images. For flower retrieval, we use the color histogram of a flower region to characterize the color features of flower and two shape-based features sets, Centroid-Contour Distance (CCD) and Angle Code Histogram (ACH), to characterize the shape features of a flower contour. Experimental results showed that our flower region extraction method based on color clustering and domain knowledge can produce accurate flower regions. Flower retrieval results on a database of 885 flower images collected from 14 plant species showed that our Region-of-Interest (ROI) based retrieval approach using both color and shape features can perform better than a method based on the global color histogram proposed by Swain and Ballard (1991) and a method based on domain knowledge-driven segmentation and color names proposed by Das et al.(1999).

  5. A flower image retrieval method based on ROI feature

    Institute of Scientific and Technical Information of China (English)

    洪安祥; 陈刚; 李均利; 池哲儒; 张亶

    2004-01-01

    Flower image retrieval is a very important step for computer-aided plant species recognition.In this paper,we propose an efficient segmentation method based on color clustering and domain knowledge to extract flower regions from flower images.For flower retrieval,we use the color histogram of a flower region to characterize the color features of flower and two shape-based features sets,Centroid-Contour Distance(CCD)and Angle Code Histogram(ACH),to characterize the shape features of a flower contour.Experimental results showed that our flower region extraction method based on color clustering and domain knowledge can produce accurate flower regions.Flower retrieval results on a database of 885 flower images collected from 14 plant species showed that our Region-of-Interest(ROD based retrieval approach using both color and shape features can perform better than a method based on the global color histogram proposed by Swain and Ballard(1991)and a method based on domain knowledge-driven segmentation and color names proposed by Das et al.(1999).

  6. Imaging features of Benign fibrous histiocytoma of bone

    International Nuclear Information System (INIS)

    Objective: To evaluate the imaging features of benign fibrous histiocytoma (BFH). Methods: Imaging data were retrospectively collected and reviewed in 11 patients with pathologically proved BFH. Of the 11 patients, X-ray was performed in all patients,MR scans in 6 patients, and CT scans in 4 patients. Results: All lesions detected were a solitary lesion.The distribution of BFH was in the tibia (n=5), femur (n=3), fibula (n=1), sacrum (n=1), and thoracic vertebrae (n=1). X-ray features included eccentric osteolytic lesions in 7 patients and centric in 2 patients, with clear boundary and thinning of the cortex, and 7 patients with varying degrees of ossified border were found. CT scan shows bone destruction with density similar to soft tissue. The majority of lesions (n=3) were observed in the expanding shell of bone, 2 patients in the tibia and 1 patient in the thoracic lesions with cortical bone perforation. The thoracic lesion as soft tissue mass was detected. All of the lesions detected in CT showed no periosteal reaction. In patients with MR images, hypo to isointense signal intensity on T1WI and hyperintense signal intensity on T2WI was found. All lesions on post-contrast T1WI were detected with homogeneous or heterogeneous lesion with moderate or significant enhancement. Conclusion: Imaging features were typical for MFH which is useful tool helping correct diagnosis of MFH. (authors)

  7. Quantitative imaging features to predict cancer status in lung nodules

    Science.gov (United States)

    Liu, Ying; Balagurunathan, Yoganand; Atwater, Thomas; Antic, Sanja; Li, Qian; Walker, Ronald; Smith, Gary T.; Massion, Pierre P.; Schabath, Matthew B.; Gillies, Robert J.

    2016-03-01

    Background: We propose a systematic methodology to quantify incidentally identified lung nodules based on observed radiological traits on a point scale. These quantitative traits classification model was used to predict cancer status. Materials and Methods: We used 102 patients' low dose computed tomography (LDCT) images for this study, 24 semantic traits were systematically scored from each image. We built a machine learning classifier in cross validation setting to find best predictive imaging features to differentiate malignant from benign lung nodules. Results: The best feature triplet to discriminate malignancy was based on long axis, concavity and lymphadenopathy with average AUC of 0.897 (Accuracy of 76.8%, Sensitivity of 64.3%, Specificity of 90%). A similar semantic triplet optimized on Sensitivity/Specificity (Youden's J index) included long axis, vascular convergence and lymphadenopathy which had an average AUC of 0.875 (Accuracy of 81.7%, Sensitivity of 76.2%, Specificity of 95%). Conclusions: Quantitative radiological image traits can differentiate malignant from benign lung nodules. These semantic features along with size measurement enhance the prediction accuracy.

  8. Cuckoo search algorithm based satellite image contrast and brightness enhancement using DWT-SVD.

    Science.gov (United States)

    Bhandari, A K; Soni, V; Kumar, A; Singh, G K

    2014-07-01

    This paper presents a new contrast enhancement approach which is based on Cuckoo Search (CS) algorithm and DWT-SVD for quality improvement of the low contrast satellite images. The input image is decomposed into the four frequency subbands through Discrete Wavelet Transform (DWT), and CS algorithm used to optimize each subband of DWT and then obtains the singular value matrix of the low-low thresholded subband image and finally, it reconstructs the enhanced image by applying IDWT. The singular value matrix employed intensity information of the particular image, and any modification in the singular values changes the intensity of the given image. The experimental results show superiority of the proposed method performance in terms of PSNR, MSE, Mean and Standard Deviation over conventional and state-of-the-art techniques. PMID:24893835

  9. Deep Optical Images of Malin 1 Reveal New Features

    Science.gov (United States)

    Galaz, Gaspar; Milovic, Carlos; Suc, Vincent; Busta, Luis; Lizana, Guadalupe; Infante, Leopoldo; Royo, Santiago

    2015-12-01

    We present Megacam deep optical images (g and r) of Malin 1 obtained with the 6.5 m Magellan/Clay telescope, detecting structures down to ˜28 B mag arcsec-2. In order to enhance galaxy features buried in the noise, we use a noise reduction filter based on the total generalized variation regularizator. This method allows us to detect and resolve very faint morphological features, including spiral arms, with a high visual contrast. For the first time, we can appreciate an optical image of Malin 1 and its morphology in full view. The images provide unprecedented detail, compared to those obtained in the past with photographic plates and CCD, including Hubble Space Telescope imaging. We detect two peculiar features in the disk/spiral arms. The analysis suggests that the first one is possibly a background galaxy, and the second is an apparent stream without a clear nature, but could be related to the claimed past interaction between Malin 1 and the galaxy SDSSJ123708.91+142253.2. Malin 1 exhibits features suggesting the presence of stellar associations and clumps of molecular gas, not seen before with such a clarity. Using these images, we obtain a diameter for Malin 1 of 160 kpc, ˜50 kpc larger than previous estimates. A simple analysis shows that the observed spiral arms reach very low luminosity and mass surface densities, to levels much lower than the corresponding values for the Milky Way. This paper includes data gathered with the 6.5 meter Magellan Telescopes located at Las Campanas Observatory, Chile.

  10. 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.

  11. Content Based Image Retrieval using Color Boosted Salient Points and Shape features of an image.

    Directory of Open Access Journals (Sweden)

    Hiremath P. S

    2008-02-01

    Full Text Available Salient points are locations in an image where there is a significant variation withrespect to a chosen image feature. Since the set of salient points in an imagecapture important local characteristics of that image, they can form the basis of agood image representation for content-based image retrieval (CBIR. Salientfeatures are generally determined from the local differential structure of images.They focus on the shape saliency of the local neighborhood. Most of thesedetectors are luminance based which have the disadvantage that thedistinctiveness of the local color information is completely ignored in determiningsalient image features. To fully exploit the possibilities of salient point detection incolor images, color distinctiveness should be taken into account in addition toshape distinctiveness. This paper presents a method for salient pointsdetermination based on color saliency. The color and texture information aroundthese points of interest serve as the local descriptors of the image. In addition,the shape information is captured in terms of edge images computed usingGradient Vector Flow fields. Invariant moments are then used to record theshape features. The combination of the local color, texture and the global shapefeatures provides a robust feature set for image retrieval. The experimentalresults demonstrate the efficacy of the method.

  12. 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.

  13. Imaging features of intraosseous ganglia: a report of 45 cases

    International Nuclear Information System (INIS)

    The aim of this study is to report the spectrum of imaging findings of intraosseous ganglia (IG) with particular emphasis on the radiographic and magnetic resonance (MR) features. Forty-five patients with a final diagnosis of IG were referred to a specialist orthopaedic oncology service with the presumptive diagnosis of either a primary or secondary bone tumour. The diagnosis was established by histology in 25 cases. In the remainder, the imaging features were considered characteristic and the lesion was stable on follow-up radiographic examination. Radiographs were available for retrospective review in all cases and MR imaging in 29. There was a minor male preponderance with a wide adult age range. Three quarters were found in relation to the weight-bearing long bones of the lower limb, particularly round the knee. On radiographs all were juxta-articular and osteolytic; 74% were eccentric in location, 80% had a sclerotic endosteal margin and 60% of cases showed a degree of trabeculation. Periosteal new bone formation and matrix mineralization were not present. Of the 29 cases that underwent MR imaging, 66% were multiloculated. On T1-weighted images the IG contents were isointense or mildly hypointense in 90% cases. Forty-one per cent of the cases showed a slightly hyperintense rim lining that enhanced with a gadolinium chelate. Thirty-eight per cent were associated with soft tissue extension and 17% with a defect of the adjacent articular cortex. Fifty-five per cent showed surrounding marrow oedema on T2-weighted or STIR images and two cases (7%) a fluid-fluid level prior to any surgical intervention. The authors contend that it is semantics to differentiate between an IG and a degenerate subchondral cyst as, while the initial pathogenesis may vary, the histological endpoint is identical, as are the imaging features apart from the degree of associated degenerative joint disease. IGs, particularly when large, may be mistaken for a bone tumour. Correlation of the

  14. Primary Neuroendocrine Tumor of the Breast: Imaging Features

    Energy Technology Data Exchange (ETDEWEB)

    Chang, Eun Deok [Department of Clinical Pathology, Uijeongbu St. Mary' s Hospital, College of Medicine, The Catholic University of Korea, Uijeongbu 480-717 (Korea, Republic of); Kim, Min Kyun [Department of Radiology, Uijeongbu St. Mary' s Hospital, College of Medicine, The Catholic University of Korea, Uijeongbu 480-717 (Korea, Republic of); Kim, Jeong Soo [Department of Surgery, Uijeongbu St. Mary' s Hospital, College of Medicine, The Catholic University of Korea, Uijeongbu 480-717 (Korea, Republic of); Whang, In Yong [Department of Radiology, Uijeongbu St. Mary' s Hospital, College of Medicine, The Catholic University of Korea, Uijeongbu 480-717 (Korea, Republic of)

    2013-07-01

    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. Characteristic imaging features of body packers: a pictorial essay.

    Science.gov (United States)

    Ab Hamid, Suzana; Abd Rashid, Saiful Nizam; Mohd Saini, Suraini

    2012-06-01

    The drug-trafficking business has risen tremendously because of the current increased demand for illegal narcotics. The smugglers conceal the drugs in their bodies (body packers) in order to bypass the tight security at international borders. A suspected body packer will normally be sent to the hospital for imaging investigations to confirm the presence of drugs in the body. Radiologists, therefore, need to be familiar with and able to identify drug packets within the human body because they shoulder the legal responsibilities. This pictorial essay describes the characteristic imaging features of drug packets within the gastrointestinal tract. PMID:22415809

  16. Beyond 31 mag arcsec‑2: The Frontier of Low Surface Brightness Imaging with the Largest Optical Telescopes

    Science.gov (United States)

    Trujillo, Ignacio; Fliri, Jüergen

    2016-06-01

    The detection of structures in the sky with optical surface brightnesses fainter than 30 mag arcsec‑2 (3σ in 10 × 10 arcsec boxes; r-band) has remained elusive in current photometric deep surveys. Here we show how present-day telescopes of 10 m class can provide broadband imaging 1.5–2 mag deeper than most previous results within a reasonable amount of time (i.e., power to explore the stellar halo of the galaxy UGC 00180, a galaxy analogous to M31 located at ∼150 Mpc, by obtaining a radial profile of surface brightness down to μ r ∼ 33 mag arcsec‑2. This depth is similar to that obtained using the star-counts techniques for Local Group galaxies, but is achieved at a distance where this technique is unfeasible. We find that the mass of the stellar halo of this galaxy is ∼4 × 109 M ⊙, i.e., (3 ± 1)% of the total stellar mass of the whole system. This amount of mass in the stellar halo is in agreement with current theoretical expectations for galaxies of this kind.

  17. Omnidirectional Thermal Imaging Surveillance System Featuring Trespasser and Faint Detection

    Directory of Open Access Journals (Sweden)

    Wong Wai Kit, Zeh-Yang Chew, Hong-Liang Lim, Chu-Kiong Loo, Way-Soong Lim

    2011-02-01

    Full Text Available This paper proposed an efficient omnidirectional thermal imaging surveillancesystem featuring trespasser and faint detection. In this thermal imaging system,the omnidirectional scenes in a monitored site such as old folks home, nursinghome, hospital etc. are first captured using a thermal camera attached to acustom made hyperbolic IR (infrared radiation reflected mirror. The capturedscenes to be monitored with trespasser or faint detection are then fed into alaptop computer for image processing and alarm purposes. Log-polar mapping isproposed to map the captured omnidirectional thermal image into panoramicimage, hence providing the observer or image processing tools a complete wideangle of view. Two effective human behavioral detection algorithms namely:Human head detection algorithm and home alone faint detection algorithm arealso designed for monitored the trespasser or fainted people detection. Theobserved significances of this new proposed omnidirectional thermal imagingsystem include: it can cover a wide angle of view (360º omnidirectional, usingminimum hardware, low cost and the output thermal images are with higher datacompression. Experimental results show that the proposed thermal imaging surveillance system achieves high accuracy in detecting trespasser andmonitoring faint detection for health care purpose.

  18. Imaging features of benign and malignant ampullary and periampullary lesions.

    Science.gov (United States)

    Nikolaidis, Paul; Hammond, Nancy A; Day, Kevin; Yaghmai, Vahid; Wood, Cecil G; Mosbach, David S; Harmath, Carla B; Taffel, Myles T; Horowitz, Jeanne M; Berggruen, Senta M; Miller, Frank H

    2014-01-01

    The ampulla of Vater is an important anatomic landmark where the common bile duct and main pancreatic duct converge in the major duodenal papilla. Imaging evaluation of the ampulla and periampullary region poses a unique diagnostic challenge to radiologists because of the region's complex and variable anatomy and the variety of lesions that can occur. Lesions intrinsic to the ampulla and involved segment of the biliary tree can be neoplastic, inflammatory, or congenital. Neoplastic lesions include ampullary adenocarcinomas and adenomas, which often are difficult to differentiate, as well as pancreatic or duodenal adenocarcinomas, pancreatic neuroendocrine tumors, and cholangiocarcinomas. Ultrasonography (US), computed tomography, magnetic resonance (MR) imaging, and MR cholangiopancreatography are commonly used to evaluate this region. Endoscopic retrograde cholangiopancreatography or endoscopic US examination may be necessary for more definitive evaluation. Periampullary conditions in the duodenum that may secondarily involve the ampulla include neoplasms, duodenitis, duodenal diverticula, and Brunner's gland hyperplasia or hamartomas. Because these lesions can exhibit a wide overlap of imaging features and subtle or nonspecific imaging findings, diagnosis is made on the basis of patient age, clinical history, and imaging and laboratory findings. Given the complexity of imaging evaluation of the ampulla and periampullary region, it is essential for radiologists to understand the variety of lesions that can occur and recognize their imaging characteristics. PMID:24819785

  19. Adrenal imaging for adenoma characterization: imaging features, diagnostic accuracies and differential diagnoses.

    Science.gov (United States)

    Park, Jung Jae; Park, Byung Kwan; Kim, Chan Kyo

    2016-06-01

    Adrenocortical adenoma is the most common adrenal tumour. This lesion is frequently encountered on cross-sectional imaging that has been performed for unrelated reasons. Adrenal adenoma manifests various imaging features on CT, MRI and positron emission tomography/CT. The learning objectives of this review are to describe the imaging findings of adrenocortical adenoma, to compare the sensitivities of different imaging modalities for adenoma characterization and to introduce differential diagnoses. PMID:26867466

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

    International Nuclear Information System (INIS)

    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)

  1. 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)

  2. A new imaging technique on strength and phase of pulsatile tissue-motion in brightness-mode ultrasonogram

    Science.gov (United States)

    Fukuzawa, Masayuki; Yamada, Masayoshi; Nakamori, Nobuyuki; Kitsunezuka, Yoshiki

    2007-03-01

    A new imaging technique has been developed for observing both strength and phase of pulsatile tissue-motion in a movie of brightness-mode ultrasonogram. The pulsatile tissue-motion is determined by evaluating the heartbeat-frequency component in Fourier transform of a series of pixel value as a function of time at each pixel in a movie of ultrasonogram (640x480pixels/frame, 8bit/pixel, 33ms/frame) taken by a conventional ultrasonograph apparatus (ATL HDI5000). In order to visualize both the strength and the phase of the pulsatile tissue-motion, we propose a pulsatile-phase image that is obtained by superimposition of color gradation proportional to the motion phase on the original ultrasonogram only at which the motion strength exceeds a proper threshold. The pulsatile-phase image obtained from a cranial ultrasonogram of normal neonate clearly reveals that the motion region gives good agreement with the anatomical shape and position of the middle cerebral artery and the corpus callosum. The motion phase is fluctuated with the shape of arteries revealing local obstruction of blood flow. The pulsatile-phase images in the neonates with asphyxia at birth reveal decreases of the motion region and increases of the phase fluctuation due to the weakness and local disturbance of blood flow, which is useful for pediatric diagnosis.

  3. 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

  4. Spinal cord ischemia: aetiology, clinical syndromes and imaging features

    International Nuclear Information System (INIS)

    The purpose of this study was to analyse MR imaging features and lesion patterns as defined by compromised vascular territories, correlating them to different clinical syndromes and aetiological aspects. In a 19.8-year period, clinical records and magnetic resonance imaging (MRI) features of 55 consecutive patients suffering from spinal cord ischemia were evaluated. Aetiologies of infarcts were arteriosclerosis of the aorta and vertebral arteries (23.6 %), aortic surgery or interventional aneurysm repair (11 %) and aortic and vertebral artery dissection (11 %), and in 23.6 %, aetiology remained unclear. Infarcts occurred in 38.2 % at the cervical and thoracic level, respectively, and 49 % of patients suffered from centromedullar syndrome caused by anterior spinal artery ischemia. MRI disclosed hyperintense pencil-like lesion pattern on T2WI in 98.2 %, cord swelling in 40 %, enhancement on post-contrast T1WI in 42.9 % and always hyperintense signal on diffusion-weighted imaging (DWI) when acquired. The most common clinical feature in spinal cord ischemia is a centromedullar syndrome, and in contrast to anterior spinal artery ischemia, infarcts in the posterior spinal artery territory are rare. The exclusively cervical location of the spinal sulcal artery syndrome seems to be a likely consequence of anterior spinal artery duplication which is observed preferentially here. (orig.)

  5. Dual-pass feature extraction on human vessel images.

    Science.gov (United States)

    Hernandez, W; Grimm, S; Andriantsimiavona, R

    2014-06-01

    We present a novel algorithm for the extraction of cavity features on images of human vessels. Fat deposits in the inner wall of such structure introduce artifacts, and regions in the images captured invalidating the usual assumption of an elliptical model which makes the process of extracting the central passage effectively more difficult. Our approach was designed to cope with these challenges and extract the required image features in a fully automated, accurate, and efficient way using two stages: the first allows to determine a bounding segmentation mask to prevent major leakages from pixels of the cavity area by using a circular region fill that operates as a paint brush followed by Principal Component Analysis with auto correction; the second allows to extract a precise cavity enclosure using a micro-dilation filter and an edge-walking scheme. The accuracy of the algorithm has been tested using 30 computed tomography angiography scans of the lower part of the body containing different degrees of inner wall distortion. The results were compared to manual annotations from a specialist resulting in sensitivity around 98 %, false positive rate around 8 %, and positive predictive value around 93 %. The average execution time was 24 and 18 ms on two types of commodity hardware over sections of 15 cm of length (approx. 1 ms per contour) which makes it more than suitable for use in interactive software applications. Reproducibility tests were also carried out with synthetic images showing no variation for the computed diameters against the theoretical measure. PMID:24197278

  6. MR imaging features of the congenital uterine anomalies

    International Nuclear Information System (INIS)

    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

  7. 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.

  8. Unusual acute encephalitis involving the thalamus: imaging features

    International Nuclear Information System (INIS)

    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

  9. 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.

  10. 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.

  11. Pro duct Image Classification Based on Fusion Features

    Institute of Scientific and Technical Information of China (English)

    YANG Xiao-hui; LIU Jing-jing; YANG Li-jun

    2015-01-01

    Two key challenges raised by a product images classification system are classi-fication precision and classification time. In some categories, classification precision of the latest techniques, in the product images classification system, is still low. In this paper, we propose a local texture descriptor termed fan refined local binary pattern, which captures more detailed information by integrating the spatial distribution into the local binary pattern feature. We compare our approach with different methods on a subset of product images on Amazon/eBay and parts of PI100 and experimental results have demonstrated that our proposed approach is superior to the current existing methods. The highest classification precision is increased by 21%and the average classification time is reduced by 2/3.

  12. 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.

  13. A Robust Technique for Feature-based Image Mosaicing using Image Fusion

    Directory of Open Access Journals (Sweden)

    Vimal Singh Bind, Priya Ranjan Muduli, Umesh Chandra Pati

    2013-03-01

    Full Text Available Since last few decades, image mosaicing in real timeapplications has been a challenging field for imageprocessing experts. It has wide applications in the field ofvideo conferencing, 3D imagereconstruction, satelliteimaging and several medical as well as computer visionfields. In this paper, we have proposed a feature basedimage mosaicing technique using image fusion. Initially,the input images are stitched together using the popularstitching algorithms i.e. Scale Invariant FeatureTransform (SIFT and Speeded-Up Robust Features(SURF. To extract the best features from the stitchingresults, the blending process is done by means of DiscreteWavelet Transform (DWT using the maximum selectionrule for both approximate as well as detail-components.The SIFT provides scale as well as rotational invarianceproperty. The SURF provides better computation speed andillumination invariance. The robustness and quality of theabove mosaicing techniques are tested by meansofthree-dimensionalrotational images.

  14. Feature Based Image Mosaic Using Steerable Filters and Harris Corner Detector

    OpenAIRE

    Mahesh; Subramanyam M .V

    2013-01-01

    Image mosaic is to be combine several views of a scene in to single wide angle view. This paper proposes the feature based image mosaic approach. The mosaic image system includes feature point detection, feature point descriptor extraction and matching. A RANSAC algorithm is applied to eliminate number of mismatches and obtain transformation matrix between the images. The input image is transformed with the correct mapping model for image stitching and same is estimated. In this paper, featur...

  15. Auto-pooling: Learning to Improve Invariance of Image Features from Image Sequences

    OpenAIRE

    Sukhbaatar, Sainbayar; Makino, Takaki; Aihara, Kazuyuki

    2013-01-01

    Learning invariant representations from images is one of the hardest challenges facing computer vision. Spatial pooling is widely used to create invariance to spatial shifting, but it is restricted to convolutional models. In this paper, we propose a novel pooling method that can learn soft clustering of features from image sequences. It is trained to improve the temporal coherence of features, while keeping the information loss at minimum. Our method does not use spatial information, so it c...

  16. Robust feature extraction for character recognition based on binary images

    Science.gov (United States)

    Wang, Lijun; Zhang, Li; Xing, Yuxiang; Wang, Zhiming; Gao, Hewei

    2006-01-01

    Optical Character Recognition (OCR) is a classical research field and has become one of most successful applications in the area of pattern recognition. Feature extraction is a key step in the process of OCR. This paper presents three algorithms for feature extraction based on binary images: the Lattice with Distance Transform (DTL), Stroke Density (SD) and Co-occurrence Matrix (CM). DTL algorithm improves the robustness of the lattice feature by using distance transform to increase the distance of the foreground and background and thus reduce the influence from the boundary of strokes. SD and CM algorithms extract robust stroke features base on the fact that human recognize characters according to strokes, including length and orientation. SD reflects the quantized stroke information including the length and the orientation. CM reflects the length and orientation of a contour. SD and CM together sufficiently describe strokes. Since these three groups of feature vectors complement each other in expressing characters, we integrate them and adopt a hierarchical algorithm to achieve optimal performance. Our methods are tested on the USPS (United States Postal Service) database and the Vehicle License Plate Number Pictures Database (VLNPD). Experimental results shows that the methods gain high recognition rate and cost reasonable average running time. Also, based on similar condition, we compared our results to the box method proposed by Hannmandlu [18]. Our methods demonstrated better performance in efficiency.

  17. 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. PMID:24696801

  18. A bright cyan-excitable orange fluorescent protein facilitates dual-emission microscopy and enhances bioluminescence imaging in vivo.

    Science.gov (United States)

    Chu, Jun; Oh, Younghee; Sens, Alex; Ataie, Niloufar; Dana, Hod; Macklin, John J; Laviv, Tal; Welf, Erik S; Dean, Kevin M; Zhang, Feijie; Kim, Benjamin B; Tang, Clement Tran; Hu, Michelle; Baird, Michelle A; Davidson, Michael W; Kay, Mark A; Fiolka, Reto; Yasuda, Ryohei; Kim, Douglas S; Ng, Ho-Leung; Lin, Michael Z

    2016-07-01

    Orange-red fluorescent proteins (FPs) are widely used in biomedical research for multiplexed epifluorescence microscopy with GFP-based probes, but their different excitation requirements make multiplexing with new advanced microscopy methods difficult. Separately, orange-red FPs are useful for deep-tissue imaging in mammals owing to the relative tissue transmissibility of orange-red light, but their dependence on illumination limits their sensitivity as reporters in deep tissues. Here we describe CyOFP1, a bright, engineered, orange-red FP that is excitable by cyan light. We show that CyOFP1 enables single-excitation multiplexed imaging with GFP-based probes in single-photon and two-photon microscopy, including time-lapse imaging in light-sheet systems. CyOFP1 also serves as an efficient acceptor for resonance energy transfer from the highly catalytic blue-emitting luciferase NanoLuc. An optimized fusion of CyOFP1 and NanoLuc, called Antares, functions as a highly sensitive bioluminescent reporter in vivo, producing substantially brighter signals from deep tissues than firefly luciferase and other bioluminescent proteins. PMID:27240196

  19. 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.

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

    International Nuclear Information System (INIS)

    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. Simultaneous fluorescence and high-resolution bright-field imaging with aberration correction over a wide field-of-view with Fourier ptychographic microscopy (FPM) (Conference Presentation)

    Science.gov (United States)

    Chung, Jaebum; Kim, Jinho; Ou, Xiaoze; Horstmeyer, Roarke; Yang, Changhuei

    2016-03-01

    We present a method to acquire both fluorescence and high-resolution bright-field images with correction for the spatially varying aberrations over a microscope's wide field-of-view (FOV). First, the procedure applies Fourier ptychographic microscopy (FPM) to retrieve the amplitude and phase of a sample, at a resolution that significantly exceeds the cutoff frequency of the microscope objective lens. At the same time, FPM algorithm is able to leverage on the redundancy within the set of acquired FPM bright-field images to estimate the microscope aberrations, which usually deteriorate in regions further away from the FOV's center. Second, the procedure acquires a raw wide-FOV fluorescence image within the same setup. Lack of moving parts allows us to use the FPM-estimated aberration map to computationally correct for the aberrations in the fluorescence image through deconvolution. Overlaying the aberration-corrected fluorescence image on top of the high-resolution bright-field image can be done with accurate spatial correspondence. This can provide means to identifying fluorescent regions of interest within the context of the sample's bright-field information. An experimental demonstration successfully improves the bright-field resolution of fixed, stained and fluorescently tagged HeLa cells by a factor of 4.9, and reduces the error caused by aberrations in a fluorescence image by 31%, over a field of view of 6.2 mm by 9.3 mm. For optimal deconvolution, we show the fluorescence image needs to have a signal-to-noise ratio of ~18.

  2. Scalable High Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning

    OpenAIRE

    Wu, Guorong; Kim, Minjeong; Wang, Qian; Munsell, Brent C.; Shen, Dinggang

    2015-01-01

    Feature selection is a critical step in deformable image registration. In particular, selecting the most discriminative features that accurately and concisely describe complex morphological patterns in image patches improves correspondence detection, which in turn improves image registration accuracy. Furthermore, since more and more imaging modalities are being invented to better identify morphological changes in medical imaging data,, the development of deformable image registration method ...

  3. Automatic archaeological feature extraction from satellite VHR images

    Science.gov (United States)

    Jahjah, Munzer; Ulivieri, Carlo

    2010-05-01

    Archaeological applications need a methodological approach on a variable scale able to satisfy the intra-site (excavation) and the inter-site (survey, environmental research). The increased availability of high resolution and micro-scale data has substantially favoured archaeological applications and the consequent use of GIS platforms for reconstruction of archaeological landscapes based on remotely sensed data. Feature extraction of multispectral remotely sensing image is an important task before any further processing. High resolution remote sensing data, especially panchromatic, is an important input for the analysis of various types of image characteristics; it plays an important role in the visual systems for recognition and interpretation of given data. The methods proposed rely on an object-oriented approach based on a theory for the analysis of spatial structures called mathematical morphology. The term "morphology" stems from the fact that it aims at analysing object shapes and forms. It is mathematical in the sense that the analysis is based on the set theory, integral geometry, and lattice algebra. Mathematical morphology has proven to be a powerful image analysis technique; two-dimensional grey tone images are seen as three-dimensional sets by associating each image pixel with an elevation proportional to its intensity level. An object of known shape and size, called the structuring element, is then used to investigate the morphology of the input set. This is achieved by positioning the origin of the structuring element to every possible position of the space and testing, for each position, whether the structuring element either is included or has a nonempty intersection with the studied set. The shape and size of the structuring element must be selected according to the morphology of the searched image structures. Other two feature extraction techniques were used, eCognition and ENVI module SW, in order to compare the results. These techniques were

  4. Secondary ovarian neoplasms in children: imaging features with histopathologic correlation

    Energy Technology Data Exchange (ETDEWEB)

    McCarville, M.B. [Dept. of Diagnostic Imaging, St. Jude Children' s Research Hospital, Memphis, TN (United States); Hill, D.A. [Dept. of Pathology, St. Jude Children' s Research Hospital, Memphis, TN (United States); Miller, B.E. [Dept. of Obstetrics and Gynecology, Univ. of Tennessee, Memphis (United States); Pratt, C.B. [Dept. of Hematology-Oncology, St. Jude Children' s Research Hospital, Memphis (United States)

    2001-05-01

    Background. Although the pathologic features and imaging appearance of childhood primary ovarian neoplasms have been well described, little information is available about the malignancies that may secondarily involve the ovary. Objective. To determine the relationship between the imaging features and the histopathology of secondary ovarian neoplasms in children treated at our institution. Materials and methods. We searched our institutional database for codes indicating metastatic ovarian disease. Of the 35 patients with such codes, 18 had pathologically proven secondary ovarian disease. From their medical records we recorded demographic data, presenting symptoms, and evidence of endocrine dysfunction. We reviewed the pre-oophorectomy imaging and the subsequent pathologic specimens. Results. One-third of the patients had bilateral pelvic masses; another third had large masses indistinguishable from the ovaries. Twelve (67 %) had either ascites, peritoneal implants, matted bowel, adenopathy, pleural effusions, or some combination of these. Five (28 %) had other metastatic disease. Primary tumors included colon adenocarcinoma (9), Burkitt's lymphoma (3), alveolar rhabdomyosarcoma (3), Wilms' tumor (1), neuroblastoma (1), and retinoblastoma (1). Conclusion. Although rare, secondary ovarian tumors should be considered in the differential diagnosis of children with ovarian masses. Bilateral ovarian masses or large masses indistinguishable from the ovaries, particularly in the presence of other metastatic foci, may help distinguish primary from secondary ovarian malignancies. (orig.)

  5. Secondary ovarian neoplasms in children: imaging features with histopathologic correlation

    International Nuclear Information System (INIS)

    Background. Although the pathologic features and imaging appearance of childhood primary ovarian neoplasms have been well described, little information is available about the malignancies that may secondarily involve the ovary. Objective. To determine the relationship between the imaging features and the histopathology of secondary ovarian neoplasms in children treated at our institution. Materials and methods. We searched our institutional database for codes indicating metastatic ovarian disease. Of the 35 patients with such codes, 18 had pathologically proven secondary ovarian disease. From their medical records we recorded demographic data, presenting symptoms, and evidence of endocrine dysfunction. We reviewed the pre-oophorectomy imaging and the subsequent pathologic specimens. Results. One-third of the patients had bilateral pelvic masses; another third had large masses indistinguishable from the ovaries. Twelve (67 %) had either ascites, peritoneal implants, matted bowel, adenopathy, pleural effusions, or some combination of these. Five (28 %) had other metastatic disease. Primary tumors included colon adenocarcinoma (9), Burkitt's lymphoma (3), alveolar rhabdomyosarcoma (3), Wilms' tumor (1), neuroblastoma (1), and retinoblastoma (1). Conclusion. Although rare, secondary ovarian tumors should be considered in the differential diagnosis of children with ovarian masses. Bilateral ovarian masses or large masses indistinguishable from the ovaries, particularly in the presence of other metastatic foci, may help distinguish primary from secondary ovarian malignancies. (orig.)

  6. A laboratory 8 keV transmission full-field x-ray microscope with a polycapillary as condenser for bright and dark field imaging

    Energy Technology Data Exchange (ETDEWEB)

    Baumbach, S., E-mail: baumbach@rheinahrcampus.de; Wilhein, T. [Institute for X-Optics, University of Applied Sciences Koblenz, RheinAhrCampus Remagen, Joseph-Rovan-Allee 2, D-53424 Remagen (Germany); Kanngießer, B.; Malzer, W. [Institute for Optics and Atomic Physics, Technical University of Berlin, Hardenbergstrasse 36, D-10623 Berlin (Germany); Stiel, H. [Max-Born-Institute, Max-Born-Strasse 2A, D-12489 Berlin (Germany)

    2015-08-15

    This article introduces a laboratory setup of a transmission full-field x-ray microscope at 8 keV photon energy. The microscope operates in bright and dark field imaging mode with a maximum field of view of 50 μm. Since the illumination geometry determines whether the sample is illuminated homogeneously and moreover, if different imaging methods can be applied, the condenser optic is one of the most significant parts. With a new type of x-ray condenser, a polycapillary optic, we realized bright field imaging and for the first time dark field imaging at 8 keV photon energy in a laboratory setup. A detector limited spatial resolution of 210 nm is measured on x-ray images of Siemens star test patterns.

  7. 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

  8. Nanoscopy—imaging life at the nanoscale: a Nobel Prize achievement with a bright future

    Science.gov (United States)

    Blom, Hans; Bates, Mark

    2015-10-01

    A grand scientific prize was awarded last year to three pioneering scientists, for their discovery and development of molecular ‘ON-OFF’ switching which, when combined with optical imaging, can be used to see the previously invisible with light microscopy. The Royal Swedish Academy of Science announced on October 8th their decision and explained that this achievement—rooted in physics and applied in biology and medicine—was awarded with the Nobel Prize in Chemistry for controlling fluorescent molecules to create images of specimens smaller than anything previously observed with light. The story of how this noble switch in optical microscopy was achieved and how it was engineered to visualize life at the nanoscale is highlighted in this invited comment.

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

    OpenAIRE

    Ya-Shuo Li; Yilong Yin; Gongping Yang; Ying Li

    2012-01-01

    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, w...

  10. A route to brightly fluorescent carbon nanotubes for near-infrared imaging in mice

    OpenAIRE

    Welsher, Kevin; Liu, Zhuang; Sarah P Sherlock; Robinson, Joshua Tucker; Chen, Zhuo; Daranciang, Dan; Dai, Hongjie

    2009-01-01

    The near-infrared photoluminescence intrinsic to semiconducting single-walled carbon nanotubes is ideal for biological imaging owing to the low autofluorescence and deep tissue penetration in the near-infrared region beyond 1 µm. However, biocompatible single-walled carbon nanotubes with high quantum yield have been elusive. Here, we show that sonicating single-walled carbon nanotubes with sodium cholate, followed by surfactant exchange to form phospholipid–polyethylene glycol coated nanotube...

  11. 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. PMID:26114849

  12. Bilateral cystic neuroblastoma: imaging features and differential diagnoses

    International Nuclear Information System (INIS)

    Neuroblastoma is one of the most common malignant tumors of childhood, with 40 % arising in the adrenal glands. Bilateral adrenal involvement from synchronous development or metastatic spread of the tumor is seen in less than 10 % of children with neuroblastoma [1[. Neuroblastoma rarely presents as a cystic suprarenal mass that is difficult to differentiate from adrenal hemorrhage, extralobar sequestration, or dilated upper-pole renal calyces. To our knowledge, bilateral cystic neuroblastoma has not been previously reported. We present a case of bilateral cystic adrenal neuroblastoma to demonstrate the imaging features of this unusual entity, and to expand the differential diagnosis of bilateral cystic suprarenal masses in an infant. (orig.). With 2 figs

  13. Aggressive primary thyroid lymphoma: imaging features of two elderly patients

    Directory of Open Access Journals (Sweden)

    Eu Hyun Kim

    2014-10-01

    Full Text Available

    We report two cases of aggressive thyroid lymphoma in elderly patients that presented as Epub ahead of print large infiltrative thyroid masses with extensive invasion to adjacent structures including trachea, esophagus, and common carotid artery. Ultrasonography displayed irregular shaped, heterogeneous hypoechoic mass, mimicking anaplastic carcinoma. Computed tomography showed heterogeneously enhancing mass compared to surrounding muscles without calcification and hemorrhage. After biopsy, the masses were histopathologically diagnosed as lymphoma. Aggressive primary thyroid lymphoma is rare; therefore, here we report its image features, with emphasis on ultrasonographic findings, and discuss its differential diagnosis.

  14. Aggressive primary thyroid lymphoma: imaging features of two elderly patients

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Eu Hyun; Kim, Jee Young; Kim, Tae Jung [Yeouido St. Mary' s Hospital, The Catholic University College of Medicine, Seoul (Korea, Republic of)

    2014-12-15

    We report two cases of aggressive thyroid lymphoma in elderly patients that presented as Epub ahead of print large infiltrative thyroid masses with extensive invasion to adjacent structures including trachea, esophagus, and common carotid artery. Ultrasonography displayed irregular shaped, heterogeneous hypoechoic mass, mimicking anaplastic carcinoma. Computed tomography showed heterogeneously enhancing mass compared to surrounding muscles without calcification and hemorrhage. After biopsy, the masses were histopathologically diagnosed as lymphoma. Aggressive primary thyroid lymphoma is rare; therefore, here we report its image features, with emphasis on ultrasonographic findings, and discuss its differential diagnosis.

  15. Aggressive primary thyroid lymphoma: imaging features of two elderly patients

    International Nuclear Information System (INIS)

    We report two cases of aggressive thyroid lymphoma in elderly patients that presented as Epub ahead of print large infiltrative thyroid masses with extensive invasion to adjacent structures including trachea, esophagus, and common carotid artery. Ultrasonography displayed irregular shaped, heterogeneous hypoechoic mass, mimicking anaplastic carcinoma. Computed tomography showed heterogeneously enhancing mass compared to surrounding muscles without calcification and hemorrhage. After biopsy, the masses were histopathologically diagnosed as lymphoma. Aggressive primary thyroid lymphoma is rare; therefore, here we report its image features, with emphasis on ultrasonographic findings, and discuss its differential diagnosis.

  16. Random projections based feature-specific structured imaging.

    Science.gov (United States)

    Baheti, Pawan K; Neifeld, Mark A

    2008-02-01

    We present a feature-specific imaging system based on the use of structured illumination. The measurements are defined as inner products between the illumination patterns and the object reflectance function, measured on a single photodetector. The illumination patterns are defined using random binary patterns and thus do not employ prior knowledge about the object. Object estimates are generated using L(1)-norm minimization and gradient-projection sparse reconstruction algorithms. The experimental reconstructions show the feasibility of the proposed approach by using 42% fewer measurements than the object dimensionality. PMID:18542256

  17. MR imaging features of chronically torn anterior cruciate ligament

    Energy Technology Data Exchange (ETDEWEB)

    Niitsu, Mamoru; Kuramochi, Masashi; Ikeda, Kotaroh; Fukubayashi, Tohru; Anno, Izumi; Itai, Yuji [Tsukuba Univ., Ibaraki (Japan). Inst. of Clinical Medicine

    1995-06-01

    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{sup *}-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).

  18. MR imaging features of chronically torn anterior cruciate ligament

    International Nuclear Information System (INIS)

    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)

  19. Super-resolved 3-D imaging of live cells organelles from bright-field photon transmission micrographs

    CERN Document Server

    Rychtarikova, Renata; Shi, Kevin; Malakhova, Daria; Machacek, Petr; Smaha, Rebecca; Urban, Jan; Stys, Dalibor

    2016-01-01

    Current biological and medical research is aimed at obtaining a detailed spatiotemporal map of a live cell's interior to describe and predict cell's physiological state. We present here an algorithm for complete 3-D modelling of cellular structures from a z-stack of images obtained using label-free wide-field bright-field light-transmitted microscopy. The method visualizes 3-D objects with a volume equivalent to the area of a camera pixel multiplied by the z-height. The computation is based on finding pixels of unchanged intensities between two consecutive images of an object spread function. These pixels represent strongly light-diffracting, light-absorbing, or light-emitting objects. To accomplish this, variables derived from R\\'{e}nyi entropy are used to suppress camera noise. Using this algorithm, the detection limit of objects is only limited by the technical specifications of the microscope setup--we achieve the detection of objects of the size of one camera pixel. This method allows us to obtain 3-D re...

  20. VLBI observations of bright AGN jets with KVN and VERA Array (KaVA): Evaluation of Imaging Capability

    CERN Document Server

    Niinuma, Kotaro; Kino, Motoki; Sohn, Bong Won; Akiyama, Kazunori; Zhao, Guang-Yao; Sawada-Satoh, Satoko; Trippe, Sascha; Hada, Kazuhiro; Jung, Taehyun; Hagiwara, Yoshiaki; Dodson, Richard; Koyama, Shoko; Honma, Mareki; Nagai, Hiroshi; Chung, Aeree; Doi, Akihiro; Fujisawa, Kenta; Han, Myoung-Hee; Kim, Joeng-Sook; Lee, Jeewon; Lee, Jeong Ae; Miyazaki, Atsushi; Oyama, Tomoaki; Sorai, Kazuo; Wajima, Kiyoaki; Bae, Jaehan; Byun, Do-Young; Cho, Se-Hyung; Choi, Yoon Kyung; Chung, Hyunsoo; Chung, Moon-Hee; Han, Seog-Tae; Hirota, Tomoya; Hwang, Jung-Wook; Je, Do-Heung; Jike, Takaaki; Jung, Dong-Kyu; Jung, Jin-Seung; Kang, Ji-Hyun; Kang, Jiman; Kang, Yong-Woo; Kan-ya, Yukitoshi; Kanaguchi, Masahiro; Kawaguchi, Noriyuki; Kim, Bong Gyu; Kim, Hyo Ryoung; Kim, Hyun-Goo; Kim, Jaeheon; Kim, Jongsoo; Kim, Kee-Tae; Kim, Mikyoung; Kobayashi, Hideyuki; Kono, Yusuke; Kurayama, Tomoharu; Lee, Changhoon; Lee, Jung-Won; Lee, Sang Hyun; Minh, Young Chol; Matsumoto, Naoko; Nakagawa, Akiharu; Oh, Chung Sik; Oh, Se-Jin; Park, Sun-Youp; Roh, Duk-Gyoo; Sasao, Tetsuo; Shibata, Katsunori M; Song, Min-Gyu; Tamura, Yoshiaki; Wi, Seog-Oh; Yeom, Jae-Hwan; Yun, Young Joo

    2014-01-01

    The Korean very-long-baseline interferometry (VLBI) network (KVN) and VLBI Exploration of Radio Astrometry (VERA) Array (KaVA) is the first international VLBI array dedicated to high-frequency (23 and 43 GHz bands) observations in East Asia. Here, we report the first imaging observations of three bright active galactic nuclei (AGNs) known for their complex morphologies: 4C 39.25, 3C 273, and M 87. This is one of the initial result of KaVA early science. Our KaVA images reveal extended outflows with complex substructure such as knots and limb brightening, in agreement with previous Very Long Baseline Array (VLBA) observations. Angular resolutions are better than 1.4 and 0.8 milliarcsecond at 23 GHz and 43 GHz, respectively. KaVA achieves a high dynamic range of ~1000, more than three times the value achieved by VERA. We conclude that KaVA is a powerful array with a great potential for the study of AGN outflows, at least comparable to the best existing radio interferometric arrays.

  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. CT and MR imaging features in patients with intracranial dolichoectasia

    International Nuclear Information System (INIS)

    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

  3. Performance Characterization of Image Feature Detectors in Relation to the Scene Content Utilizing a Large Image Database

    OpenAIRE

    Ferrarini, Bruno; Ehsan, Shoaib; Rehman, Naveed Ur; McDonald-Maier, Klaus D.

    2015-01-01

    Selecting the most suitable local invariant feature detector for a particular application has rendered the task of evaluating feature detectors a critical issue in vision research. No state-of-the-art image feature detector works satisfactorily under all types of image transformations. Although the literature offers a variety of comparison works focusing on performance evaluation of image feature detectors under several types of image transformation, the influence of the scene content on the ...

  4. 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.

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

    International Nuclear Information System (INIS)

    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.)

  6. Clinical feature and imaging findings of juvenile ankylosing spondylitis

    International Nuclear Information System (INIS)

    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

  7. Medical image analysis of 3D CT images based on extensions of Haralick texture features

    Czech Academy of Sciences Publication Activity Database

    Tesař, Ludvík; Shimizu, A.; Smutek, D.; Kobatake, H.; Nawano, S.

    2008-01-01

    Roč. 32, č. 6 (2008), s. 513-520. ISSN 0895-6111 R&D Projects: GA AV ČR 1ET101050403; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : image segmentation * Gaussian mixture model * 3D image analysis Subject RIV: IN - Informatics, Computer Science Impact factor: 1.192, year: 2008 http://library.utia.cas.cz/separaty/2008/AS/tesar-medical image analysis of 3d ct image s based on extensions of haralick texture features.pdf

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

    International Nuclear Information System (INIS)

    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. Clinical and imaging features of neonatal chlamydial pneumonia

    International Nuclear Information System (INIS)

    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)

  10. Spectral Characterization of Bright Materials on Vesta

    Science.gov (United States)

    Capaccioni, Fabrizio; DeSanctis, M. C.; Ammannito, E.; Li, Jian-Yang; Longobardo, A.; Mittlefehldt, David W.; Palomba, E.; Pieters, C. M.; Schroeder, S. E.; Tosi, F.; Hiesinger, H.; Blewett, D. T.; Russell, C. T.; Raymond, C. A.

    2012-01-01

    The surface of Vesta, as observed by the camera and imaging spectrometer onboard the Dawn spacecraft, displays large surface diversity in terms of its geology and mineralogy with noticeably dark and bright areas on the surface often associated with various geological features and showing remarkably different forms. Here we report our initial attempt to spectrally characterize the areas that are distinctively brighter than their surroundings.

  11. Probing the bright radio flare and afterglow of GRB 130427A with the Arcminute Microkelvin Imager

    Science.gov (United States)

    Anderson, G. E.; van der Horst, A. J.; Staley, T. D.; Fender, R. P.; Wijers, R. A. M. J.; Scaife, A. M. M.; Rumsey, C.; Titterington, D. J.; Rowlinson, A.; Saunders, R. D. E.

    2014-05-01

    We present one of the best sampled early-time light curves of a gamma-ray burst (GRB) at radio wavelengths. Using the Arcminute Mircrokelvin Imager (AMI), we observed GRB 130427A at the central frequency of 15.7 GHz between 0.36 and 59.32 d post-burst. These results yield one of the earliest radio detections of a GRB and demonstrate a clear rise in flux less than one day after the γ-ray trigger followed by a rapid decline. This early-time radio emission probably originates in the GRB reverse shock so our AMI light curve reveals the first ever confirmed detection of a reverse shock peak in the radio domain. At later times (about 3.2 d post-burst), the rate of decline decreases, indicating that the forward shock component has begun to dominate the light curve. Comparisons of the AMI light curve with modelling conducted by Perley et al. show that the most likely explanation of the early-time 15.7 GHz peak is caused by the self-absorption turn-over frequency, rather than the peak frequency, of the reverse shock moving through the observing bands.

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

    International Nuclear Information System (INIS)

    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.)

  13. 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.)

  14. SOFT COMPUTING BASED MEDICAL IMAGE RETRIEVAL USING SHAPE AND TEXTURE FEATURES

    Directory of Open Access Journals (Sweden)

    M. Mary Helta Daisy

    2014-01-01

    Full Text Available Image retrieval is a challenging and important research applications like digital libraries and medical image databases. Content-based image retrieval is useful in retrieving images from database based on the feature vector generated with the help of the image features. In this study, we present image retrieval based on the genetic algorithm. The shape feature and morphological based texture features are extracted images in the database and query image. Then generating chromosome based on the distance value obtained by the difference feature vector of images in the data base and the query image. In the selected chromosome the genetic operators like cross over and mutation are applied. After that the best chromosome selected and displays the most similar images to the query image. The retrieval performance of the method shows better retrieval result.

  15. Robust Colour Image Watermarking Scheme Based on Feature Points and Image Normalization in DCT Domain

    Directory of Open Access Journals (Sweden)

    Ibrahim Alsonosi Nasir

    2014-04-01

    Full Text Available Geometric attacks can desynchronize the location of the watermark and hence cause incorrect watermark detection. This paper presents a robust c olour image watermarking scheme based on visually significant feature points and image norma lization technique. The feature points are used as synchronization marks between watermark emb edding and detection. The watermark is embedded into the non overlapped normalized circula r regions in the luminance component or the blue component of a color image. The embedding of the watermark is carried out by modifying the DCT coefficients values in selected b locks. The original unmarked image is not required for watermark extraction Experimental results show that the proposed scheme successfully makes the watermark perceptually invis ible as well as robust to common signal processing and geometric attacks.

  16. Hurricane Imaging Radiometer (HIRAD) Observations of Brightness Temperatures and Ocean Surface Wind Speed and Rain Rate During NASA's GRIP and HS3 Campaigns

    Science.gov (United States)

    Miller, Timothy L.; James, M. W.; Roberts, J. B.; Jones, W. L.; Biswas, S.; Ruf, C. S.; Uhlhorn, E. W.; Atlas, R.; Black, P.; Albers, C.

    2012-01-01

    HIRAD flew on high-altitude aircraft over Earl and Karl during NASA s GRIP (Genesis and Rapid Intensification Processes) campaign in August - September of 2010, and plans to fly over Atlantic tropical cyclones in September of 2012 as part of the Hurricane and Severe Storm Sentinel (HS3) mission. HIRAD is a new C-band radiometer using a synthetic thinned array radiometer (STAR) technology to obtain spatial resolution of approximately 2 km, out to roughly 30 km each side of nadir. By obtaining measurements of emissions at 4, 5, 6, and 6.6 GHz, observations of ocean surface wind speed and rain rate can be retrieved. The physical retrieval technique has been used for many years by precursor instruments, including the Stepped Frequency Microwave Radiometer (SFMR), which has been flying on the NOAA and USAF hurricane reconnaissance aircraft for several years to obtain observations within a single footprint at nadir angle. Results from the flights during the GRIP and HS3 campaigns will be shown, including images of brightness temperatures, wind speed, and rain rate. Comparisons will be made with observations from other instruments on the campaigns, for which HIRAD observations are either directly comparable or are complementary. Features such as storm eye and eye-wall, location of storm wind and rain maxima, and indications of dynamical features such as the merging of a weaker outer wind/rain maximum with the main vortex may be seen in the data. Potential impacts on operational ocean surface wind analyses and on numerical weather forecasts will also be discussed.

  17. CT imaging features of tuberculous spondylitis in children

    International Nuclear Information System (INIS)

    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=0.0010.05). 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

  18. Magnetic Resonance Imaging and DWI Features of Orbital Rhabdomyosarcoma

    Institute of Scientific and Technical Information of China (English)

    Xuetao Mu; Hong Wang; Yueyue Li; Yuwen Hao; Chunnan Wu; Lin Ma

    2014-01-01

    Purpose:.To describe the magnetic resonance imaging (MRI) features of orbital rhabdomyosarcoma (RMS). Methods:.Thirty-nine patients with histopathologically con-firmed orbital RMS were retrospectively reviewed. All patients underwent orbital conventional MRI, including axial,.sagittal, and coronal T1-weighted,.T2-weighted,.and postcontrast T1-weighted sequences. The location, shape, margin, and MRI signal of the 39 lesions were reviewed..DWI in 15 patients and susceptibility weighted imaging (SWI) in 2 patients were also analyzed. Results:.Orbital MRI was available in 39 patients and re-vealed a soft tissue mass in the orbital region in all cases..Of the 39 patients,.the primary tumor sites were limited to the orbital proper in 31 cases, while 28 cases had extraocular muscle invasion and 8 cases had extraorbital invasion..All le-sions were unilateral..Thirty-three cases were well-defined soft tissue masses and 6 cases appeared as less well-defined soft-tissue masses..Thirty-four cases showed homogeneous isoin-tense or slightly hypointense signals on T1-weighted imaging (T1WI) and hyperintense signal on T2-weighted imaging (T2WI) compared with extraocular muscles. Five cases had heterogeneous signals with focal areas of increased signal on T1WI or decreased signal on T2WI, including 1 case with hy-pointense signal on SWI..The mean apparent diffusion coeffi-cient (ADC) value of the viable part of tumors was (0.925 ± 0.09)×10-3 mm2/s. All cases showed moderate to marked en-hancement after contrast administration. Conclusion:Several MRI features-including homogeneous isointense or slightly hypointense signal on T1WI and slightly hyperintense signal on T2WI, relative low ADC values, and moderate to marked enhancement,.extraocular muscles inva-sion, and extraorbital extensionare helpful in the diagnosis of orbital RMS. (Eye Science 2014; 29:6-11).

  19. 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.

  20. Imaging trace element distributions in single organelles and subcellular features

    Science.gov (United States)

    Kashiv, Yoav; Austin, Jotham R.; Lai, Barry; Rose, Volker; Vogt, Stefan; El-Muayed, Malek

    2016-02-01

    The distributions of chemical elements within cells are of prime importance in a wide range of basic and applied biochemical research. An example is the role of the subcellular Zn distribution in Zn homeostasis in insulin producing pancreatic beta cells and the development of type 2 diabetes mellitus. We combined transmission electron microscopy with micro- and nano-synchrotron X-ray fluorescence to image unequivocally for the first time, to the best of our knowledge, the natural elemental distributions, including those of trace elements, in single organelles and other subcellular features. Detected elements include Cl, K, Ca, Co, Ni, Cu, Zn and Cd (which some cells were supplemented with). Cell samples were prepared by a technique that minimally affects the natural elemental concentrations and distributions, and without using fluorescent indicators. It could likely be applied to all cell types and provide new biochemical insights at the single organelle level not available from organelle population level studies.

  1. Feature-based imaging system: The Peach Bottom field trials

    International Nuclear Information System (INIS)

    Feature-based systems that combine imaging and signal analysis capabilities may be useful for nondestructive evaluation (NDE) of plant components. This report describes the field evaluation of an integrated system at a plant site during a scheduled outage for pipe weld examination to discriminate intergranular stress corrosion cracking (IGCSS) from benign, geometrical reflectors. The integrated system consisted of a personal computer (PC)-based system capable of detailed analysis of ultrasonic signal data and an in-service inspection (ISI) imaging system used in many commercial pipe examinations for IGSCC. The integrated system was trained to discriminate automatically IGSCC from other reflectors using EPRI NDE Center's inventory of field-removed samples. The methods and results of this training are described. Several classifiers were synthesized using mathematical features derived from signals that were collected to simulate field conditions. Data collection procedures were developed that required minimal operator training. Field data were collected and analyzed before and after pipe decontamination prior to pipe replacement. Automatic decision maps were generated for easier interpretation and comparison. The field trial was conducted in October 1987--January 1988. Select pipe specimens were decontaminated and shipped to a contractor's facility for detailed metallurgical and dye penetrant analysis. A comparison between reflector calls from the ultrasonic data and penetrant test results are provided in the final section. As a basis for comparison, the performance of the automated system was compared with manual calls. The automated technique results were better than manual; although both were well below acceptable standards as defined for IGSCC qualification. 2 refs., 174 figs., 10 tabs

  2. Synovial sarcoma: dynamic contrast-enhanced MR imaging features

    Energy Technology Data Exchange (ETDEWEB)

    Rijswijk, C.S.P. van; Bloem, J.L. [Rijksuniversiteit Leiden (Netherlands). Dept. of Diagnostic Radiology; Hogendoorn, P.C.W. [Dept. of Pathology, Leiden Univ. Medical Center (Netherlands); Taminiau, A.H.M. [Dept. of Orthopedic Surgery, Leiden Univ. Medical Center (Netherlands)

    2001-01-01

    Objective. To determine whether previously described so-called malignant dynamic contrast-enhanced magnetic resonance (MR) imaging features - early start, peripheral enhancement and early plateau or washout phase - occur consistently in synovial sarcoma.Design and patients. Dynamic contrast-enhanced MR images of 10 patients with histologically proven synovial sarcoma were reviewed. The start, pattern and progression of tumor enhancement were assessed and correlated with histopathology.Results. In all patients, the time interval between arterial and early tumor enhancement was less than 7 s (mean 4.40 s, SD 2.09 s). Six synovial sarcomas showed enhancement with a subsequent rapidly progressive linear increase in signal intensity followed by a plateau in one lesion and washout in five. Four lesions showed a late sustained increase in enhancement after the initial rapid increase in enhancement. The pattern of initial enhancement was peripheral in only two lesions, diffuse in four and heterogeneous in four lesions.Conclusions. Enhancement of tumor within 7 s after arterial enhancement is, of the three parameters described previously, the only sign that occurs consistently in synovial sarcoma. (orig.)

  3. Synovial sarcoma: dynamic contrast-enhanced MR imaging features

    International Nuclear Information System (INIS)

    Objective. To determine whether previously described so-called malignant dynamic contrast-enhanced magnetic resonance (MR) imaging features - early start, peripheral enhancement and early plateau or washout phase - occur consistently in synovial sarcoma.Design and patients. Dynamic contrast-enhanced MR images of 10 patients with histologically proven synovial sarcoma were reviewed. The start, pattern and progression of tumor enhancement were assessed and correlated with histopathology.Results. In all patients, the time interval between arterial and early tumor enhancement was less than 7 s (mean 4.40 s, SD 2.09 s). Six synovial sarcomas showed enhancement with a subsequent rapidly progressive linear increase in signal intensity followed by a plateau in one lesion and washout in five. Four lesions showed a late sustained increase in enhancement after the initial rapid increase in enhancement. The pattern of initial enhancement was peripheral in only two lesions, diffuse in four and heterogeneous in four lesions.Conclusions. Enhancement of tumor within 7 s after arterial enhancement is, of the three parameters described previously, the only sign that occurs consistently in synovial sarcoma. (orig.)

  4. The imaging feature of multidrug-resistant tuberculosis

    International Nuclear Information System (INIS)

    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)

  5. Covert photo classification by fusing image features and visual attributes.

    Science.gov (United States)

    Lang, Haitao; Ling, Haibin

    2015-10-01

    In this paper, we study a novel problem of classifying covert photos, whose acquisition processes are intentionally concealed from the subjects being photographed. Covert photos are often privacy invasive and, if distributed over Internet, can cause serious consequences. Automatic identification of such photos, therefore, serves as an important initial step toward further privacy protection operations. The problem is, however, very challenging due to the large semantic similarity between covert and noncovert photos, the enormous diversity in the photographing process and environment of cover photos, and the difficulty to collect an effective data set for the study. Attacking these challenges, we make three consecutive contributions. First, we collect a large data set containing 2500 covert photos, each of them is verified rigorously and carefully. Second, we conduct a user study on how humans distinguish covert photos from noncovert ones. The user study not only provides an important evaluation baseline, but also suggests fusing heterogeneous information for an automatic solution. Our third contribution is a covert photo classification algorithm that fuses various image features and visual attributes in the multiple kernel learning framework. We evaluate the proposed approach on the collected data set in comparison with other modern image classifiers. The results show that our approach achieves an average classification rate (1-EER) of 0.8940, which significantly outperforms other competitors as well as human's performance. PMID:25966474

  6. Basic features and noise sensitivity of magnetotelluric invariant images

    International Nuclear Information System (INIS)

    domains. Based on the phase tensor imaging features, it was possible to estimate the maximum depth extension of the Middle-Hungarian tectonic line.

  7. Automated Image Retrieval of Chest CT Images Based on Local Grey Scale Invariant Features.

    Science.gov (United States)

    Arrais Porto, Marcelo; Cordeiro d'Ornellas, Marcos

    2015-01-01

    Textual-based tools are regularly employed to retrieve medical images for reading and interpretation using current retrieval Picture Archiving and Communication Systems (PACS) but pose some drawbacks. All-purpose content-based image retrieval (CBIR) systems are limited when dealing with medical images and do not fit well into PACS workflow and clinical practice. This paper presents an automated image retrieval approach for chest CT images based local grey scale invariant features from a local database. Performance was measured in terms of precision and recall, average retrieval precision (ARP), and average retrieval rate (ARR). Preliminary results have shown the effectiveness of the proposed approach. The prototype is also a useful tool for radiology research and education, providing valuable information to the medical and broader healthcare community. PMID:26262345

  8. Feature Based Image Mosaic Using Steerable Filters and Harris Corner Detector

    Directory of Open Access Journals (Sweden)

    Mahesh

    2013-05-01

    Full Text Available Image mosaic is to be combine several views of a scene in to single wide angle view. This paper proposes the feature based image mosaic approach. The mosaic image system includes feature point detection, feature point descriptor extraction and matching. A RANSAC algorithm is applied to eliminate number of mismatches and obtain transformation matrix between the images. The input image is transformed with the correct mapping model for image stitching and same is estimated. In this paper, feature points are detected using steerable filters and Harris, and compared with traditional Harris, KLT, and FAST corner detectors.

  9. Application of image visual characterization and soft feature selection in content-based image retrieval

    Science.gov (United States)

    Jarrah, Kambiz; Kyan, Matthew; Lee, Ivan; Guan, Ling

    2006-01-01

    Fourier descriptors (FFT) and Hu's seven moment invariants (HSMI) are among the most popular shape-based image descriptors and have been used in various applications, such as recognition, indexing, and retrieval. In this work, we propose to use the invariance properties of Hu's seven moment invariants, as shape feature descriptors, for relevance identification in content-based image retrieval (CBIR) systems. The purpose of relevance identification is to find a collection of images that are statistically similar to, or match with, an original query image from within a large visual database. An automatic relevance identification module in the search engine is structured around an unsupervised learning algorithm, the self-organizing tree map (SOTM). In this paper we also proposed a new ranking function in the structure of the SOTM that exponentially ranks the retrieved images based on their similarities with respect to the query image. Furthermore, we propose to extend our studies to optimize the contribution of individual feature descriptors for enhancing the retrieval results. The proposed CBIR system is compatible with the different architectures of other CBIR systems in terms of its ability to adapt to different similarity matching algorithms for relevance identification purposes, whilst offering flexibility of choice for alternative optimization and weight estimation techniques. Experimental results demonstrate the satisfactory performance of the proposed CBIR system.

  10. Unsupervised Multi-Feature Tag Relevance Learning for Social Image Retrieval

    OpenAIRE

    Li, X; Snoek, C.G.M.; Worring, M.

    2010-01-01

    Interpreting the relevance of a user-contributed tag with respect to the visual content of an image is an emerging problem in social image retrieval. In the literature this problem is tackled by analyzing the correlation between tags and images represented by specific visual features. Unfortunately, no single feature represents the visual content completely, e.g., global features are suitable for capturing the gist of scenes, while local features are better for depicting objects. To solve the...

  11. Content-Based Medical Image Retrieval Based on Image Feature Projection in Relevance Feedback Level

    Directory of Open Access Journals (Sweden)

    Mohammad Behnam

    2014-04-01

    Full Text Available The purpose of this study is to design a content-based medical image retrieval system and provide a new method to reduce semantic gap between visual features and semantic concepts. Generally performance of the retrieval systems based on only visual contents decrease because these features often fail to describe the high level semantic concepts in user’s mind. In this paper this problem is solved using a new approach based on projection of relevant and irrelevant images in to a new space with low dimensionality and less overlapping in relevance feedback level. For this purpose, first we change the feature space using Principal Component Analysis (PCA and Linear Discriminant Analysis (LDA techniques and then classify the feedback images applying Support Vector Machine (SVM classifier. The proposed framework has been evaluated on a database consisting of 10,000 medical X-ray images of 57 semantic classes. The obtained results show that the proposed approach significantly improves the accuracy of retrieval system.

  12. Content-Based Medical Image Retrieval Based on Image Feature Projection in Relevance Feedback Level

    Directory of Open Access Journals (Sweden)

    Mohammad Behnam

    2014-09-01

    Full Text Available The purpose of this study is to design a content-based medical image retrieval system and provide a new method to reduce semantic gap between visual features and semantic concepts. Generally performance of the retrieval systems based on only visual contents decrease because these features often fail to describe the high level semantic concepts in user’s mind. In this paper this problem is solved using a new approach based on projection of relevant and irrelevant images in to a new space with low dimensionality and less overlapping in relevance feedback level. For this purpose, first we change the feature space using Principal Component Analysis (PCA and Linear Discriminant Analysis (LDA techniques and then classify the feedback images applying Support Vector Machine (SVM classifier. The proposed framework has been evaluated on a database consisting of 10,000 medical X-ray images of 57 semantic classes. The obtained results show that the proposed approach significantly improves the accuracy of retrieval system.

  13. Scalable High-Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning.

    Science.gov (United States)

    Wu, Guorong; Kim, Minjeong; Wang, Qian; Munsell, Brent C; Shen, Dinggang

    2016-07-01

    Feature selection is a critical step in deformable image registration. In particular, selecting the most discriminative features that accurately and concisely describe complex morphological patterns in image patches improves correspondence detection, which in turn improves image registration accuracy. Furthermore, since more and more imaging modalities are being invented to better identify morphological changes in medical imaging data, the development of deformable image registration method that scales well to new image modalities or new image applications with little to no human intervention would have a significant impact on the medical image analysis community. To address these concerns, a learning-based image registration framework is proposed that uses deep learning to discover compact and highly discriminative features upon observed imaging data. Specifically, the proposed feature selection method uses a convolutional stacked autoencoder to identify intrinsic deep feature representations in image patches. Since deep learning is an unsupervised learning method, no ground truth label knowledge is required. This makes the proposed feature selection method more flexible to new imaging modalities since feature representations can be directly learned from the observed imaging data in a very short amount of time. Using the LONI and ADNI imaging datasets, image registration performance was compared to two existing state-of-the-art deformable image registration methods that use handcrafted features. To demonstrate the scalability of the proposed image registration framework, image registration experiments were conducted on 7.0-T brain MR images. In all experiments, the results showed that the new image registration framework consistently demonstrated more accurate registration results when compared to state of the art. PMID:26552069

  14. Segmentation and classification of medical images using texture-primitive features: Application of BAM-type artificial neural network

    Directory of Open Access Journals (Sweden)

    Sharma Neeraj

    2008-01-01

    Full Text Available The objective of developing this software is to achieve auto-segmentation and tissue characterization. Therefore, the present algorithm has been designed and developed for analysis of medical images based on hybridization of syntactic and statistical approaches, using artificial neural network (ANN. This algorithm performs segmentation and classification as is done in human vision system, which recognizes objects; perceives depth; identifies different textures, curved surfaces, or a surface inclination by texture information and brightness. The analysis of medical image is directly based on four steps: 1 image filtering, 2 segmentation, 3 feature extraction, and 4 analysis of extracted features by pattern recognition system or classifier. In this paper, an attempt has been made to present an approach for soft tissue characterization utilizing texture-primitive features with ANN as segmentation and classifier tool. The present approach directly combines second, third, and fourth steps into one algorithm. This is a semisupervised approach in which supervision is involved only at the level of defining texture-primitive cell; afterwards, algorithm itself scans the whole image and performs the segmentation and classification in unsupervised mode. The algorithm was first tested on Markov textures, and the success rate achieved in classification was 100%; further, the algorithm was able to give results on the test images impregnated with distorted Markov texture cell. In addition to this, the output also indicated the level of distortion in distorted Markov texture cell as compared to standard Markov texture cell. Finally, algorithm was applied to selected medical images for segmentation and classification. Results were in agreement with those with manual segmentation and were clinically correlated.

  15. Recognition using information-optimal adaptive feature-specific imaging.

    Science.gov (United States)

    Baheti, Pawan K; Neifeld, Mark A

    2009-04-01

    We present an information-theoretic adaptive feature-specific imaging (AFSI) system for a M-class recognition task. The proposed system utilizes the recently developed task-specific information (TSI) framework to incorporate the knowledge from previous measurements and adapt the projection matrix at each step. The decision-making framework is based on sequential hypothesis testing. We quantify the number of measurements required to achieve a specified probability of misclassification (P(e)), and we compare the performances of three approaches: the new TSI-based AFSI system, a previously reported statistical AFSI system, and static FSI (SFSI). The TSI-based AFSI system exhibits significant improvement compared with SFSI and statistical AFSI at low signal-to-noise ratio (SNR). It is shown that for M=4 hypotheses, SNR=-20 dB and desired P(e)=10(-2), TSI-based AFSI requires 3 times fewer measurements than statistical AFSI, and 16 times fewer measurements than SFSI. We also describe an extension of the proposed method that is suitable for recognition in the presence of nuisance parameters such as illumination conditions and target orientations. PMID:19340282

  16. Imaging features of central nervous system fungal infections

    Directory of Open Access Journals (Sweden)

    Jain Krishan

    2007-01-01

    Full Text Available Fungal infections of the central nervous system (CNS are rare in the general population and are invariably secondary to primary focus elsewhere, usually in the lung or intestine. Except for people with longstanding diabetes, they are most frequently encountered in immunocompromised patients such as those with acquired immunodeficiency syndrome or after organ transplantation. Due to the lack of inflammatory response, neuroradiological findings are often nonspecific and are frequently mistaken for tuberculous meningitis, pyogenic abscess or brain tumor. Intracranial fungal infections are being identified more frequently due to the increased incidence of AIDS patients, better radiological investigations, more sensitive microbiological techniques and better critical care of moribund patients. Although almost any fungus may cause encephalitis, cryptococcal meningoencephalitis is most frequently seen, followed by aspergillosis and candidiasis. The biology, epidemiology and imaging features of the common fungal infections of the CNS will be reviewed. The radiographic appearance alone is often not specific, but the combination of the appropriate clinical setting along with computed tomography or magnetic resonance may help to suggest the correct diagnosis.

  17. A combinatorial Bayesian and Dirichlet model for prostate MR image segmentation using probabilistic image features.

    Science.gov (United States)

    Li, Ang; Li, Changyang; Wang, Xiuying; Eberl, Stefan; Feng, Dagan; Fulham, Michael

    2016-08-21

    Blurred boundaries and heterogeneous intensities make accurate prostate MR image segmentation problematic. To improve prostate MR image segmentation we suggest an approach that includes: (a) an image patch division method to partition the prostate into homogeneous segments for feature extraction; (b) an image feature formulation and classification method, using the relevance vector machine, to provide probabilistic prior knowledge for graph energy construction; (c) a graph energy formulation scheme with Bayesian priors and Dirichlet graph energy and (d) a non-iterative graph energy minimization scheme, based on matrix differentiation, to perform the probabilistic pixel membership optimization. The segmentation output was obtained by assigning pixels with foreground and background labels based on derived membership probabilities. We evaluated our approach on the PROMISE-12 dataset with 50 prostate MR image volumes. Our approach achieved a mean dice similarity coefficient (DSC) of 0.90  ±  0.02, which surpassed the five best prior-based methods in the PROMISE-12 segmentation challenge. PMID:27461085

  18. A combinatorial Bayesian and Dirichlet model for prostate MR image segmentation using probabilistic image features

    Science.gov (United States)

    Li, Ang; Li, Changyang; Wang, Xiuying; Eberl, Stefan; Feng, Dagan; Fulham, Michael

    2016-08-01

    Blurred boundaries and heterogeneous intensities make accurate prostate MR image segmentation problematic. To improve prostate MR image segmentation we suggest an approach that includes: (a) an image patch division method to partition the prostate into homogeneous segments for feature extraction; (b) an image feature formulation and classification method, using the relevance vector machine, to provide probabilistic prior knowledge for graph energy construction; (c) a graph energy formulation scheme with Bayesian priors and Dirichlet graph energy and (d) a non-iterative graph energy minimization scheme, based on matrix differentiation, to perform the probabilistic pixel membership optimization. The segmentation output was obtained by assigning pixels with foreground and background labels based on derived membership probabilities. We evaluated our approach on the PROMISE-12 dataset with 50 prostate MR image volumes. Our approach achieved a mean dice similarity coefficient (DSC) of 0.90  ±  0.02, which surpassed the five best prior-based methods in the PROMISE-12 segmentation challenge.

  19. The statistical distribution of magnetic field strength in G-band bright points

    CERN Document Server

    Criscuoli, Serena

    2013-01-01

    G-band bright points are small-sized features characterized by high photometric contrast. Theoretical investigations indicate that these features have associated magnetic field strengths between 1-2 kG. Results from observations instead lead to contradictory results, indicating magnetic fields of only kG strength in some and including hG strengths in others. In order to understand the differences between measurements reported in the literature, and to reconcile them with results from theory, we analyze the distribution of magnetic field strength of G-band bright features identified on synthetic images of the solar photosphere, and its sensitivity to observational and methodological effects. We investigate the dependence of magnetic field strength distributions of G-band bright points identified in 3D magnetohydrodynamic simulations on feature selection method, data sampling, alignment and spatial resolution. The distribution of magnetic field strength of G-band bright features shows two peaks, one at about 1....

  20. The gray run length and its statistical texture features of coal flotation froth image

    Energy Technology Data Exchange (ETDEWEB)

    Wang Yong; Yang Gong-xun; Lu Mai-xi; Gao Shu-hua [China University of Mining and Technology, Beijing (China). School of Mechanical Electronic and Information Engineering

    2006-07-01

    Aiming at the problem of statistical texture features of coal flotation froth image, many images of coal flotation froth were collected in laboratory. The types and features of froth image were analyzed. Method of extracting gray run length matrix was presented. The run length factors were extracted, which show visual feature of froth. Relationship of these features were studied with flotation time. The result shows that theses parameters show the texture features of coal flotation froth image, which has relationship with special types of froth. The information about froth was offered for visual supervision system of coal flotation. 6 refs., 7 figs.

  1. Image Labeling for LIDAR Intensity Image Using K-Nn of Feature Obtained by Convolutional Neural Network

    Science.gov (United States)

    Umemura, Masaki; Hotta, Kazuhiro; Nonaka, Hideki; Oda, Kazuo

    2016-06-01

    We propose an image labeling method for LIDAR intensity image obtained by Mobile Mapping System (MMS) using K-Nearest Neighbor (KNN) of feature obtained by Convolutional Neural Network (CNN). Image labeling assigns labels (e.g., road, cross-walk and road shoulder) to semantic regions in an image. Since CNN is effective for various image recognition tasks, we try to use the feature of CNN (Caffenet) pre-trained by ImageNet. We use 4,096-dimensional feature at fc7 layer in the Caffenet as the descriptor of a region because the feature at fc7 layer has effective information for object classification. We extract the feature by the Caffenet from regions cropped from images. Since the similarity between features reflects the similarity of contents of regions, we can select top K similar regions cropped from training samples with a test region. Since regions in training images have manually-annotated ground truth labels, we vote the labels attached to top K similar regions to the test region. The class label with the maximum vote is assigned to each pixel in the test image. In experiments, we use 36 LIDAR intensity images with ground truth labels. We divide 36 images into training (28 images) and test sets (8 images). We use class average accuracy and pixel-wise accuracy as evaluation measures. Our method was able to assign the same label as human beings in 97.8% of the pixels in test LIDAR intensity images.

  2. The brightness of colour.

    Directory of Open Access Journals (Sweden)

    David Corney

    Full Text Available BACKGROUND: The perception of brightness depends on spatial context: the same stimulus can appear light or dark depending on what surrounds it. A less well-known but equally important contextual phenomenon is that the colour of a stimulus can also alter its brightness. Specifically, stimuli that are more saturated (i.e. purer in colour appear brighter than stimuli that are less saturated at the same luminance. Similarly, stimuli that are red or blue appear brighter than equiluminant yellow and green stimuli. This non-linear relationship between stimulus intensity and brightness, called the Helmholtz-Kohlrausch (HK effect, was first described in the nineteenth century but has never been explained. Here, we take advantage of the relative simplicity of this 'illusion' to explain it and contextual effects more generally, by using a simple Bayesian ideal observer model of the human visual ecology. We also use fMRI brain scans to identify the neural correlates of brightness without changing the spatial context of the stimulus, which has complicated the interpretation of related fMRI studies. RESULTS: Rather than modelling human vision directly, we use a Bayesian ideal observer to model human visual ecology. We show that the HK effect is a result of encoding the non-linear statistical relationship between retinal images and natural scenes that would have been experienced by the human visual system in the past. We further show that the complexity of this relationship is due to the response functions of the cone photoreceptors, which themselves are thought to represent an efficient solution to encoding the statistics of images. Finally, we show that the locus of the response to the relationship between images and scenes lies in the primary visual cortex (V1, if not earlier in the visual system, since the brightness of colours (as opposed to their luminance accords with activity in V1 as measured with fMRI. CONCLUSIONS: The data suggest that perceptions

  3. Topographic Feature Extraction for Bengali and Hindi Character Images

    CERN Document Server

    Bag, Soumen; 10.5121/sipij.2011.2215

    2011-01-01

    Feature selection and extraction plays an important role in different classification based problems such as face recognition, signature verification, optical character recognition (OCR) etc. The performance of OCR highly depends on the proper selection and extraction of feature set. In this paper, we present novel features based on the topography of a character as visible from different viewing directions on a 2D plane. By topography of a character we mean the structural features of the strokes and their spatial relations. In this work we develop topographic features of strokes visible with respect to views from different directions (e.g. North, South, East, and West). We consider three types of topographic features: closed region, convexity of strokes, and straight line strokes. These features are represented as a shape-based graph which acts as an invariant feature set for discriminating very similar type characters efficiently. We have tested the proposed method on printed and handwritten Bengali and Hindi...

  4. An Algorithm of Image Contrast Enhancement Based on Pixels Neighborhood’s Local Feature

    Directory of Open Access Journals (Sweden)

    Chen Yan

    2013-12-01

    Full Text Available In this study, we proposed an algorithm of Image Contrast enhancement based on local feature to acquire edge information of image, remove Ray Imaging noise and overcome edge blurry and other defects. This method can extract edge features and finish contrast enhancement in varying degrees for pixels neighborhood with different characteristics by using neighborhood local variance and complexity function, which can achieve local features enhancement. The stimulation shows that the method can not only enhance the contrast of the entire image, but also effectively preserves image edge information and improve image quality.

  5. 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.

  6. MR imaging of the neonatal brain: Pathologic features

    International Nuclear Information System (INIS)

    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

  7. FEATURE DIMENSION REDUCTION FOR EFFICIENT MEDICAL IMAGE RETRIEVAL SYSTEM USING UNIFIED FRAMEWORK

    Directory of Open Access Journals (Sweden)

    Yogapriya Jaganathan

    2013-01-01

    Full Text Available Feature dimensionality reduction problem is a major issue in Content Based Medical Image Retrieval (CBMIR for the effective management of medical images with the support of visual features for the purpose of diagnosis and educational research field. However, high dimensional features would be an origin for substantial challenges in retrieval. The proposed CBMIR is used a unified approach based on extraction of visual features, optimized feature selection, classification of optimized features and similarity measurements. However, high dimensional features would be an origin for substantial challenges in retrieval. The Texture features are selected using Gray Level Co-occurrence Matrix (GLCM, Tamura Features (TF and Gabor Filter (GF in which pull out of features are formed a feature vector database. Fuzzy based PSO (FPSO is applied for Feature selection to overcome the difficulty of feature vectors being surrounded in local optima of original PSO. This procedure also integrates a smart policymaking structure of ACO procedure into the novel FPSO where the global optimum position to be exclusive for every feature particle. The Fuzzy based Particle Swarm Optimization and Ant Colony Optimization (FPSO-ACO technique is used to trim down the feature vector dimensionality and classification is accomplished using an extensive Fuzzy based Relevance Vector Machine (FRVM to form collections of relevant image features that would provide an accepted way to classify dimensionally concentrated feature vectors of images. The Euclidean Distance (ED is recognized as finest for similarity measurement between the medical query image and the medical image database. This proposed approach can acquire the query from the user and had retrieved the desired images from the database. The retrieval performance would be assessed based on precision and recall. This proposed CBMIR is used to provide comfort to the physician to obtain more assurance in their decisions for

  8. 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.

  9. Feature Coverage Indexes for Dual Homography Estimation in Constructing Panorama Image

    Directory of Open Access Journals (Sweden)

    Kyungkoo Jun

    2016-01-01

    Full Text Available Enlarged images can be obtained by various methods. Stitching is one of the efficient methods. It can produce panoramic images by stitching adjacent images which contain overlapping regions even though they are obtained through separate image sensors. Images that contain multiple different planes are hard to be stitched together because each plane has a different homography matrix for perspective warping. For this, a dual homography was proposed. However its performance varies depending on feature detectors which are used to find matching feature points between images. In this paper, we propose three feature coverage indexes which evaluate the stitching performance of feature detectors and predict the outcomes of the stitching. We evaluate four well-known feature detectors by the proposed indexes by applying them to the image stitching process and show that the prediction by the index values coincides with the stitching results.

  10. [Image Feature Extraction and Discriminant Analysis of Xinjiang Uygur Medicine Based on Color Histogram].

    Science.gov (United States)

    Hamit, Murat; Yun, Weikang; Yan, Chuanbo; Kutluk, Abdugheni; Fang, Yang; Alip, Elzat

    2015-06-01

    Image feature extraction is an important part of image processing and it is an important field of research and application of image processing technology. Uygur medicine is one of Chinese traditional medicine and researchers pay more attention to it. But large amounts of Uygur medicine data have not been fully utilized. In this study, we extracted the image color histogram feature of herbal and zooid medicine of Xinjiang Uygur. First, we did preprocessing, including image color enhancement, size normalizition and color space transformation. Then we extracted color histogram feature and analyzed them with statistical method. And finally, we evaluated the classification ability of features by Bayes discriminant analysis. Experimental results showed that high accuracy for Uygur medicine image classification was obtained by using color histogram feature. This study would have a certain help for the content-based medical image retrieval for Xinjiang Uygur medicine. PMID:26485983

  11. The Matching Research of Strawberry Diseases Image Features Based on KD-Tree Search Method

    OpenAIRE

    Jianshu, Chen; Jianlun, Wang; Shuting, Wang; Hao, Liu

    2013-01-01

    International audience According to the problem of the low matching accuracy rate and the low speed in the matching technology for image search, we choose the image of the strawberry diseases as the object of the research, to extract the feature of strawberry diseases image and then do cluster analysis using SPSS, and choose the feature combination according to the clustering effect. Do search matching experiments on the feature combination by KD-Tree matching algorithm respectively, and d...

  12. A novel registration method for retinal images based on local features

    OpenAIRE

    Chen, Jian; R Theodore Smith; Tian, Jie; Laine, Andrew F

    2008-01-01

    Sometimes it is very hard to automatically detect the bifurcations of vascular network in retinal images so that the general feature based registration methods will fail to register two images. In order to solve this problem, we developed a novel local feature based retinal image registration method. We first detect the corner points instead of bifurcations since corner points are sufficient and uniformly distributed in the overlaps. Second, a novel highly distinctive local feature is extract...

  13. Content-Based Digital Image Retrieval based on Multi-Feature Amalgamation

    Directory of Open Access Journals (Sweden)

    Linhao Li

    2013-12-01

    Full Text Available In actual implementation, digital image retrieval are facing all kinds of problems. There still exists some difficulty in measures and methods for application. Currently there is not a unambiguous algorithm which can directly shown the obvious feature of image content and satisfy the color, scale invariance and rotation invariance of feature simultaneously. So the related technology about image retrieval based on content is analyzed by us. The research focused on global features such as seven HU invariant moments, edge direction histogram and eccentricity. The method for blocked image is also discussed. During the process of image matching, the extracted image features are looked as the points in vector space. The similarity of two images is measured through the closeness between two points and the similarity is calculated by Euclidean distance and the intersection distance of histogram. Then a novel method based on multi-features amalgamation is proposed, to solve the problems in retrieval method for global feature and local feature. It extracts the eccentricity, seven HU invariant moments and edge direction histogram to calculate the similarity distance of each feature of the images, then they are normalized. Contraposing the interior of global feature the weighted feature distance is adopted to form similarity measurement function for retrieval. The features of blocked images are extracted with the partitioning method based on polar coordinate. Finally by the idea of hierarchical retrieval between global feature and local feature, the results are output through global features like invariant moments etc. These results will be taken as the input of local feature match for the second-layer retrieval, which can improve the accuracy of retrieval effectively.

  14. Performance Evaluation of Content Based Image Retrieval on Feature Optimization and Selection Using Swarm Intelligence

    OpenAIRE

    Kirti Jain; Dr. Sarita Singh Bhadauria

    2016-01-01

    The diversity and applicability of swarm intelligence is increasing everyday in the fields of science and engineering. Swarm intelligence gives the features of the dynamic features optimization concept. We have used swarm intelligence for the process of feature optimization and feature selection for content-based image retrieval. The performance of content-based image retrieval faced the problem of precision and recall. The value of precision and recall depends on the retrieval capacity of th...

  15. A new approach for 3D reconstruction from bright field TEM imaging: Beam precession assisted electron tomography

    International Nuclear Information System (INIS)

    The successful combination of electron beam precession and bright field electron tomography for 3D reconstruction is reported. Beam precession is demonstrated to be a powerful technique to reduce the contrast artifacts due to diffraction and curvature in thin foils. Taking advantage of these benefits, Precession assisted electron tomography has been applied to reconstruct the morphology of Sn precipitates embedded in an Al matrix, from a tilt series acquired in a range from +49o to -61o at intervals of 2o and with a precession angle of 0.6o in bright field mode. The combination of electron tomography and beam precession in conventional TEM mode is proposed as an alternative procedure to obtain 3D reconstructions of nano-objects without a scanning system or a high angle annular dark field detector. -- Highlights: → Electron beam precession reduces spurious diffraction contrast in bright field mode. → Bend contour related contrast depends on precession angle. → Electron beam precession is combined with bright field electron tomography. → Precession assisted BF tomography allowed 3D reconstruction of a Sn precipitate.

  16. Pancreatitis in patients with pancreas divisum: Imaging features at MRI and MRCP

    OpenAIRE

    2013-01-01

    AIM: To determine the magnetic resonance cholangiopancreatography (MRCP) and magnetic resonance imaging (MRI) features of pancreatitis with pancreas divisum (PD) and the differences vs pancreatitis without divisum.

  17. Image search engine with selective filtering and feature-element-based classification

    Science.gov (United States)

    Li, Qing; Zhang, Yujin; Dai, Shengyang

    2001-12-01

    With the growth of Internet and storage capability in recent years, image has become a widespread information format in World Wide Web. However, it has become increasingly harder to search for images of interest, and effective image search engine for the WWW needs to be developed. We propose in this paper a selective filtering process and a novel approach for image classification based on feature element in the image search engine we developed for the WWW. First a selective filtering process is embedded in a general web crawler to filter out the meaningless images with GIF format. Two parameters that can be obtained easily are used in the filtering process. Our classification approach first extract feature elements from images instead of feature vectors. Compared with feature vectors, feature elements can better capture visual meanings of the image according to subjective perception of human beings. Different from traditional image classification method, our classification approach based on feature element doesn't calculate the distance between two vectors in the feature space, while trying to find associations between feature element and class attribute of the image. Experiments are presented to show the efficiency of the proposed approach.

  18. 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...

  19. A Partial Intensity Invariant Feature Descriptor for Multimodal Retinal Image Registration

    OpenAIRE

    Chen, Jian; Tian, Jie; Lee, Noah; Zheng, Jian; Smith, R. Theodore; Laine, Andrew F

    2010-01-01

    Detection of vascular bifurcations is a challenging task in multimodal retinal image registration. Existing algorithms based on bifurcations usually fail in correctly aligning poor quality retinal image pairs. To solve this problem, we propose a novel highly distinctive local feature descriptor named partial intensity invariant feature descriptor (PIIFD) and describe a robust automatic retinal image registration framework named Harris-PIIFD. PIIFD is invariant to image rotation, partially inv...

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

    International Nuclear Information System (INIS)

    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

  1. Automatic registration of CT and MR brain images using correlation of geometrical features

    International Nuclear Information System (INIS)

    This paper describes an automated approach to register CT and MR brain images. Differential operators in scale space are applied to each type of image data, so as to produce feature images depicting ''ridgeness''. The resulting CT and MR feature images show similarities which can be used for matching. No segmentation is needed and the method is devoid of human interaction. The matching is accomplished by hierarchical correlation techniques. Results of 2-D and 3-D matching experiments are presented. The correlation function ensures an accurate match even if the scanned volumes to be matched do not completely overlap, or if some of the features in the images are not similar

  2. Variability of Image Features Computed from Conventional and Respiratory-Gated PET/CT Images of Lung Cancer

    Directory of Open Access Journals (Sweden)

    Jasmine A. Oliver

    2015-12-01

    Full Text Available Radiomics is being explored for potential applications in radiation therapy. How various imaging protocols affect quantitative image features is currently a highly active area of research. To assess the variability of image features derived from conventional [three-dimensional (3D] and respiratory-gated (RG positron emission tomography (PET/computed tomography (CT images of lung cancer patients, image features were computed from 23 lung cancer patients. Both protocols for each patient were acquired during the same imaging session. PET tumor volumes were segmented using an adaptive technique which accounted for background. CT tumor volumes were delineated with a commercial segmentation tool. Using RG PET images, the tumor center of mass motion, length, and rotation were calculated. Fifty-six image features were extracted from all images consisting of shape descriptors, first-order features, and second-order texture features. Overall, 26.6% and 26.2% of total features demonstrated less than 5% difference between 3D and RG protocols for CT and PET, respectively. Between 10 RG phases in PET, 53.4% of features demonstrated percent differences less than 5%. The features with least variability for PET were sphericity, spherical disproportion, entropy (first and second order, sum entropy, information measure of correlation 2, Short Run Emphasis (SRE, Long Run Emphasis (LRE, and Run Percentage (RPC; and those for CT were minimum intensity, mean intensity, Root Mean Square (RMS, Short Run Emphasis (SRE, and RPC. Quantitative analysis using a 3D acquisition versus RG acquisition (to reduce the effects of motion provided notably different image feature values. This study suggests that the variability between 3D and RG features is mainly due to the impact of respiratory motion.

  3. A method to evaluate the performance of X-ray imaging scintillators by means of the brightness-sharpness index (BSI)

    International Nuclear Information System (INIS)

    Purpose: To propose an image quality index, the brightness-sharpness index (BSI), for assessing the quality of the image produced by phosphors of medical imaging detectors. Material and methods: BSI was evaluated by experimental X-ray luminescence and modulation transfer function measurements. BSI was determined for a number of test phosphor screens prepared from Gd2O2S:Tb, La2O2S:Tb, and Y2O2S:Tb phosphor materials. The screens covered a wide range of coating thicknesses from 50 to 150 mg/cm2 and measurements were performed for X-ray tube voltages between 50 and 120 kVp. Results: Gd2O2S:Tb phosphor exhibited higher brightness and sharpness, as compared to the other phosphor materials, for all screens and X-ray tube voltages used. Best Gd2O2S:Tb performance was observed for thin screens and high tube voltages. La2O2S:Tb exhibited higher BSI values than Y2O2S:Tb for medium and high tube voltages. Conclusion: Results showed that phosphor materials of high X-ray detection and X-ray-to-light conversion properties exhibit high BSI values indicating that BSI may provide a means of phosphor performance evaluation for imaging applications. (orig.)

  4. Nasopharyngeal carcinoma: Imaging features of unusual cancer in children

    Directory of Open Access Journals (Sweden)

    Ayda A. Youssef

    2015-12-01

    Conclusion: Pediatric NPC is generally not suspected clinically until late into the disease process. Awareness that NPC can occur in children should prompt careful evaluation for distinctive radiographic features. Earlier diagnosis may then direct the patient to timely appropriate therapy when these key radiographic features are present and recognized.

  5. Age Estimation Based on AAM and 2D-DCT Features of Facial Images

    Directory of Open Access Journals (Sweden)

    Asuman Günay

    2015-02-01

    Full Text Available This paper proposes a novel age estimation method - Global and Local feAture based Age estiMation (GLAAM - relying on global and local features of facial images. Global features are obtained with Active Appearance Models (AAM. Local features are extracted with regional 2D-DCT (2- dimensional Discrete Cosine Transform of normalized facial images. GLAAM consists of the following modules: face normalization, global feature extraction with AAM, local feature extraction with 2D-DCT, dimensionality reduction by means of Principal Component Analysis (PCA and age estimation with multiple linear regression. Experiments have shown that GLAAM outperforms many methods previously applied to the FG-NET database.

  6. Fast Image Retrieval of Textile Industrial Accessory Based on Multi-Feature Fusion

    Institute of Scientific and Technical Information of China (English)

    沈文忠; 杨杰

    2004-01-01

    A hierarchical retrieval scheme of the accessory image database is proposed based on textile industrial accessory contour feature and region feature. At first smallest enclosed rectangle[1] feature (degree of accessory coordination) is used to filter the image database to decouple the image search scope. After the accessory contour information and region information are extracted, the fusion multi-feature of the centroid distance Fourier descriptor and distance distribution histogram is adopted to finish image retrieval accurately. All the features above are invariable under translation, scaling and rotation. Results from the test on the image database including 1,000 accessory images demonstrate that the method is effective and practical with high accuracy and fast speed.

  7. Feature Extraction with Ordered Mean Values for Content Based Image Classification

    Directory of Open Access Journals (Sweden)

    Sudeep Thepade

    2014-01-01

    Full Text Available Categorization of images into meaningful classes by efficient extraction of feature vectors from image datasets has been dependent on feature selection techniques. Traditionally, feature vector extraction has been carried out using different methods of image binarization done with selection of global, local, or mean threshold. This paper has proposed a novel technique for feature extraction based on ordered mean values. The proposed technique was combined with feature extraction using discrete sine transform (DST for better classification results using multitechnique fusion. The novel methodology was compared to the traditional techniques used for feature extraction for content based image classification. Three benchmark datasets, namely, Wang dataset, Oliva and Torralba (OT-Scene dataset, and Caltech dataset, were used for evaluation purpose. Performance measure after evaluation has evidently revealed the superiority of the proposed fusion technique with ordered mean values and discrete sine transform over the popular approaches of single view feature extraction methodologies for classification.

  8. Image Retrieval via Relevance Vector Machine with Multiple Features

    OpenAIRE

    Zemin Liu; Wei Zong

    2014-01-01

    With the fast development of computer network technique, there is large amount of image information every day. Researchers have paid more and more attention to the problem of how users quickly retrieving and identifying the images that they may interest. Meanwhile, with the rapid development of artificial intelligence and pattern recognition techniques, it provides people with new thought on the study on complex image retrieval while it’s very difficult for traditional machine learning ...

  9. Combined image and text relational database features and implications

    International Nuclear Information System (INIS)

    A relational database has been developed that allows comparison of patient information, imaging signs, and diagnosis with surgical pathology and the actual images. This allows comparison of the diagnostic accuracy of CT, MR imaging, US, and digital subtraction angiography with pathologic, cytologic, and surgical findings. This is a significant research and quality-assurance tool. This system is unique because of its ability to have a totally relational database linking binary image files with ASCII text. Previously this has not been possible at 8-bit pixel depth because of the lack of interface modules

  10. Image Mining for Mammogram Classification by Association Rule Using Statistical and GLCM features

    Directory of Open Access Journals (Sweden)

    Aswini Kumar Mohanty

    2011-09-01

    Full Text Available The image mining technique deals with the extraction of implicit knowledge and image with data relationship or other patterns not explicitly stored in the images. It is an extension of data mining to image domain. The main objective of this paper is to apply image mining in the domain such as breast mammograms to classify and detect the cancerous tissue. Mammogram image can be classified into normal, benign and malignant class and to explore the feasibility of data mining approach. A new association rule algorithm is proposed in this paper. Experimental results show that this new method can quickly discover frequent item sets and effectively mine potential association rules. A total of 26 features including histogram intensity features and GLCM features are extracted from mammogram images. A new approach of feature selection is proposed which approximately reduces 60% of the features and association rule using image content is used for classification. The most interesting one is that oscillating search algorithm which is used for feature selection provides the best optimal features and no where it is applied or used for GLCM feature selection from mammogram. Experiments have been taken for a data set of 300 images taken from MIAS of different types with the aim of improving the accuracy by generating minimum no. of rules to cover more patterns. The accuracy obtained by this method is approximately 97.7% which is highly encouraging.

  11. Change Detection in Uav Video Mosaics Combining a Feature Based Approach and Extended Image Differencing

    Science.gov (United States)

    Saur, Günter; Krüger, Wolfgang

    2016-06-01

    Change detection is an important task when using unmanned aerial vehicles (UAV) for video surveillance. We address changes of short time scale using observations in time distances of a few hours. Each observation (previous and current) is a short video sequence acquired by UAV in near-Nadir view. Relevant changes are, e.g., recently parked or moved vehicles. Examples for non-relevant changes are parallaxes caused by 3D structures of the scene, shadow and illumination changes, and compression or transmission artifacts. In this paper we present (1) a new feature based approach to change detection, (2) a combination with extended image differencing (Saur et al., 2014), and (3) the application to video sequences using temporal filtering. In the feature based approach, information about local image features, e.g., corners, is extracted in both images. The label "new object" is generated at image points, where features occur in the current image and no or weaker features are present in the previous image. The label "vanished object" corresponds to missing or weaker features in the current image and present features in the previous image. This leads to two "directed" change masks and differs from image differencing where only one "undirected" change mask is extracted which combines both label types to the single label "changed object". The combination of both algorithms is performed by merging the change masks of both approaches. A color mask showing the different contributions is used for visual inspection by a human image interpreter.

  12. An adequate approach to image retrieval based on local level feature extraction

    International Nuclear Information System (INIS)

    Image retrieval based on text annotation has become obsolete and is no longer interesting for scientists because of its high time complexity and low precision in results. Alternatively, increase in the amount of digital images has generated an excessive need for an accurate and efficient retrieval system. This paper proposes content based image retrieval technique at a local level incorporating all the rudimentary features. Image undergoes the segmentation process initially and each segment is then directed to the feature extraction process. The proposed technique is also based on image?s content which primarily includes texture, shape and color. Besides these three basic features, FD (Fourier Descriptors) and edge histogram descriptors are also calculated to enhance the feature extraction process by taking hold of information at the boundary. Performance of the proposed method is found to be quite adequate when compared with the results from one of the best local level CBIR (Content Based Image Retrieval) techniques. (author)

  13. An Adequate Approach to Image Retrieval Based on Local Level Feature Extraction

    Directory of Open Access Journals (Sweden)

    Sumaira Muhammad Hayat Khan

    2010-10-01

    Full Text Available Image retrieval based on text annotation has become obsolete and is no longer interesting for scientists because of its high time complexity and low precision in results. Alternatively, increase in the amount of digital images has generated an excessive need for an accurate and efficient retrieval system. This paper proposes content based image retrieval technique at a local level incorporating all the rudimentary features. Image undergoes the segmentation process initially and each segment is then directed to the feature extraction process. The proposed technique is also based on image?s content which primarily includes texture, shape and color. Besides these three basic features, FD (Fourier Descriptors and edge histogram descriptors are also calculated to enhance the feature extraction process by taking hold of information at the boundary. Performance of the proposed method is found to be quite adequate when compared with the results from one of the best local level CBIR (Content Based Image Retrieval techniques.

  14. 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.

  15. Feature

    Science.gov (United States)

    2011-01-01

    Shi Changxu, former vice-president of NSFC wins Top Prize of National Science and Technology Award of China Both China and the world materials community have greatly benefitted from his service, by RPH Chang Shi Changxu—a great teacher and mentor for materials scientists, by Gaoqing Max Lu A bright example for all of us—Professor Shi Changxu, by Wei Gao Professor Shi Changxu—The Giant Materials Scientist of China, by Wuzong Zhou Congratulations to Academician Changxu Shi on the Occasion of His Winning the 2010 Chinese Science & Technology Grand Prize, by Ju Li, Kai Chen, Zhiwei Shan, Guanjun Qiao, Jun Sun and Evan Ma Materials—the foundation for technology revolutions, by Zhong Lin Wang

  16. Extremely High Brightness from Polymer-Encapsulated Quantum Dots for Two-photon Cellular and Deep-tissue Imaging

    OpenAIRE

    Fan, Yanyan; Liu, Helin; Han, Rongcheng; Huang, Lu; Shi, Hao; Sha, Yinlin; Jiang, Yuqiang

    2015-01-01

    Materials possessing high two photon absorption (TPA) are highly desirable for a range of fields, such as three-dimensional data storage, TP microscopy (TPM) and photodynamic therapy (PDT). Specifically, for TPM, high TP excitation (TPE) brightness (σ × ϕ, where σ is TPA cross-sections and ϕ is fluorescence quantum yield), excellent photostability and minimal cytotoxicity are highly desirable. However, when TPA materials are transferred to aqueous media through molecule engineering or nanopar...

  17. Artificial-neural-network-based classification of mammographic microcalcifications using image structure features

    Science.gov (United States)

    Dhawan, Atam P.; Chitre, Yateen S.; Moskowitz, Myron

    1993-07-01

    Mammography associated with clinical breast examination and self-breast examination is the only effective and viable method for mass breast screening. It is however, difficult to distinguish between benign and malignant microcalcifications associated with breast cancer. Most of the techniques used in the computerized analysis of mammographic microcalcifications segment the digitized gray-level image into regions representing microcalcifications. We present a second-order gray-level histogram based feature extraction approach to extract microcalcification features. These features, called image structure features, are computed from the second-order gray-level histogram statistics, and do not require segmentation of the original image into binary regions. Several image structure features were computed for 100 cases of `difficult to diagnose' microcalcification cases with known biopsy results. These features were analyzed in a correlation study which provided a set of five best image structure features. A feedforward backpropagation neural network was used to classify mammographic microcalcifications using the image structure features. The network was trained on 10 cases of mammographic microcalcifications and tested on additional 85 `difficult-to-diagnose' microcalcifications cases using the selected image structure features. The trained network yielded good results for classification of `difficult-to- diagnose' microcalcifications into benign and malignant categories.

  18. 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. PMID:21912534

  19. Feature Based Image Sequence Retargeting in the Uncompressed Video Domain

    Directory of Open Access Journals (Sweden)

    Kavitha. S

    2013-01-01

    Full Text Available The system propose a video retargeting algorithmto resize images based on the extracted saliency informationfrom the compressed domain. The system utilizes DCTcoefficients in JP2 bit stream to perform saliency detectionwith the consideration of the human visual sensitivity.Valuable retargeting requires emphasize the main satisfiedwhile retain immediate context with minimal visualdeformation. A number of algorithms have been proposedfor image retargeting with image substance taken as muchas potential. But, they usually suffer from deformationresults, such as edge or structure twists. A structure andcontent preserving image retargeting technique is used thatpreserves the content and image structure. The imagecontent saliency is estimated from the structure of thecontent using probability map. A block structure energy isuse for structure conservation along both directions. Blockstructure energy uses top down strategy to constrict theimage structure consistently. However, the flexibilities ofretargeting are altered for different images. To defeat thisproblem, the patch transform is introduced, where an imageis broken into non-overlapping patches, and modificationsor constraints are applied in the “patch domain”.. Thus, theresized image is produced to preserve the structure andimage content quality.

  20. A HYBRID APPROACH BASED MEDICAL IMAGE RETRIEVAL SYSTEM USING FEATURE OPTIMIZED CLASSIFICATION SIMILARITY FRAMEWORK

    Directory of Open Access Journals (Sweden)

    Yogapriya Jaganathan

    2013-01-01

    Full Text Available For the past few years, massive upgradation is obtained in the pasture of Content Based Medical Image Retrieval (CBMIR for effective utilization of medical images based on visual feature analysis for the purpose of diagnosis and educational research. The existing medical image retrieval systems are still not optimal to solve the feature dimensionality reduction problem which increases the computational complexity and decreases the speed of a retrieval process. The proposed CBMIR is used a hybrid approach based on Feature Extraction, Optimization of Feature Vectors, Classification of Features and Similarity Measurements. This type of CBMIR is called Feature Optimized Classification Similarity (FOCS framework. The selected features are Textures using Gray level Co-occurrence Matrix Features (GLCM and Tamura Features (TF in which extracted features are formed as feature vector database. The Fuzzy based Particle Swarm Optimization (FPSO technique is used to reduce the feature vector dimensionality and classification is performed using Fuzzy based Relevance Vector Machine (FRVM to form groups of relevant image features that provide a natural way to classify dimensionally reduced feature vectors of images. The Euclidean Distance (ED is used as similarity measurement to measure the significance between the query image and the target images. This FOCS approach can get the query from the user and has retrieved the needed images from the databases. The retrieval algorithm performances are estimated in terms of precision and recall. This FOCS framework comprises several benefits when compared to existing CBMIR. GLCM and TF are used to extract texture features and form a feature vector database. Fuzzy-PSO is used to reduce the feature vector dimensionality issues while selecting the important features in the feature vector database in which computational complexity is decreased. Fuzzy based RVM is used for feature classification in which it increases the

  1. Integrating Color and Spatial Feature for Content-Based Image Retrieval

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    In this paper, we present a novel and efficient scheme for extracting, indexing and retrieving color images. Our motivation was to reduce the space overhead of partition-based approaches taking advantage of the fact that only a relatively low number of distinct values of a particular visual feature is present in most images. To extract color feature and build indices into our image database we take into consideration factors such as human color perception and perceptual range, and the image is partitioned into a set of regions by using a simple classifying scheme. The compact color feature vector and the spatial color histogram, which are extracted from the seqmented image region, are used for representing the color and spatial information in the image. We have also developed the region-based distance measures to compare the similarity of two images. Extensive tests on a large image collection were conducted to demonstrate the effectiveness of the proposed approach.

  2. A novel high-contrast imaging technique based on optical tunneling to search for faint companions around bright stars at the limit of diffraction

    CERN Document Server

    Derigs, Dominik; Ghosh, Dhriti Sundar; Abel-Tibérini, Laëtitia

    2016-01-01

    We present a novel application of optical tunneling in the context of high-angular resolution, high-contrast techniques with the aim of improving direct imaging capabilities of faint companions in the vicinity of bright stars. In contrast to existing techniques like coronagraphy, we apply well-established techniques from integrated optics to exclusively extinct a very narrow angular direction coming from the sky. This extinction is achieved in the pupil plane and does not suffer from diffraction pattern residuals. We give a comprehensive presentation of the underlying theory as well as first laboratory results.

  3. Kernel Density Feature Points Estimator for Content-Based Image Retrieval

    CERN Document Server

    Zuva, Tranos; Ojo, Sunday O; Ngwira, Seleman M

    2012-01-01

    Research is taking place to find effective algorithms for content-based image representation and description. There is a substantial amount of algorithms available that use visual features (color, shape, texture). Shape feature has attracted much attention from researchers that there are many shape representation and description algorithms in literature. These shape image representation and description algorithms are usually not application independent or robust, making them undesirable for generic shape description. This paper presents an object shape representation using Kernel Density Feature Points Estimator (KDFPE). In this method, the density of feature points within defined rings around the centroid of the image is obtained. The KDFPE is then applied to the vector of the image. KDFPE is invariant to translation, scale and rotation. This method of image representation shows improved retrieval rate when compared to Density Histogram Feature Points (DHFP) method. Analytic analysis is done to justify our m...

  4. 3D Elastic Registration of Ultrasound Images Based on Skeleton Feature

    Institute of Scientific and Technical Information of China (English)

    LI Dan-dan; LIU Zhi-Yan; SHEN Yi

    2005-01-01

    In order to eliminate displacement and elastic deformation between images of adjacent frames in course of 3D ultrasonic image reconstruction, elastic registration based on skeleton feature was adopt in this paper. A new automatically skeleton tracking extract algorithm is presented, which can extract connected skeleton to express figure feature. Feature points of connected skeleton are extracted automatically by accounting topical curvature extreme points several times. Initial registration is processed according to barycenter of skeleton. Whereafter, elastic registration based on radial basis function are processed according to feature points of skeleton. Result of example demonstrate that according to traditional rigid registration, elastic registration based on skeleton feature retain natural difference in shape for organ's different part, and eliminate slight elastic deformation between frames caused by image obtained process simultaneously. This algorithm has a high practical value for image registration in course of 3D ultrasound image reconstruction.

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

    KAUST Repository

    Wang, Jingyan

    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.

  6. 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.

  7. An Image Retrieval Method Based on Color and Texture Features

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    The technique of image retrieval is widely used in science experiment, military affairs, public security,advertisement, family entertainment, library and so on. The existing algorithms are mostly based on the characteristics of color, texture, shape and space relationship. This paper introduced an image retrieval algorithm, which is based on the matching of weighted EMD(Earth Mover's Distance) distance and texture distance. EMD distance is the distance between the histograms of two images in HSV(Hue, Saturation, Value) color space, and texture distance is the L1 distance between the texture spectra of two images. The experimental results show that the retrieval rate can be increased obviously by using the proposed algorithm.

  8. 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.)

  9. Crowd Density and Counting Estimation Based on Image Textural Feature

    Directory of Open Access Journals (Sweden)

    Jianjie Yang

    2014-10-01

    Full Text Available This paper proposes an image textural analytical method for estimating the crowd density and counting. At first, the target detection is conducted to obtain the foreground image. This crowd image is used to calculate the gray level co-occurrence matrix (GLCM. Then, according to the characteristic values of the gray level co-occurrence matrix, i.e., energy, entropy, contrast, homogeneity, we use support vector machine (SVM to estimate crowd density. Simultaneously, the method of linear regression is used to estimate the crowd counting. The accuracy of evaluation is improved since we extract the target image textural traits to overcome the influence of background for estimation results. Finally, the experimental results show that the proposed approaches of crowd density and counting are feasible and effective

  10. Mature and immature ovarian teratomas: US, CT and MR imaging features

    International Nuclear Information System (INIS)

    Mature cystic ovarian teratomas, also called dermoid cysts, are one of the most frequent ovarian tumors of younger female patients and are suggested when a fat-containing cystic tumor is identified on imaging. However, the presence of fat is not pathognomonic for dermoid cyst, and it may also be identified in immature teratomas, whose prognosis and treatment are different. Some imaging features are helpful to differentiate between both tumors, including the presence of enhancement on CT and MRI. Knowledge of the imaging features of these tumors allows for a confident diagnosis to be made in most cases. A few rare and less typical imaging features should also be recognized. (authors)

  11. Ultrasound Image Classification for Down Syndrome During First Trimester Using Haralick Features

    Directory of Open Access Journals (Sweden)

    R. Sonia

    2014-05-01

    Full Text Available Down syndrome or Trisomy 21 is a genetic disorder which causes mental disability to the baby during the gestation period. Ultrasound scan, a noninvasive test which includes ultrasound fetal image scan for the Nuchal Translucency measurement (NT. This work proposes a method to detect and classify the down syndrome images for Nuchal translucency from ultrasound scan images using Gray Level Co-occurrence Matrix (GLCM. Fourteen GLCM features are used for feature extraction. The features are classified using Support Vector Machine (SVM classifier for normal NT and abnormal NT image. The high performance and classification rate of 94.4% is obtained using SVM classifier with Polynomial Kernel function.

  12. Image Analysis of Soil Micromorphology: Feature Extraction, Segmentation, and Quality Inference

    Directory of Open Access Journals (Sweden)

    Petros Maragos

    2004-06-01

    Full Text Available We present an automated system that we have developed for estimation of the bioecological quality of soils using various image analysis methodologies. Its goal is to analyze soilsection images, extract features related to their micromorphology, and relate the visual features to various degrees of soil fertility inferred from biochemical characteristics of the soil. The image methodologies used range from low-level image processing tasks, such as nonlinear enhancement, multiscale analysis, geometric feature detection, and size distributions, to object-oriented analysis, such as segmentation, region texture, and shape analysis.

  13. An Effective Combined Feature For Web Based Image Retrieval

    OpenAIRE

    H.M.R.B Herath; Y.P.R.D Yapa

    2015-01-01

    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 c...

  14. The imaging features of MACROLANETM in breast augmentation

    International Nuclear Information System (INIS)

    MacrolaneTM is an injectable, biocompatible, soft-tissue filler that has been available in the UK since 2008 and is promoted for use in breast augmentation. There are few data available on the long-term effects of this relatively new product and concerns have been raised about the implications for breast imaging, in particular breast screening. In this context we present a spectrum of imaging appearances and complications encountered to date.

  15. Survey on Sparse Coded Features for Content Based Face Image Retrieval

    OpenAIRE

    Johnvictor, D.; Selvavinayagam, G.

    2014-01-01

    Content based image retrieval, a technique which uses visual contents of image to search images from large scale image databases according to users' interests. This paper provides a comprehensive survey on recent technology used in the area of content based face image retrieval. Nowadays digital devices and photo sharing sites are getting more popularity, large human face photos are available in database. Multiple types of facial features are used to represent discriminality on large scale hu...

  16. Fusion of tf.idf Weighted Bag of Visual Features for Image Classification

    OpenAIRE

    Moulin, Christophe; Barat, Cécile; Ducottet, Christophe

    2010-01-01

    Image representation using bag of visual words approach is commonly used in image classification. Features are extracted from images and clustered into a visual vocabulary. Images can then be represented as a normalized histogram of visual words similarly to textual documents represented as a weighted vector of terms. As a result, text categorization techniques are applicable to image classification. In this paper, our contribution is twofold. First, we propose a suitable Term-Frequency and I...

  17. Feature Understanding and Target Detection for Sparse Microwave Synthetic Aperture Radar Images

    OpenAIRE

    Zhang Zenghui; Yu Wenxian

    2016-01-01

    Sparse microwave imaging using sparse priors of observed scenes in space, time, frequency, or polarization domain and echo data with sampling rate smaller than the traditional Nyquist rate as well as optimization algorithms for reconstructing the microwave images of observed scenes has many advantages over traditional microwave imaging systems. In sparse microwave imaging, image acquisition and representation vary; therefore, new feature analysis and cognitive interpretation theories and meth...

  18. Imaging features of calcifying pseudoneoplasms of the neuraxis

    International Nuclear Information System (INIS)

    Objective: To identify the imaging characteristics of calcifying pseudoneoplasms of the neuraxis (CAPNON) and do literature review. Methods: Five patients of pathologically-proved CAPNON underwent preoperative MR examination,among which 4 underwent CT scan, 2 underwent DSA examination and 1 underwent SPECT. All imaging data were retrospectively analyzed with the emphasis on imaging characteristics.Results Five patients of CAPNON with the diameter of 1.5 to 5.0 cm were found in five patients (Male 4; Female 1; age 25 to 60 years old). Three lesions were located in the skull base, one was located in the cervical spine and one in the foramen magnum and upper cervical segment. All patients underwent MRI examination and 4 of them also took CT scanning. On plain CT, all lesions showed obvious calcification. On T1WI all masses showed hypointensity, and on T2WI 4 of the lesions showed iso- or hypointensity and 1 heterogeneous signal intensity. On contrast-enhanced MR images, peripheral enhancement was demonstrated in 3 lesions, homogeneous enhancement was found in case and one lesion showed no enhancement. The pathologic analysis indicated that inside the lesions were abundant calcification, fibroepithelial tissue and mucoid matrix and no edema was detected around the lesions. Conclusions: CAPNON displayed the predilection to male adults and the neuraxis was the predilection site. Calcification on CT images, hypointensity on MR images and peripheral enhancement will be helpful for the diagnosis of CAPNON, but the final confirmation still needs the pathologic results. (authors)

  19. 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.

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

    International Nuclear Information System (INIS)

    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

  1. Content-based retrieval of remote sensed images using a feature-based approach

    Science.gov (United States)

    Vellaikal, Asha; Dao, Son; Kuo, C.-C. Jay

    1995-01-01

    A feature-based representation model for content-based retrieval from a remote sensed image database is described in this work. The representation is formed by clustering spatially local pixels, and the cluster features are used to process several types of queries which are expected to occur frequently in the context of remote sensed image retrieval. Preliminary experimental results show that the feature-based representation provides a very promising tool for content-based access.

  2. 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

    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...

  3. Rotation and Scale Invariant Wavelet Feature for Content-Based Texture Image Retrieval.

    Science.gov (United States)

    Lee, Moon-Chuen; Pun, Chi-Man

    2003-01-01

    Introduces a rotation and scale invariant log-polar wavelet texture feature for image retrieval. The underlying feature extraction process involves a log-polar transform followed by an adaptive row shift invariant wavelet packet transform. Experimental results show that this rotation and scale invariant wavelet feature is quite effective for image…

  4. Scale space smoothing, image feature extraction and bessel filters

    OpenAIRE

    Mahmoodi S.; Gunn S.

    2011-01-01

    The Green function of Mumford-Shah functional in the absence of discontinuities is known to be a modified Bessel function of the second kind and zero degree. Such a Bessel function is regularized here and used as a filter for feature extraction. It is demonstrated in this paper that a Bessel filter does not follow the scale space smoothing property of bounded linear filters such as Gaussian filters. The features extracted by the Bessel filter are therefore scale invariant. Edges, blobs, and j...

  5. Feature extraction and track measurement for low resolution images: A cost effective method

    International Nuclear Information System (INIS)

    In a track counting system a digital USB CCD camera is often used to make a communication between the visually seen etched tracks of a solid state nuclear track detector and the image analyzer software installed on the PC. The camera's characteristics determine the size of the image, and the number of pixels per track. The resolution and contrast of the images are the key features in how well an image analyzer can perform the task of track measurement. In this paper we present an approach to increase the resolution and contrast of the images, aiming to extract the features which cannot be simply attained from the original image. The presented algorithm as an image processing technique is used to replace the economical cost of high quality imaging system with the computational cost of image processing. The tracks' characteristics will remain intact and the contrast of the image will be enhanced through Shannon entropy reaching its maximum. Feature preservation is done through maximizing the similarity between the original low resolution image and the processed higher resolution image. Similarity is defined as the mutual information between two images. This resolution increment will result in contrast enhancement and increased information transfer for feature extraction purpose. Experimental images of alpha tracks taken by a 350KP USB digital camera are used to verify the efficiency of the proposed algorithm. - Highlights: ► Two objectives, one for contrast enhancement and another for feature preservation. ► Quality improvement of low resolution nuclear track images. ► Replacing the cost of a high quality imaging system with computation cost. ► A Robust optimization method for problems of nuclear track images analysis. ► Achieving a method for more accurate accumulate dose measurements

  6. Quantification winter wheat LAI with HJ-1CCD image features over multiple growing seasons

    Science.gov (United States)

    Li, Xinchuan; Zhang, Youjing; Luo, Juhua; Jin, Xiuliang; Xu, Ying; Yang, Wenzhi

    2016-02-01

    Remote sensing images are widely used to map leaf area index (LAI) continuously over landscape. The objective of this study is to explore the ideal image features from Chinese HJ-1 A/B CCD images for estimating winter wheat LAI in Beijing. Image features were extracted from such images over four seasons of winter wheat growth, including five vegetation indices (VIs), principal components (PC), tasseled cap transformations (TCT) and texture parameters. The LAI was significantly correlated with the near-infrared reflectance band, five VIs [normalized difference vegetation index, enhanced vegetation index (EVI), modified nonlinear vegetation index (MNLI), optimization of soil-adjusted vegetation index, and ratio vegetation index], the first principal component (PC1) and the second TCT component (TCT2). However, these image features cannot significantly improve the estimation accuracy of winter wheat LAI in conjunction with eight texture measures. To determine the few ideal features with the best estimation accuracy, partial least squares regression (PLSR) and variable importance in projection (VIP) were applied to predict LAI values. Four remote sensing features (TCT2, PC1, MNLI and EVI) were chosen based on VIP values. The result of leave-one-out cross-validation demonstrated that the PLSR model based on these four features produced better result than the ten features' model, throughout the whole growing season. The results of this study suggest that selecting a few ideal image features is sufficient for LAI estimation.

  7. A Combined Method of Fractal and GLCM Features for MRI and CT Scan Images Classification

    OpenAIRE

    Redouan Korchiyne; Sidi Mohamed Farssi; Abderrahmane Sbihi; Rajaa Touahni; Mustapha Tahiri Alaoui

    2014-01-01

    Fractal analysis has been shown to be useful in image processing for characterizing shape and gray-scale complexity. The fractal feature is a compact descriptor used to give a numerical measure of the degree of irregularity of the medical images. This descriptor property does not give ownership of the local image structure. In this paper, we present a combination of this parameter based on Box Counting with GLCM Features. This powerful combination has proved good results especiall...

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

    International Nuclear Information System (INIS)

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

  9. 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.

  10. Abdominal Manifestations of Lymphoma: Spectrum of Imaging Features

    International Nuclear Information System (INIS)

    Non-Hodgkin and Hodgkin lymphomas frequently involve many structures in the abdomen and pelvis. Extranodal disease is more common with Non-Hodgkin's lymphoma than with Hodgkin's lymphoma. Though it may be part of a systemic lymphoma, single onset of nodal lymphoma is not rare. Extranodal lymphoma has been described in virtually every organ and tissue. In decreasing order of frequency, the spleen, liver, gastrointestinal tract, pancreas, abdominal wall, genitourinary tract, adrenal, peritoneal cavity, and biliary tract are involved. The purpose of this review is to discuss and illustrate the spectrum of appearances of nodal and extranodal lymphomas, including AIDS-related lymphomas, in the abdominopelvic region using a multimodality approach, especially cross-sectional imaging techniques. The most common radiologic patterns of involvement are illustrated. Familiarity with the imaging manifestations that are diagnostically specific for lymphoma is important because imaging plays an important role in the noninvasive management of disease

  11. Bioluminescence: a versatile technique for imaging cellular and molecular features

    Science.gov (United States)

    Paley, Miranda A.

    2016-01-01

    Bioluminescence is a ubiquitous imaging modality for visualizing biological processes in vivo. This technique employs visible light and interfaces readily with most cell and tissue types, making it a versatile technology for preclinical studies. Here we review basic bioluminescence imaging principles, along with applications of the technology that are relevant to the medicinal chemistry community. These include noninvasive cell tracking experiments, analyses of protein function, and methods to visualize small molecule metabolites. In each section, we also discuss how bioluminescent tools have revealed insights into experimental therapies and aided drug discovery. Last, we highlight the development of new bioluminescent tools that will enable more sensitive and multi-component imaging experiments and, thus, expand our broader understanding of living systems.

  12. Biomedical image representation and classification using an entropy weighted probabilistic concept feature space

    Science.gov (United States)

    Rahman, Md Mahmudur; Antani, Sameer K.; Demner-Fushman, Dinna; Thoma, George R.

    2014-03-01

    This paper presents a novel approach to biomedical image representation for classification by mapping image regions to local concepts and represent images in a weighted entropy based probabilistic feature space. In a heterogeneous collection of medical images, it is possible to identify specific local patches that are perceptually and/or semantically distinguishable. The variation of these patches is effectively modeled as local concepts based on their low-level features as inputs to a multi-class SVM classifier. The probability of occurrence of each concept in an image is measured by spreading and normalizing each region's class confidence score based on the probabilistic output of the classifier. Furthermore, importance of concepts is measured as Shannon entropy based on pixel values of image patches and used to refine the feature vector to overcome the limitation of the "TF-IDF"- based weighting. In addition, to take the localization information of concepts into consideration, each image each segmented into five overlapping regions and local concept feature vectors are generated from those regions to finally obtain a combined semi-global feature vector. A systematic evaluation of image classification on two biomedical image data sets demonstrates improvement of more than 10% for the proposed feature representation approach compared to the commonly used low level and visual word-based approaches.

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

    International Nuclear Information System (INIS)

    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.

  14. Use of Wavelet-Fuzzy Features with PCA for Image Registration

    Directory of Open Access Journals (Sweden)

    Safia Sadruddin

    2014-01-01

    Full Text Available In this paper, we discuss an Image Registration system based on neural network, which uses Wavelet-fuzzy features of an image. In this system, Wavelet-fuzzy features are extracted from an image and then reduced using Principal Component Analysis (PCA. The reduced feature set is then used for training the neural network for image registration. The geometric transformation between the reference and sensed image sets are evaluated using affine transformation parameters. The trained neural network produces registration parameters (translation, rotation and scaling with respect to reference and sensed image. Two parameters namely Mean Absolute Registration Error and Mutual Information are used as evaluation parameters. Experimentally, we show that the proposed technique for image registration is accurate and robust for distorted and noisy inputs.

  15. 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.

  16. The Machine Recognition for Population Feature of Wheat Images Based on BP Neural Network

    Institute of Scientific and Technical Information of China (English)

    LI Shao-kun; SUO Xing-mei; BAI Zhong-ying; QI Zhi-li; Liu Xiao-hong; GAO Shi-ju; ZHAO Shuang-ning

    2002-01-01

    Recognition and analysis of dynamic information about population images during wheat growth periods can be taken for the base of quantitative diagnosis for wheat growth. A recognition system based on self-learning BP neural network for feature data of wheat population images, such as total green areas and leaves areas was designed in this paper. In addition, some techniques to create favorable conditions for image recognition was discussed, which were as follows: (1) The method of collecting images by a digital camera and assistant equipment under natural conditions in fields. (2) An algorithm of pixei labeling was used to segment image and extract feature. (3)A high pass filter based on Laplacian was used to strengthen image information. The results showed that the ANN system was availability for image recognition of wheat population feature.

  17. Herschel and SCUBA-2 imaging and spectroscopy of a bright, lensed submillimetre galaxy at z = 2.3

    OpenAIRE

    Ivison, R. J.; Swinbank, A. M.; Swinyard, B.; Smail, I.; Pearson, C. P.; Rigopoulou, D.; Polehampton, E.; Baluteau, J. -P.; Barlow, M.J.; Blain, A. W.; Bock, J.; Clements, D.L.; Coppin, K.; Cooray, A.; Danielson, A.

    2010-01-01

    We present a detailed analysis of the far-infrared (-IR) properties of the bright, lensed, z = 2.3, submillimetre-selected galaxy (SMG), SMM J2135-0102 (hereafter SMM J2135), using new observations with Herschel, SCUBA-2 and the Very Large Array (VLA). These data allow us to constrain the galaxy's spectral energy distribution (SED) and show that it has an intrinsic rest-frame 8-1000-μm luminosity, Lbol, of (2.3±0.2) × 1012 and a likely star-formation rate (SFR) of ~400 yr-1. The galaxy sits...

  18. Malformations of cortical development:3T magnetic resonance imaging features

    Institute of Scientific and Technical Information of China (English)

    Bilal; Battal; Selami; Ince; Veysel; Akgun; Murat; Kocaoglu; Emrah; Ozcan; Mustafa; Tasar

    2015-01-01

    Malformation of cortical development(MCD) is a term representing an inhomogeneous group of central nervous system abnormalities, referring particularly to embriyological aspect as a consequence of any of the three developmental stages, i.e., cell proliferation, cell migration and cortical organization. These include cotical dysgenesis, microcephaly, polymicrogyria, schizencephaly, lissencephaly, hemimegalencephaly, heterotopia and focal cortical dysplasia. Since magnetic resonance imaging is the modality of choice that best identifies the structural anomalies of the brain cortex, we aimed to provide a mini review of MCD by using 3T magnetic resonance scanner images.

  19. A new method to extract stable feature points based on self-generated simulation images

    Science.gov (United States)

    Long, Fei; Zhou, Bin; Ming, Delie; Tian, Jinwen

    2015-10-01

    Recently, image processing has got a lot of attention in the field of photogrammetry, medical image processing, etc. Matching two or more images of the same scene taken at different times, by different cameras, or from different viewpoints, is a popular and important problem. Feature extraction plays an important part in image matching. Traditional SIFT detectors reject the unstable points by eliminating the low contrast and edge response points. The disadvantage is the need to set the threshold manually. The main idea of this paper is to get the stable extremums by machine learning algorithm. Firstly we use ASIFT approach coupled with the light changes and blur to generate multi-view simulated images, which make up the set of the simulated images of the original image. According to the way of generating simulated images set, affine transformation of each generated image is also known. Instead of the traditional matching process which contain the unstable RANSAC method to get the affine transformation, this approach is more stable and accurate. Secondly we calculate the stability value of the feature points by the set of image with its affine transformation. Then we get the different feature properties of the feature point, such as DOG features, scales, edge point density, etc. Those two form the training set while stability value is the dependent variable and feature property is the independent variable. At last, a process of training by Rank-SVM is taken. We will get a weight vector. In use, based on the feature properties of each points and weight vector calculated by training, we get the sort value of each feature point which refers to the stability value, then we sort the feature points. In conclusion, we applied our algorithm and the original SIFT detectors to test as a comparison. While in different view changes, blurs, illuminations, it comes as no surprise that experimental results show that our algorithm is more efficient.

  20. Adaptive Feature Selection and Extraction Approaches for Image Retrieval based on Region

    Directory of Open Access Journals (Sweden)

    Haiyu Song

    2010-02-01

    Full Text Available Image retrieval based on region is one of the most promising and active research directions in recent year's CBIR, while region segmentation, feature selection and feature extraction of region are key issues. However, the existing approaches always adopt a uniform approach of segmentation and feature extraction for all images in the same system. In this paper, we propose adaptive image segmentation and feature extraction approach according to different category image for image retrieval system. To improve performance, we propose adaptive segmentation approach according to different category image. Textured image is segmented by Gaussian Mixture Models (GMM, while non-textured image is segmented by our proposed block-based normalized cut. To accurately describe feature of region, we propose weight assignment method for centroid pixel and its neighbor by convolution with normal distribution when image segmentation by GMM. To improve generalization, we propose adaptive number of Fourier descriptors of shape signature which depends on the energy distribution of Fourier descriptors, instead of fixed number by experience. To simply and efficiently describe the spatial relationships of multi-object or multi-region in same image, we apply simplified topological relationships. The experiments demonstrate that proposed approaches are superior to the traditional approaches.

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

    International Nuclear Information System (INIS)

    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

  2. MR imaging features of foot involvement in ankylosing spondylitis

    International Nuclear Information System (INIS)

    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

  3. 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

  4. Magnetic resonance imaging features of papillary breast lesions

    Energy Technology Data Exchange (ETDEWEB)

    Sarica, Ozgur, E-mail: sozgur@yahoo.com; Uluc, Fatih, E-mail: drfatihuluc@yahoo.com; Tasmali, Deniz, E-mail: deniztasmali@hotmail.com

    2014-03-15

    Purpose: This study was aimed to assess the role of magnetic resonance imaging (MRI) in the evaluation of the papillary lesions of the breast and their morphological relationship with the mammary ducts. The potential diagnostic contributory role of ductal oriented protocols to conventional dynamic magnetic resonance examination was also explored. Materials and methods: Retrospective data were collected from 46 patients who had been diagnosed with papillary breast lesions and undergone magnetic resonance examination. The presence of dilated ducts and their morphological relation with the lesion were recorded. Lesions were classified as follows: papilloma, papillomatosis and malignant papillary lesion. Statistical difference between groups was studied for each morphological and dynamic lesion characteristic. Results: Dilated ducts and characteristics of intraductal material can be identified by magnetic resonance imaging. Certain MRI findings such as a mass with crescentic peripheral fluid or focal intraductal mass on T2 weighted images may suggest the presence of an intraductal/papillary lesion. In this respect, non-fatsat T2 weighted images appear particularly useful. There was a significant difference between papilloma and papillomatosis with regard to segmental and heterogeneous contrast enhancement (p < 0.05 for both comparisons). In addition, there was a significant difference between papillomas and carcinomas with regard to homogenous, heterogeneous and segmental contrast enhancement (p < 0.05 for all). On the other hand, papillomatosis and carcinoma did not differ significantly in terms of any of the morphological or dynamical MR criteria compared. Conclusion: Papillary lesions can be detected by MRI. Despite some overlaps in MRI findings between carcinoma, papilloma and papillomatosis, MRI may help differentiate these lesions. Major benefit of retroareolar imaging appears to arise from its ability to demonstrate ductal relation and extension of contrast

  5. MISD Compiler for Feature Vector Computation in Serial Input Images

    Directory of Open Access Journals (Sweden)

    Lucas Leiva

    2011-06-01

    Full Text Available In this paper a compiler capable of generate Multiple Instruction Single Data (MISD architectures for feature vector calculation is presented. The input is a high-level language, avoiding to developers to involve in low level design. Instead, the output is expressed in a Hardware Description Language (HDL, and can be used for FPGA configuration. A FPGA is a programmable device which allows parallelism, increasing the system speed up. The tool is intended to use in feature vector calculation of region of interest (ROI for real time video applications. These ROIs arrives serially. Also, is possible to evaluate the vector in design time, allowing system prototyping. The compiler optimizes the response time and the number of registers required to meet real time constraints.

  6. Result Analysis on Content Base Image Retrieval using Combination of Color, Shape and Texture Features

    Directory of Open Access Journals (Sweden)

    Neha Jain, Sumit Sharma, Ravi Mohan Sairam

    2012-12-01

    Full Text Available Image retrieval based on color, texture and shape is an emerging and wide area of research scope. In this paper we present a novel framework for combining all the three i.e. color, texture and shape information, and achieve higher retrieval efficiency using dominant color feature. The image and its complement are partitioned into non-overlapping tiles of equal size. The features drawn from conditional co-occurrence histograms between the image tiles and corresponding complement tiles, in RGB color space, serve as local descriptors of color, shape and texture. We apply the integration of the above combination, then we cluster based on alike properties. Based on five dominant colors we retrieve the similar images. We also create the histogram of edges. Image information is captured in terms of edge images computed using Gradient Vector Flow fields. Invariant moments are then used to record the shape features. The combination of the color, shape and texture features between image and its complement in conjunction with the shape features provide a robust feature set for image retrieval. The experimental results demonstrate the efficacy of the method.

  7. In-situ Microwave Brightness Temperature Variability from Ground-based Radiometer Measurements at Dome C in Antarctica Induced by Wind-formed Features

    Science.gov (United States)

    Royer, A.; Picard, G.; Arnaud, L.; Brucker, L.; Fily, M..

    2014-01-01

    Space-borne microwave radiometers are among the most useful tools to study snow and to collect information on the Antarctic climate. They have several advantages over other remote sensing techniques: high sensitivity to snow properties of interest (temperature, grain size, density), subdaily coverage in the polar regions, and their observations are independent of cloud conditions and solar illumination. Thus, microwave radiometers are widely used to retrieve information over snow-covered regions. For the Antarctic Plateau, many studies presenting retrieval algorithms or numerical simulations have assumed, explicitly or not, that the subpixel-scale heterogeneity is negligible and that the retrieved properties were representative of whole pixels. In this presentation, we investigate the spatial variations of brightness temperature over arange of a few kilometers in the Dome C area (Antarctic Plateau).

  8. Feature Recognition of Low-resolution Fiber Image

    Institute of Scientific and Technical Information of China (English)

    YU Su-ping; ZENG Pei-feng; WU Xiong-ying; CHEN Jian-ping

    2006-01-01

    The interpolatory edge operator is applied to the recognition of cotton and ramie fibers. Its performance is studied in comparison with the Canny edge operator in the fiber's edge detection for cross-sectional image. The input image is interpolated other than Gaussian function smoothing. The quality of edge output is improved by the interpolatory edge operator. It produces edge output with good continuity for low-resolution input. The fine edge output, such as crossmarkings, can be distinguished clearly, so the interpolatory edge operator is suitable for the study of cotton and ramie fibers. Furthermore, the application of the interpolatory edge operator can cut the hardware cost, reduce the storage and speed up the data transmission.

  9. Spinal dural arteriovenous fistula: Imaging features and its mimics

    Energy Technology Data Exchange (ETDEWEB)

    Jeog, Ying; Ting, David Yen; Hsu, Hui Ling; Huang, Yen Lin; Chen, Chi Jen; Tseng, Ting Chi [Dept. of Radiology, aipei Medical University-Shuang Ho Hospital, New Taipei City, Taiwan (China)

    2015-10-15

    Spinal dural arteriovenous fistula (SDAVF) is the most common spinal vascular malformation, however it is still rare and underdiagnosed. Magnetic resonance imaging findings such as spinal cord edema and dilated and tortuous perimedullary veins play a pivotal role in the confirmation of the diagnosis. However, spinal angiography remains the gold standard in the diagnosis of SDAVF. Classic angiographic findings of SDAVF are early filling of radicular veins, delayed venous return, and an extensive network of dilated perimedullary venous plexus. A series of angiograms of SDAVF at different locations along the spinal column, and mimics of serpentine perimedullary venous plexus on MR images, are demonstrated. Thorough knowledge of SDAVF aids correct diagnosis and prevents irreversible complications.

  10. Spinal dural arteriovenous fistula: Imaging features and its mimics

    International Nuclear Information System (INIS)

    Spinal dural arteriovenous fistula (SDAVF) is the most common spinal vascular malformation, however it is still rare and underdiagnosed. Magnetic resonance imaging findings such as spinal cord edema and dilated and tortuous perimedullary veins play a pivotal role in the confirmation of the diagnosis. However, spinal angiography remains the gold standard in the diagnosis of SDAVF. Classic angiographic findings of SDAVF are early filling of radicular veins, delayed venous return, and an extensive network of dilated perimedullary venous plexus. A series of angiograms of SDAVF at different locations along the spinal column, and mimics of serpentine perimedullary venous plexus on MR images, are demonstrated. Thorough knowledge of SDAVF aids correct diagnosis and prevents irreversible complications

  11. Precoccygeal epidermal inclusion cyst: ultrasound and MR imaging features.

    OpenAIRE

    Halefoglu, A.M.; Sen, E Y

    2012-01-01

    In this case report, we are presenting a 33 year-old pregnant woman who suffered from pelvic and coccygeal pain. Her medical examination and laboratory tests were found within normal limits. In order to explain her pain, initially a pelvic ultrasound was performed which revealed a huge hypoechoic cystic mass in the precoccygeal-presacral region. She then underwent a pelvic magnetic resonance imaging (MRI) examination in order to better delineate the characteristics and extension of this huge ...

  12. Featured Image: Violent History of the Toothbrush Cluster

    Science.gov (United States)

    Kohler, Susanna

    2016-03-01

    This stunning composite image shows the components of the galaxy cluster RX J0603.3+4214, located at a redshift of z=0.225. This image contains Chandra X-ray data (red), radio data from the Giant Metrewave Radio Telescope (green), and optical from the Subaru Telescope (background). The shape of the enormous (6.5 million light-years across!) radio relic, shown in green, gives this collection of galaxies its nickname: the Toothbrush Cluster. A team of scientists led by Myungkook James Jee (Yonsei University and University of California, Davis) used Hubble and Subaru to study weak gravitational lensing by the Toothbrush Cluster, in order to determine how the clusters mass is distributed. Jee and collaborators found that most of the dark-matter mass is located in two large clumps on a north-south axis (shown by the white contours overlaid on the image), suggesting that the Toothbrush Cluster is the result of a past merger between two clusters. This violent merger is likely what caused the enormous Toothbrush radio relic. Check out the paper below for more information!CitationM. James Jee et al 2016 ApJ 817 179. doi:10.3847/0004-637X/817/2/179

  13. Image retrieval system based on machine learning and using color features

    OpenAIRE

    Demšar, Janez; Radolović, Dragan; Solina, Franc

    2014-01-01

    We describe an interactive system for content based image retrieval. The system presents the user with 15 randomly selected images from the database. The user grades the images with one of five possible grades (YES, yes, neutral, no, NO) according to what he is looking for. The system returns the first 15 images with the highest probability of YES grade. The attributes used are a combination of color features. Three different machine learning techniques are compared.

  14. Mathematical morphology-based approach to the enhancement of morphological features in medical images

    OpenAIRE

    Kimori, Yoshitaka

    2011-01-01

    Background Medical image processing is essential in many fields of medical research and clinical practice because it greatly facilitates early and accurate detection and diagnosis of diseases. In particular, contrast enhancement is important for optimal image quality and visibility. This paper proposes a new image processing method for enhancing morphological features of masses and other abnormalities in medical images. Method The proposed method involves two steps: (1) selective extraction o...

  15. Advantage in Bright-blood and Black-blood Magnetic Resonance Imaging with High-resolution for Analysis of Carotid Atherosclerotic Plaques

    Directory of Open Access Journals (Sweden)

    Mei Li

    2015-01-01

    Full Text Available Background: About 50% of the cerebral ischemia events are induced by intracranial and extracranial atherosclerosis. This study aimed to evaluate the feasibility and accuracy for displaying atherosclerotic plaques in carotid arteries and analyzing their ingredients by using high-resolution new magnetic resonance imaging (MRI techniques. Methods: Totally, 49 patients suspected of extracranial carotid artery stenosis were subjected to cranial MRI scan and magnetic resonance angiography (MRA examination on carotid arteries, and high-resolution bright-blood and black-blood MRI analysis was carried out within 1 week. Digital subtraction angiography (DSA examination was carried out for 16 patients within 1 month. Results: Totally, 103 plaques were detected in the 49 patients, which were characterized by localized or diffusive thickening of the vessel wall, with the intrusion of crescent-shaped abnormal signal into lumens. Fibrous cap was displayed as isointensity in T1-weighted image (T1WI and hyperintensities in proton density weighted image (PDWI and T2-weighted image (T2WI, lipid core was displayed as isointensity or slight hyperintensities in T1WI, isointensity, hyperintensities or hypointensity in PDWI, and hypointensity in T2WI. Calcification in plaques was detected in 11 patients. Eight patients were detected with irregular plaque surface or ulcerative plaques, which were characterized by irregular intravascular space surface in the black-blood sequences, black hypointensity band was not detected in three-dimensional time-of-flight, or the hypointensity band was not continuous, and intrusion of hyperintensities into plaques can be detected. Bright-blood and black-blood techniques were highly correlated with the diagnosis of contrast-enhanced MRA in angiostenosis degree, Rs = 0.97, P < 0.001. In comparison to DSA, the sensitivity, specificity, and accuracy of MRI diagnosis of stenosis for ≥50% were 88.9%, 100%, and 97.9%, respectively

  16. 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. PMID:27046897

  17. A PCA Based Automatic Image Categorization Approach Using Dominant Color Features

    Institute of Scientific and Technical Information of China (English)

    WUChunming; QIANHui; WANGDonghui

    2005-01-01

    Automatic Image categorization is a universal problem in area of Content-based image retrieval (CBIR). The goal of automatic image categorization is to find a mapping between images and the predefined image categories. The difficulty of this problem is that how to describe image content and incorporate low-level features into semantic categories. As a solution, we propose a Principal component analysis (PCA) based approach. This approach assumes that the images in the same semantic category have the similar spatial distribution of color components and treats the images in the same category as a linear combination of a fixed set of dominant color blocks with special textural information. A three-step algorithm is designed: (1) extracting Dominant colors (DC) of images, which describe the major color information in an image; (2) Establishing a feature space based on DC blocks and its textural information; (3) using PCA to reduce dimensionality of feature space and using the basis vectors to categorize images. An experimental database containing nine categories including cars, flowers, houses, portraits, fish, bark, sunshine, leaves and fresco is constructed to test the algorithm based on our image categorization approach. The results show that this approach is effective and a reasonable compromise between accuracy and speed in practice.

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

    Energy Technology Data Exchange (ETDEWEB)

    Ziereisen, France; Damry, Nash; Christophe, Catherine [Queen Fabiola Children' s University Hospital, Department of Radiology, Brussels (Belgium); Dan, Bernard [Queen Fabiola Children' s University Hospital, Department of Neurology, Brussels (Belgium); Azzi, Nadira; Ferster, Alina [Queen Fabiola Children' s University Hospital, Department of Paediatrics, Brussels (Belgium)

    2006-03-15

    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.)

  19. Single-system ureteroceles in infants and children: imaging features

    International Nuclear Information System (INIS)

    Purpose. The purpose of this manuscript is to describe the clinical and imaging findings in children who have single-system ureteroceles.Materials and methods. We reviewed the urology records and imaging studies in 32 consecutive infants and children who were diagnosed in our department with single-system ureteroceles.Results. There were 35 ureteroceles in the 32 patients - 29 were unilateral (14 right-sided, 15 left-sided) and 3 were bilateral. Twenty-five patients were boys (78 %) and 7 girls. Mean age at presentation was 0.7 years (0-9.2 years). Prenatally detected hydronephrosis or cystic renal dysplasia was the most common presentation (24 patients). Four presented with urinary infection, 2 with abdominal mass, 1 had myelomeningocele, and 1 had hypospadias. Three patients also had multiple non-urologic, congenital anomalies. Thirty-three ureteroceles were intravesical, and 2 were ectopic to the bladder neck. Twenty-four ureteroceles were associated with ipsilateral hydroureteronephrosis and 10 with ipsilateral multicystic dysplastic kidney. One patient had a normal ipsilateral kidney and a contralateral multicystic dysplastic kidney. The ureterocele was identified on at least one imaging study in each patient. Sixteen ureteroceles (47 %) everted at VCUG, mimicking paraureteral diverticula. Other variations included ureterocele prolapse and inadvertent ureterocele catheterization (1 each).Conclusions. Single-system ureterocele is an important, although uncommon cause of hydronephrosis and renal dysplasia in infants and children. Single-system ureterocele is distinguished clinically from the more common duplex-system ureterocele by its frequent occurrence in boys and its association with multicystic dysplastic kidney. Because these ureteroceles are frequently small and have a propensity to evert at VCUG, they can be mistaken for paraureteral diverticula. (orig.)

  20. Single-system ureteroceles in infants and children: imaging features

    Energy Technology Data Exchange (ETDEWEB)

    Zerin, J.M.; Baker, D.R. [Dept. of Radiology, Indiana University Medical Center, James Whitcomb Riley Hospital for Children, Indianapolis, IN (United States); Casale, J.A. [Dept. of Urology, Indiana University Medical Center, James Whitcomb Riley Hospital for Children, Indianapolis, IN (United States)

    2000-03-01

    Purpose. The purpose of this manuscript is to describe the clinical and imaging findings in children who have single-system ureteroceles.Materials and methods. We reviewed the urology records and imaging studies in 32 consecutive infants and children who were diagnosed in our department with single-system ureteroceles.Results. There were 35 ureteroceles in the 32 patients - 29 were unilateral (14 right-sided, 15 left-sided) and 3 were bilateral. Twenty-five patients were boys (78 %) and 7 girls. Mean age at presentation was 0.7 years (0-9.2 years). Prenatally detected hydronephrosis or cystic renal dysplasia was the most common presentation (24 patients). Four presented with urinary infection, 2 with abdominal mass, 1 had myelomeningocele, and 1 had hypospadias. Three patients also had multiple non-urologic, congenital anomalies. Thirty-three ureteroceles were intravesical, and 2 were ectopic to the bladder neck. Twenty-four ureteroceles were associated with ipsilateral hydroureteronephrosis and 10 with ipsilateral multicystic dysplastic kidney. One patient had a normal ipsilateral kidney and a contralateral multicystic dysplastic kidney. The ureterocele was identified on at least one imaging study in each patient. Sixteen ureteroceles (47 %) everted at VCUG, mimicking paraureteral diverticula. Other variations included ureterocele prolapse and inadvertent ureterocele catheterization (1 each).Conclusions. Single-system ureterocele is an important, although uncommon cause of hydronephrosis and renal dysplasia in infants and children. Single-system ureterocele is distinguished clinically from the more common duplex-system ureterocele by its frequent occurrence in boys and its association with multicystic dysplastic kidney. Because these ureteroceles are frequently small and have a propensity to evert at VCUG, they can be mistaken for paraureteral diverticula. (orig.)

  1. Clinical and CT imaging features of abdominal fat necrosis

    International Nuclear Information System (INIS)

    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)

  2. Differential diagnostic features of the radionuclide scrotal image

    Energy Technology Data Exchange (ETDEWEB)

    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. Imaging features of type-B Niemann-Pick disease

    Energy Technology Data Exchange (ETDEWEB)

    Muntaner, L. [Dept. of Radiology, Son Dureta University Hospital, Palma de Mallorca (Spain); Galmes, A. [Dept. of Hematology, Son Dureta University Hospital, Palma de Mallorca (Spain); Chabas, A. [Instituto de Bioquimica Clinica Corporacio Sanitaria, Barcelona (Spain); Herrera, M. [Dept. of Radiology, Son Dureta University Hospital, Palma de Mallorca (Spain)

    1997-04-01

    We report two cases of a mild form of type-B Niemann-Pick disease manifesting as an adult-onset chronic non-neuropathic clinical picture. Femoral T1- and T2-weighted low-intensity non-enhancing coarse bone marrow pattern was evident on femoral MR associated with splenic hypodense nodule(s) on abdominal CT. The role of imaging is discussed in relation to current techniques of confirmation of this entity based on demonstration of lipid-laden cells within marrow aspirates (which are often sea-blue histiocytes) and sphingomyelinase assay of cultured skin fibroblasts. (orig.). With 2 figs.

  4. Imaging features of type-B Niemann-Pick disease

    International Nuclear Information System (INIS)

    We report two cases of a mild form of type-B Niemann-Pick disease manifesting as an adult-onset chronic non-neuropathic clinical picture. Femoral T1- and T2-weighted low-intensity non-enhancing coarse bone marrow pattern was evident on femoral MR associated with splenic hypodense nodule(s) on abdominal CT. The role of imaging is discussed in relation to current techniques of confirmation of this entity based on demonstration of lipid-laden cells within marrow aspirates (which are often sea-blue histiocytes) and sphingomyelinase assay of cultured skin fibroblasts. (orig.). With 2 figs

  5. Differential diagnostic features of the radionuclide scrotal image

    International Nuclear Information System (INIS)

    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

  6. 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.

  7. Imaging features of ductal plate malformations in adults

    International Nuclear Information System (INIS)

    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.

  8. Acute toxic encephalopathies: CT and MR imaging features

    International Nuclear Information System (INIS)

    An endless variety of toxins can cause degenerative brain lesions both by chronic use of small amounts and by acute exposures from industrial accidents or suicide attempts. The more commonly occurring toxins encountered clinically include carbon monoxide, cyanide, methanol, and ethylene glycol. CT and MR imaging are of great importance in the assessment of the comatose patient. Some of these toxins have a propensity for selective bilateral and symmetric involvement of the basal ganglia as well as the white matter. CT and MR can demonstrate the extent and distribution of the morphologic brain changes

  9. Automatic classification of hepatocellular carcinoma images based on nuclear and structural features

    Science.gov (United States)

    Kiyuna, Tomoharu; Saito, Akira; Marugame, Atsushi; Yamashita, Yoshiko; Ogura, Maki; Cosatto, Eric; Abe, Tokiya; Hashiguchi, Akinori; Sakamoto, Michiie

    2013-03-01

    Diagnosis of hepatocellular carcinoma (HCC) on the basis of digital images is a challenging problem because, unlike gastrointestinal carcinoma, strong structural and morphological features are limited and sometimes absent from HCC images. In this study, we describe the classification of HCC images using statistical distributions of features obtained from image analysis of cell nuclei and hepatic trabeculae. Images of 130 hematoxylin-eosin (HE) stained histologic slides were captured at 20X by a slide scanner (Nanozoomer, Hamamatsu Photonics, Japan) and 1112 regions of interest (ROI) images were extracted for classification (551 negatives and 561 positives, including 113 well-differentiated positives). For a single nucleus, the following features were computed: area, perimeter, circularity, ellipticity, long and short axes of elliptic fit, contour complexity and gray level cooccurrence matrix (GLCM) texture features (angular second moment, contrast, homogeneity and entropy). In addition, distributions of nuclear density and hepatic trabecula thickness within an ROI were also extracted. To represent an ROI, statistical distributions (mean, standard deviation and percentiles) of these features were used. In total, 78 features were extracted for each ROI and a support vector machine (SVM) was trained to classify negative and positive ROIs. Experimental results using 5-fold cross validation show 90% sensitivity for an 87.8% specificity. The use of statistical distributions over a relatively large area makes the HCC classifier robust to occasional failures in the extraction of nuclear or hepatic trabecula features, thus providing stability to the system.

  10. NOTE: Prostate cancer multi-feature analysis using trans-rectal ultrasound images

    Science.gov (United States)

    Mohamed, S. S.; Salama, M. M. A.; Kamel, M.; El-Saadany, E. F.; Rizkalla, K.; Chin, J.

    2005-08-01

    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.

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

    International Nuclear Information System (INIS)

    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)

  12. 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.

  13. Face Recognition from Still Images to Video Sequences: A Local-Feature-Based Framework

    Directory of Open Access Journals (Sweden)

    Chen Shaokang

    2011-01-01

    Full Text Available Although automatic faces recognition has shown success for high-quality images under controlled conditions, for video-based recognition it is hard to attain similar levels of performance. We describe in this paper recent advances in a project being undertaken to trial and develop advanced surveillance systems for public safety. In this paper, we propose a local facial feature based framework for both still image and video-based face recognition. The evaluation is performed on a still image dataset LFW and a video sequence dataset MOBIO to compare 4 methods for operation on feature: feature averaging (Avg-Feature, Mutual Subspace Method (MSM, Manifold to Manifold Distance (MMS, and Affine Hull Method (AHM, and 4 methods for operation on distance on 3 different features. The experimental results show that Multi-region Histogram (MRH feature is more discriminative for face recognition compared to Local Binary Patterns (LBP and raw pixel intensity. Under the limitation on a small number of images available per person, feature averaging is more reliable than MSM, MMD, and AHM and is much faster. Thus, our proposed framework—averaging MRH feature is more suitable for CCTV surveillance systems with constraints on the number of images and the speed of processing.

  14. Learning How to Extract Rotation-Invariant and Scale-Invariant Features from Texture Images

    Directory of Open Access Journals (Sweden)

    Alexandre X. Falcão

    2008-05-01

    Full Text Available Learning how to extract texture features from noncontrolled environments characterized by distorted images is a still-open task. By using a new rotation-invariant and scale-invariant image descriptor based on steerable pyramid decomposition, and a novel multiclass recognition method based on optimum-path forest, a new texture recognition system is proposed. By combining the discriminating power of our image descriptor and classifier, our system uses small-size feature vectors to characterize texture images without compromising overall classification rates. State-of-the-art recognition results are further presented on the Brodatz data set. High classification rates demonstrate the superiority of the proposed system.

  15. A Combined Method of Fractal and GLCM Features for MRI and CT Scan Images Classification

    Directory of Open Access Journals (Sweden)

    Redouan Korchiyne

    2014-08-01

    Full Text Available Fractal analysis has been shown to be useful in image processing for characterizing shape and gray-scale complexity. The fractal feature is a compact descriptor used to give a numerical measure of the degree of irregularity of the medical images. This descriptor property does not give ownership of the local image structure. In this paper, we present a combination of this parameter based on Box Counting with GLCM Features. This powerful combination has proved good results especially in classification of medical texture from MRI and CT Scan images of trabecular bone. This method has the potential to improve clinical diagnostics tests for osteoporosis pathologies.

  16. Detecting edges in the X-ray surface brightness of galaxy clusters

    CERN Document Server

    Sanders, J S; Russell, H R; Walker, S A; Blundell, K M

    2016-01-01

    The effects of many physical processes in the intracluster medium of galaxy clusters imprint themselves in X-ray surface brightness images. It is therefore important to choose optimal methods for extracting information from and enhancing the interpretability of such images. We describe in detail a gradient filtering edge detection method that we previously applied to images of the Centaurus cluster of galaxies. The Gaussian gradient filter measures the gradient in the surface brightness distribution on particular spatial scales. We apply this filter on different scales to Chandra X-ray observatory images of two clusters with AGN feedback, the Perseus cluster and M87, and a merging system, A3667. By combining filtered images on different scales using radial filters spectacular images of the edges in a cluster are produced. We describe how to assess the significance of features in filtered images. We find the gradient filtering technique to have significant advantages for detecting many kinds of features compar...

  17. 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. PMID:27002328

  18. AN INTEGRATED FRAMEWORK BASED ON TEXTURE FEATURES, CUCKOO SEARCH AND RELEVANCE VECTOR MACHINE FOR MEDICAL IMAGE RETRIEVAL SYSTEM

    Directory of Open Access Journals (Sweden)

    Yogapriya Jaganathan

    2013-01-01

    Full Text Available As medical images are widely used in healthcare applications, Content Based Medical Image Retrieval (CBMIR system is needed for physicians to convey effective decisions to patients and for medical research students to learn imaging characteristics for their extensive research based on visual features. However the performance of the retrieval is restricted due to high feature dimensionality of visual features. To reduce the high feature dimension, an integrated approach is proposed such as Visual feature extraction, Feature selection, Feature Classification and Similarity measurements. The selected feature is texture features by using Local Binary Patterns (LBP in which extracted texture features are designed as feature vector database. Fuzzy based Cuckoo Search (FCKS techniques are applied for feature selection to reduce the high feature vector dimensionality and addresses the difficulty of feature vectors being surrounded in local feature optima also the global optimum feature position to be special for all feature cuckoo hosts. Fuzzy based Relevance Vector Machine (FRVM classification is an proficient method to customize the collections of relevant image features that would classify dimensionally determined optimized feature vectors of images. The Euclidean Distance (ED is a standard technique for similarity measurement between the query image and the image database. The proposed system is implemented on thousands of medical images and achieved a high retrieval precision and recall compared with other two methods as validated through experiments.

  19. 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.

  20. A Novel Feature Extraction Scheme for Medical X-Ray Images

    Directory of Open Access Journals (Sweden)

    Prachi.G.Bhende

    2016-02-01

    Full Text Available X-ray images are gray scale images with almost the same textural characteristic. Conventional texture or color features cannot be used for appropriate categorization in medical x-ray image archives. This paper presents a novel combination of methods like GLCM, LBP and HOG for extracting distinctive invariant features from Xray images belonging to IRMA (Image Retrieval in Medical applications database that can be used to perform reliable matching between different views of an object or scene. GLCM represents the distributions of the intensities and the information about relative positions of neighboring pixels of an image. The LBP features are invariant to image scale and rotation, change in 3D viewpoint, addition of noise, and change in illumination A HOG feature vector represents local shape of an object, having edge information at plural cells. These features have been exploited in different algorithms for automatic classification of medical X-ray images. Excellent experimental results obtained in true problems of rotation invariance, particular rotation angle, demonstrate that good discrimination can be achieved with the occurrence statistics of simple rotation invariant local binary patterns.

  1. Hybrid Feature Point Based Registration of 2D Abdominal CT Images

    Directory of Open Access Journals (Sweden)

    Asmita A. Moghe

    2010-07-01

    Full Text Available Liver lesions like abscess, cirrhosis, metastases etc usually appear globular with gray levels differing remarkably from that of the surrounding liver region but the boundaries of these lesions are poorly defined and give an approximate picture of the extent of invasion of the lesion into surrounding regions. Choice of feature points and their matching in the images under consideration is crucial and image dependent. This leads to variations in registration methods. The objective of the proposed technique is to enhance registration for such abdominal CT images with the use of invariant points lying on the boundaries of lesions and the lesion centroids as the feature points. This paper uses a combination of hull points and centroids as feature points to register the images and compares results with those obtained by registration using only centroids as feature points. The outer margins of lesions become more sharply defined which helps in improving diagnostic accuracy.

  2. 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

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

    International Nuclear Information System (INIS)

    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.

  4. 基于图像重建的Zernike矩形状特征评价%Image Zernike Moments Shape Feature Evaluation Based on Image Reconstruction

    Institute of Scientific and Technical Information of China (English)

    刘茂福; 何炎祥; 叶斌

    2007-01-01

    The evaluation approach to the accuracy of the image feature descriptors plays an important role in image feature extraction. We point out that the image shape feature can be described by the Zernike moments set while briefly introducing the basic concept of the Zernike moment. After talking about the image reconstruction technique based on the inverse transformation of Zernike moment, the evaluation approach to the accuracy of the Zernike moments shape feature via the dissimilarity degree and the reconstruction ratio between the original image and the reconstructed image is proposed. The experiment results demonstrate the feasibility of this evaluation approach to image Zernike moments shape feature.

  5. Unsupervised Skin cancer detection by combination of texture and shape features in dermoscopy images

    Directory of Open Access Journals (Sweden)

    Hamed aghapanah rudsari

    2014-05-01

    Full Text Available In this paper a novel unsupervised feature extraction method for detection of melanoma in skin images is presented. First of all, normal skin surrounding the lesion is removed in a segmentation process. In the next step, some shape and texture features are extracted from the output image of the first step: GLCM, GLRLM, the proposed directional-frequency features, and some parameters of Ripplet transform are used as texture features; Also, NRL features and Zernike moments are used as shape features. Totally, 63 texture features and 31 shape features are extracted. Finally, the number of extracted features is reduced using PCA method and a proposed method based on Fisher criteria. Extracted features are classified using the Perceptron Neural Networks, Support Vector Machine, 4-NN, and Naïve Bayes. The results show that SVM has the best performance. The proposed algorithm is applied on a database that consists of 160 labeled images. The overall results confirm the superiority of the proposed method in both accuracy and reliability over previous works.

  6. Blind image quality assessment using joint statistics of gradient magnitude and Laplacian features.

    Science.gov (United States)

    Xue, Wufeng; Mou, Xuanqin; Zhang, Lei; Bovik, Alan C; Feng, Xiangchu

    2014-11-01

    Blind image quality assessment (BIQA) aims to evaluate the perceptual quality of a distorted image without information regarding its reference image. Existing BIQA models usually predict the image quality by analyzing the image statistics in some transformed domain, e.g., in the discrete cosine transform domain or wavelet domain. Though great progress has been made in recent years, BIQA is still a very challenging task due to the lack of a reference image. Considering that image local contrast features convey important structural information that is closely related to image perceptual quality, we propose a novel BIQA model that utilizes the joint statistics of two types of commonly used local contrast features: 1) the gradient magnitude (GM) map and 2) the Laplacian of Gaussian (LOG) response. We employ an adaptive procedure to jointly normalize the GM and LOG features, and show that the joint statistics of normalized GM and LOG features have desirable properties for the BIQA task. The proposed model is extensively evaluated on three large-scale benchmark databases, and shown to deliver highly competitive performance with state-of-the-art BIQA models, as well as with some well-known full reference image quality assessment models. PMID:25216482

  7. Digital Library ImageRetrieval usingScale Invariant Feature and Relevance Vector Machine

    Directory of Open Access Journals (Sweden)

    Hongtao Zhang

    2014-10-01

    Full Text Available With the advance of digital library, the digital content develops with rich information connotation. Traditional information retrieval methods based on external characteristic and text description are unable to sufficientlyreveal and express the substance and semantic relation of multimedia information, and unable to fully reveal and describe the representative characteristics of information. Because of the abundant connotation of image content and the people’s abstract subjectivity in studying image content, the visual feature of the image is difficult to be described by key words. Therefore, this method not always can meet people’s needs, and the study of digital library image retrieval technique based on content is important to both academic research and application. At present, image retrieval methods are mainly based on the text and content, etc. But these existing algorithms have shortages, such as large errors and slow speeds. Motivated by the above fact, we in this paper propose a new approach based on relevance vector machine (RVM. The proposed approach first extracts the patch-level scale invariant image feature (SIFT, and then constructs the global features for images. The image feature is then delivered into RVM for retrieval. We evaluate the proposed approach on Corel dataset. The experimental result shows that the proposed method in this text has high accuracy when retrieves images.

  8. An Optimized Feature Selection for Image Classification Based on SVM-ACO

    OpenAIRE

    Priyanka Dhasal; Shiv Shakti Shrivastava; Hitesh Gupta; Parmalik Kumar

    2012-01-01

    Multi- class classification plays an import role in image classification. Multi-class classification used different classifier for the classification of data, such as binary classifier and support vector machine. In this dissertation we proposed a feature sampling technique of image classification. Our sampling technique optimized the feature selection process and reduced the unclassified region in multi-class classification. For the process of optimization we used ant colony optimization alg...

  9. Extraction of Geometric Features of Wear Particles in Color Ferrograph Images Based on RGB Color Space

    Institute of Scientific and Technical Information of China (English)

    CHEN Gui-ming; WANG Han-gong; ZHANG Bao-jun; PAN Wei

    2003-01-01

    This paper analyzes the potential color formats of ferrograph images, and presents the algorithms of converting the formats to RGB(Red, Green, Blue) color space. Through statistical analysis of wear par-ticles' geometric features of color ferrograph images in the RGB color space, we give the differences of ferro-graph wear panicles' geometric features among RGB color spaces and gray scale space, and calculate their respective distributions.

  10. A new approach to modeling the influence of image features on fixation selection in scenes

    OpenAIRE

    Nuthmann, Antje; Einhäuser, Wolfgang

    2015-01-01

    Which image characteristics predict where people fixate when memorizing natural images? To answer this question, we introduce a new analysis approach that combines a novel scene-patch analysis with generalized linear mixed models (GLMMs). Our method allows for (1) directly describing the relationship between continuous feature value and fixation probability, and (2) assessing each feature's unique contribution to fixation selection. To demonstrate this method, we estimated the relative contri...

  11. Automatic Target Recognition in Synthetic Aperture Sonar Images Based on Geometrical Feature Extraction

    OpenAIRE

    J. Del Rio Vera; Coiras, E.; Groen, J; Evans, B.

    2009-01-01

    This paper presents a new supervised classification approach for automated target recognition (ATR) in SAS images. The recognition procedure starts with a novel segmentation stage based on the Hilbert transform. A number of geometrical features are then extracted and used to classify observed objects against a previously compiled database of target and non-target features. The proposed approach has been tested on a set of 1528 simulated images created by the NURC SIGMAS sonar model, achieving...

  12. Automatic Target Recognition in Synthetic Aperture Sonar Images Based on Geometrical Feature Extraction

    Science.gov (United States)

    Del Rio Vera, J.; Coiras, E.; Groen, J.; Evans, B.

    2009-12-01

    This paper presents a new supervised classification approach for automated target recognition (ATR) in SAS images. The recognition procedure starts with a novel segmentation stage based on the Hilbert transform. A number of geometrical features are then extracted and used to classify observed objects against a previously compiled database of target and non-target features. The proposed approach has been tested on a set of 1528 simulated images created by the NURC SIGMAS sonar model, achieving up to 95% classification accuracy.

  13. STUDY ON THE TECHNIQUE TO DETECT TEXTURE FEATURES IN SAR IMAGES

    Institute of Scientific and Technical Information of China (English)

    Fu Yusheng; Ding Dongtao; Hou Yinming

    2004-01-01

    This letter studies on the detection of texture features in Synthetic Aperture Radar (SAR) images. Through analyzing the feature detection method proposed by Lopes, an improved texture detection method is proposed, which can not only detect the edge and lines but also avoid stretching edge and suppressing lines of the former algorithm. Experimental results with both simulated and real SAR images verify the advantage and practicability of the improved method.

  14. A Feature Subtraction Method for Image Based Kinship Verification under Uncontrolled Environments

    DEFF Research Database (Denmark)

    Duan, Xiaodong; Tan, Zheng-Hua

    The most fundamental problem of local feature based kinship verification methods is that a local feature can capture the variations of environmental conditions and the differences between two persons having a kin relation, which can significantly decrease the performance. To address this problem...... the feature distance between face image pairs with kinship and maximize the distance between non-kinship pairs. Based on the subtracted feature, the verification is realized through a simple Gaussian based distance comparison method. Experiments on two public databases show that the feature...... subtraction method outperforms or is comparable to state-of-the-art kinship verification methods. Copyright ©2015 by IEEE....

  15. Orientation Modeling for Amateur Cameras by Matching Image Line Features and Building Vector Data

    Science.gov (United States)

    Hung, C. H.; Chang, W. C.; Chen, L. C.

    2016-06-01

    With the popularity of geospatial applications, database updating is getting important due to the environmental changes over time. Imagery provides a lower cost and efficient way to update the database. Three dimensional objects can be measured by space intersection using conjugate image points and orientation parameters of cameras. However, precise orientation parameters of light amateur cameras are not always available due to their costliness and heaviness of precision GPS and IMU. To automatize data updating, the correspondence of object vector data and image may be built to improve the accuracy of direct georeferencing. This study contains four major parts, (1) back-projection of object vector data, (2) extraction of image feature lines, (3) object-image feature line matching, and (4) line-based orientation modeling. In order to construct the correspondence of features between an image and a building model, the building vector features were back-projected onto the image using the initial camera orientation from GPS and IMU. Image line features were extracted from the imagery. Afterwards, the matching procedure was done by assessing the similarity between the extracted image features and the back-projected ones. Then, the fourth part utilized line features in orientation modeling. The line-based orientation modeling was performed by the integration of line parametric equations into collinearity condition equations. The experiment data included images with 0.06 m resolution acquired by Canon EOS Mark 5D II camera on a Microdrones MD4-1000 UAV. Experimental results indicate that 2.1 pixel accuracy may be reached, which is equivalent to 0.12 m in the object space.

  16. Coronal bright points associated with minifilament eruptions

    International Nuclear Information System (INIS)

    Coronal bright points (CBPs) are small-scale, long-lived coronal brightenings that always correspond to photospheric network magnetic features of opposite polarity. In this paper, we subjectively adopt 30 CBPs in a coronal hole to study their eruptive behavior using data from the Atmospheric Imaging Assembly (AIA) and the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory. About one-quarter to one-third of the CBPs in the coronal hole go through one or more minifilament eruption(s) (MFE(s)) throughout their lifetimes. The MFEs occur in temporal association with the brightness maxima of CBPs and possibly result from the convergence and cancellation of underlying magnetic dipoles. Two examples of CBPs with MFEs are analyzed in detail, where minifilaments appear as dark features of a cool channel that divide the CBPs along the neutral lines of the dipoles beneath. The MFEs show the typical rising movements of filaments and mass ejections with brightenings at CBPs, similar to large-scale filament eruptions. Via differential emission measure analysis, it is found that CBPs are heated dramatically by their MFEs and the ejected plasmas in the MFEs have average temperatures close to the pre-eruption BP plasmas and electron densities typically near 109 cm–3. These new observational results indicate that CBPs are more complex in dynamical evolution and magnetic structure than previously thought.

  17. Dark blood versus bright blood T2* acquisition in cardiovascular magnetic resonance (CMR) for thalassaemia major (TM) patients: Evaluation of feasibility, reproducibility and image quality

    Energy Technology Data Exchange (ETDEWEB)

    Liguori, Carlo, E-mail: c.liguori@unicampus.it [Department of Diagnostic Imaging, Campus Bio Medico University, via Alvaro del Portillo 200, 00128 Rome (Italy); Di Giampietro, Ilenia; Pitocco, Francesca; De Vivo, Aldo Eros [Department of Diagnostic Imaging, Campus Bio Medico University, via Alvaro del Portillo 200, 00128 Rome (Italy); Schena, Emiliano [Unit of Measurements and Biomedical Instrumentation, Campus Bio Medico University, via Alvaro del Portillo 200, 00128 Rome (Italy); Mortato, Luca [Department of Diagnostic Imaging, Campus Bio Medico University, via Alvaro del Portillo 200, 00128 Rome (Italy); Pirro, Federica [Department of Biomaging and Radiological Sciences, Catholic University of Sacred Herart, Largo A. Gemelli 1, 00135 Rome (Italy); Cianciulli, Paolo [Thalassemia Unit, Ospedale Sant Eugenio, Piazzale dell’Umanesimo 10, 00143 Rome (Italy); Zobel, Bruno Beomonte [Department of Diagnostic Imaging, Campus Bio Medico University, via Alvaro del Portillo 200, 00128 Rome (Italy)

    2014-01-15

    Objectives: To compare the effectiveness of dark blood (DB) versus bright blood (BB) sequences. To assess the intra and inter-observer variability and inter-study reproducibility between BB versus DB. To evaluate image quality level in the two sequences. Methods: In a setting of 138 patients we performed CMR using cardiac gated Gradient-multiecho single breath-hold BB and DB sequences in the middle ventricular septum. Each acquisition was repeated during the same exam. Truncation method was used to account for background noise. Image quality (IQ) was assessed using a 5 point grading scale and image analysis was conducted by 2 experienced observers. Results: Compared with the conventional BB acquisition, the coefficient of correlation and significance of the DB technique was superior for intra-observer reproducibility (p < 0.001), inter-observer reproducibility (p < 0.001) and inter-study reproducibility (p < 0.001). The variability is also lower for DB sequences for T2* values <14 ms. Assessment of artifacts showed a superior score for DB versus BB scans (4 versus 3, p < 0.001). Conclusions: Improvement in terms of inter observer and inter study variability using DB sequences was obtained. The greatest disparity between them was seen in inter-study reproducibility and higher IQ in DB was seen. Study demonstrates better performance of DB imaging compared to BB in presence of comparable effectiveness.

  18. Dark blood versus bright blood T2* acquisition in cardiovascular magnetic resonance (CMR) for thalassaemia major (TM) patients: Evaluation of feasibility, reproducibility and image quality

    International Nuclear Information System (INIS)

    Objectives: To compare the effectiveness of dark blood (DB) versus bright blood (BB) sequences. To assess the intra and inter-observer variability and inter-study reproducibility between BB versus DB. To evaluate image quality level in the two sequences. Methods: In a setting of 138 patients we performed CMR using cardiac gated Gradient-multiecho single breath-hold BB and DB sequences in the middle ventricular septum. Each acquisition was repeated during the same exam. Truncation method was used to account for background noise. Image quality (IQ) was assessed using a 5 point grading scale and image analysis was conducted by 2 experienced observers. Results: Compared with the conventional BB acquisition, the coefficient of correlation and significance of the DB technique was superior for intra-observer reproducibility (p < 0.001), inter-observer reproducibility (p < 0.001) and inter-study reproducibility (p < 0.001). The variability is also lower for DB sequences for T2* values <14 ms. Assessment of artifacts showed a superior score for DB versus BB scans (4 versus 3, p < 0.001). Conclusions: Improvement in terms of inter observer and inter study variability using DB sequences was obtained. The greatest disparity between them was seen in inter-study reproducibility and higher IQ in DB was seen. Study demonstrates better performance of DB imaging compared to BB in presence of comparable effectiveness

  19. A new approach to modeling the influence of image features on fixation selection in scenes.

    Science.gov (United States)

    Nuthmann, Antje; Einhäuser, Wolfgang

    2015-03-01

    Which image characteristics predict where people fixate when memorizing natural images? To answer this question, we introduce a new analysis approach that combines a novel scene-patch analysis with generalized linear mixed models (GLMMs). Our method allows for (1) directly describing the relationship between continuous feature value and fixation probability, and (2) assessing each feature's unique contribution to fixation selection. To demonstrate this method, we estimated the relative contribution of various image features to fixation selection: luminance and luminance contrast (low-level features); edge density (a mid-level feature); visual clutter and image segmentation to approximate local object density in the scene (higher-level features). An additional predictor captured the central bias of fixation. The GLMM results revealed that edge density, clutter, and the number of homogenous segments in a patch can independently predict whether image patches are fixated or not. Importantly, neither luminance nor contrast had an independent effect above and beyond what could be accounted for by the other predictors. Since the parcellation of the scene and the selection of features can be tailored to the specific research question, our approach allows for assessing the interplay of various factors relevant for fixation selection in scenes in a powerful and flexible manner. PMID:25752239

  20. Automated prostate cancer detection via comprehensive multi-parametric magnetic resonance imaging texture feature models

    International Nuclear Information System (INIS)

    Prostate cancer is the most common form of cancer and the second leading cause of cancer death in North America. Auto-detection of prostate cancer can play a major role in early detection of prostate cancer, which has a significant impact on patient survival rates. While multi-parametric magnetic resonance imaging (MP-MRI) has shown promise in diagnosis of prostate cancer, the existing auto-detection algorithms do not take advantage of abundance of data available in MP-MRI to improve detection accuracy. The goal of this research was to design a radiomics-based auto-detection method for prostate cancer via utilizing MP-MRI data. In this work, we present new MP-MRI texture feature models for radiomics-driven detection of prostate cancer. In addition to commonly used non-invasive imaging sequences in conventional MP-MRI, namely T2-weighted MRI (T2w) and diffusion-weighted imaging (DWI), our proposed MP-MRI texture feature models incorporate computed high-b DWI (CHB-DWI) and a new diffusion imaging modality called correlated diffusion imaging (CDI). Moreover, the proposed texture feature models incorporate features from individual b-value images. A comprehensive set of texture features was calculated for both the conventional MP-MRI and new MP-MRI texture feature models. We performed feature selection analysis for each individual modality and then combined best features from each modality to construct the optimized texture feature models. The performance of the proposed MP-MRI texture feature models was evaluated via leave-one-patient-out cross-validation using a support vector machine (SVM) classifier trained on 40,975 cancerous and healthy tissue samples obtained from real clinical MP-MRI datasets. The proposed MP-MRI texture feature models outperformed the conventional model (i.e., T2w+DWI) with regard to cancer detection accuracy. Comprehensive texture feature models were developed for improved radiomics-driven detection of prostate cancer using MP-MRI. Using a

  1. UNLABELED SELECTED SAMPLES IN FEATURE EXTRACTION FOR CLASSIFICATION OF HYPERSPECTRAL IMAGES WITH LIMITED TRAINING SAMPLES

    Directory of Open Access Journals (Sweden)

    A. Kianisarkaleh

    2015-12-01

    Full Text Available Feature extraction plays a key role in hyperspectral images classification. Using unlabeled samples, often unlimitedly available, unsupervised and semisupervised feature extraction methods show better performance when limited number of training samples exists. This paper illustrates the importance of selecting appropriate unlabeled samples that used in feature extraction methods. Also proposes a new method for unlabeled samples selection using spectral and spatial information. The proposed method has four parts including: PCA, prior classification, posterior classification and sample selection. As hyperspectral image passes these parts, selected unlabeled samples can be used in arbitrary feature extraction methods. The effectiveness of the proposed unlabeled selected samples in unsupervised and semisupervised feature extraction is demonstrated using two real hyperspectral datasets. Results show that through selecting appropriate unlabeled samples, the proposed method can improve the performance of feature extraction methods and increase classification accuracy.

  2. Pilocytic astrocytoma presenting with atypical features on magnetic resonance imaging.

    Science.gov (United States)

    Nakano, Yoshiteru; Yamamoto, Junkoh; Takahashi, Mayu; Soejima, Yoshiteru; Akiba, Daisuke; Kitagawa, Takehiro; Ueta, Kunihiro; Miyaoka, Ryo; Umemura, Takeru; Nishizawa, Shigeru

    2015-10-01

    Pilocytic astrocytoma, which is classified as a grade I astrocytic tumor by the World Health Organization, is the most common type of glioma in children and young adults. Pilocytic astrocytoma generally appears as a well-circumscribed, contrast-enhancing lesion, frequently with cystic components on magnetic resonance imaging (MRI). However, it has been reported that the MRI appearance of pilocytic astrocytoma may be similar to that of high-grade gliomas in some cases. We here report on 6 cases of pilocytic astrocytoma with atypical MRI findings, including small cyst formation, heterogeneously enhancing tumor nodules, irregularly enhancing tumor nodules, and enhancing tumor nodules with internal hemorrhage. All tumors were successfully resected, and the histological diagnoses were pilocytic astrocytoma. When the tumor is located near a cerebral cistern or ventricle, the risk of leptomeningeal dissemination is increased. Furthermore, partial resection has also been associated with a higher risk of recurrence and leptomeningeal dissemination. To date, all but one patient are alive and recurrence-free. Because the preoperative diagnosis influences the decision on the extent of resection and because of the high risk of leptomeningeal dissemination associated with these tumors, careful and correct diagnosis by MRI is important. PMID:25454397

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

    International Nuclear Information System (INIS)

    Background. Characterization of textural features (spatial distributions of image intensity levels) has been considered as a tool for automatic tumor segmentation. The purpose of this work is to study the variability of the textural features in PET images due to different acquisition modes and reconstruction parameters. Material and methods. Twenty patients with solid tumors underwent PET/CT scans on a GE Discovery VCT scanner, 45-60 minutes post-injection of 10 mCi of [18F]FDG. Scans were acquired in both 2D and 3D modes. For each acquisition the raw PET data was reconstructed using five different reconstruction parameters. Lesions were segmented on a default image using the threshold of 40% of maximum SUV. Fifty different texture features were calculated inside the tumors. The range of variations of the features were calculated with respect to the average value. Results. Fifty textural features were classified based on the range of variation in three categories: small, intermediate and large variability. Features with small variability (range = 5%) were entropy-first order, energy, maximal correlation coefficient (second order feature) and low-gray level run emphasis (high-order feature). The features with intermediate variability (10% = range = 25%) were entropy-GLCM, sum entropy, high gray level run emphasis, gray level non-uniformity, small number emphasis, and entropy-NGL. Forty remaining features presented large variations (range > 30%). Conclusion. Textural features such as entropy-first order, energy, maximal correlation coefficient, and low-gray level run emphasis exhibited small variations due to different acquisition modes and reconstruction parameters. Features with low level of variations are better candidates for reproducible tumor segmentation. Even though features such as contrast-NGTD, coarseness, homogeneity, and busyness have been previously used, our data indicated that these features presented large variations, therefore they could not be

  4. Introduction: Feature Issue on Phantoms for the Performance Evaluation and Validation of Optical Medical Imaging Devices

    OpenAIRE

    Hwang, Jeeseong; Ramella-Roman, Jessica C.; Nordstrom, Robert

    2012-01-01

    The editors introduce the Biomedical Optics Express feature issue on “Phantoms for the Performance Evaluation and Validation of Optical Medical Imaging Devices.” This topic was the focus of a technical workshop that was held on November 7–8, 2011, in Washington, D.C. The feature issue includes 13 contributions from workshop attendees.

  5. Improved medical image modality classification using a combination of visual and textual features.

    Science.gov (United States)

    Dimitrovski, Ivica; Kocev, Dragi; Kitanovski, Ivan; Loskovska, Suzana; Džeroski, Sašo

    2015-01-01

    In this paper, we present the approach that we applied to the medical modality classification tasks at the ImageCLEF evaluation forum. More specifically, we used the modality classification databases from the ImageCLEF competitions in 2011, 2012 and 2013, described by four visual and one textual types of features, and combinations thereof. We used local binary patterns, color and edge directivity descriptors, fuzzy color and texture histogram and scale-invariant feature transform (and its variant opponentSIFT) as visual features and the standard bag-of-words textual representation coupled with TF-IDF weighting. The results from the extensive experimental evaluation identify the SIFT and opponentSIFT features as the best performing features for modality classification. Next, the low-level fusion of the visual features improves the predictive performance of the classifiers. This is because the different features are able to capture different aspects of an image, their combination offering a more complete representation of the visual content in an image. Moreover, adding textual features further increases the predictive performance. Finally, the results obtained with our approach are the best results reported on these databases so far. PMID:24997992

  6. Automated classification of patients with coronary artery disease using grayscale features from left ventricle echocardiographic images.

    Science.gov (United States)

    Acharya, U Rajendra; Sree, S Vinitha; Muthu Rama Krishnan, M; Krishnananda, N; Ranjan, Shetty; Umesh, Pai; Suri, Jasjit S

    2013-12-01

    Coronary Artery Disease (CAD), caused by the buildup of plaque on the inside of the coronary arteries, has a high mortality rate. To efficiently detect this condition from echocardiography images, with lesser inter-observer variability and visual interpretation errors, computer based data mining techniques may be exploited. We have developed and presented one such technique in this paper for the classification of normal and CAD affected cases. A multitude of grayscale features (fractal dimension, entropies based on the higher order spectra, features based on image texture and local binary patterns, and wavelet based features) were extracted from echocardiography images belonging to a huge database of 400 normal cases and 400 CAD patients. Only the features that had good discriminating capability were selected using t-test. Several combinations of the resultant significant features were used to evaluate many supervised classifiers to find the combination that presents a good accuracy. We observed that the Gaussian Mixture Model (GMM) classifier trained with a feature subset made up of nine significant features presented the highest accuracy, sensitivity, specificity, and positive predictive value of 100%. We have also developed a novel, highly discriminative HeartIndex, which is a single number that is calculated from the combination of the features, in order to objectively classify the images from either of the two classes. Such an index allows for an easier implementation of the technique for automated CAD detection in the computers in hospitals and clinics. PMID:23958645

  7. Herschel and SCUBA-2 imaging and spectroscopy of a bright, lensed submillimetre galaxy at z = 2.3

    CERN Document Server

    Ivison, R J; Swinyard, B; Smail, Ian; Pearson, C P; Rigopoulou, D; Polehampton, E; Baluteau, J -P; Barlow, M J; Blain, A W; Bock, J; Clements, D L; Coppin, K; Cooray, A; Danielson, A; Dwek, E; Edge, A C; Franceschini, A; Fulton, T; Glenn, J; Griffin, M; Isaak, K; Leeks, S; Lim, T; Naylor, D; Oliver, S J; Page, M J; Perez-Fournon, I; Rowan-Robinson, M; Savini, G; Scott, D; Spencer, L; Valtchanov, I; Vigroux, L; Wright, G S

    2010-01-01

    We present a detailed analysis of the far-IR properties of the bright, lensed, z = 2.3, SMG, SMM J2135-0102, using new observations with Herschel, SCUBA-2 and the VLA. These data allow us to constrain the galaxy's SED and show that it has an intrinsic rest-frame 8-1000um luminosity, L(bol), of (2.3 +/- 0.2) x 10^12 L(sun) and a likely SFR of ~400 M(sun)/yr. The galaxy sits on the far-IR/radio correlation for far-IR-selected galaxies. At ~>70um, the SED can be described adequately by dust components with T(d) ~ 30 and 60K. Using SPIRE's Fourier Transform Spectrometer we report a detection of the [CII] 158um cooling line. If the [CII], CO and far-IR continuum arise in photo-dissociation regions, we derive a characteristic gas density, n ~ 10^3 cm^-3, and a far-UV radiation field, G_0, 10^3x stronger than the Milky Way. L([CII])/L(bol) is significantly higher than in local ULIRGs but similar to the values found in local star-forming galaxies and starburst nuclei. This is consistent with SMM J2135-0102 being powe...

  8. The Feature Extraction Based on Texture Image Information for Emotion Sensing in Speech

    Directory of Open Access Journals (Sweden)

    Kun-Ching Wang

    2014-09-01

    Full Text Available In this paper, we present a novel texture image feature for Emotion Sensing in Speech (ESS. This idea is based on the fact that the texture images carry emotion-related information. The feature extraction is derived from time-frequency representation of spectrogram images. First, we transform the spectrogram as a recognizable image. Next, we use a cubic curve to enhance the image contrast. Then, the texture image information (TII derived from the spectrogram image can be extracted by using Laws’ masks to characterize emotional state. In order to evaluate the effectiveness of the proposed emotion recognition in different languages, we use two open emotional databases including the Berlin Emotional Speech Database (EMO-DB and eNTERFACE corpus and one self-recorded database (KHUSC-EmoDB, to evaluate the performance cross-corpora. The results of the proposed ESS system are presented using support vector machine (SVM as a classifier. Experimental results show that the proposed TII-based feature extraction inspired by visual perception can provide significant classification for ESS systems. The two-dimensional (2-D TII feature can provide the discrimination between different emotions in visual expressions except for the conveyance pitch and formant tracks. In addition, the de-noising in 2-D images can be more easily completed than de-noising in 1-D speech.

  9. Review of Metaplastic Carcinoma of the Breast: Imaging Findings and Pathologic Features

    Directory of Open Access Journals (Sweden)

    Rebecca Leddy

    2012-01-01

    Full Text Available Metaplastic carcinoma (MPC, an uncommon but often aggressive breast cancer, can be challenging to differentiate from other types of breast cancer and even benign lesions based on the imaging appearance. It has a variable pathology classification system. These types of tumors are generally rapidly growing palpable masses. MPCs on imaging can present with imaging features similar to invasive ductal carcinoma and probably even benign lesions. The purpose of this article is to review MPC of the breast including the pathology subtypes, imaging features, and imaging pathology correlations. By understanding the clinical picture, pathology, and overlap in imaging characteristics of MPC with invasive ductal carcinoma and probably benign lesions can assist in diagnosing these difficult malignancies.

  10. Automatic Registration of SAR Images with the Integrated Complementary Invariant Feature

    Directory of Open Access Journals (Sweden)

    Xiao-hua Wang

    2014-01-01

    Full Text Available The accurate Synthetic Aperture Radar (SAR image registration is important for exact analyses of mine deformation and ecological environment change. Currently, many image registration algorithms have been proposed, but these registration algorithms cannot be directly applied to SAR image, so an integrated registration approach is presented in this paper. Firstly, it is the coarse matching with Canny edge dividing regions; secondly, it is the fine matching by SIFT algorithm with improved Canny edge features; finally, obtain accurate registration SAR image. This approach has fewer computations than that simply using SIFT feature matching. Experimental analyses with SAR images of Yanzhou Mine demonstrate the efficiency and the accuracy of this approach for mine SAR image registration, which provides a simple and effective tool in SAR monitoring of mining deformation and ecological changes

  11. Computation of rotation local invariant features using the integral image for real time object detection

    OpenAIRE

    Villamizar, Michael; Sanfeliu, Alberto; Andrade-Cetto, J.

    2006-01-01

    We present a framework for object detection that is invariant to object translation, scale, rotation, and to some degree, occlusion, achieving high detection rates, at 14 fps in color images and at 30 fps in gray scale images. Our approach is based on boosting over a set of simple local features. In contrast to previous approaches, and to efficiently cope with orientation changes, we propose the use of non-Gaussian steerable filters, together with a new orientation integral image for a speedy...

  12. Face Recognition from Still Images to Video Sequences: A Local-Feature-Based Framework

    OpenAIRE

    Shaokang Chen; Sandra Mau; Harandi, Mehrtash T.; Conrad Sanderson; Abbas Bigdeli; Lovell, Brian C.

    2011-01-01

    Although automatic faces recognition has shown success for high-quality images under controlled conditions, for video-based recognition it is hard to attain similar levels of performance. We describe in this paper recent advances in a project being undertaken to trial and develop advanced surveillance systems for public safety. In this paper, we propose a local facial feature based framework for both still image and video-based face recognition. The evaluation is performed on a still image d...

  13. MR Imaging of Pregnancy Luteoma: a Case Report and Correlation with the Clinical Features

    OpenAIRE

    Kao, Hung-Wen; Wu, Ching-Jiunn; Chung, Kuo-Teng; Wang, Sheng-Ru; Chen, Cheng-Yu

    2005-01-01

    We report here on a 26-year-old pregnant female who developed hirsutism and virilization during her third trimester along with a significantly elevated serum testosterone level. Abdominal US and MR imaging studies were performed, and they showed unique imaging features that may suggest the diagnosis of pregnancy luteoma in the clinical context. After the delivery, the serum testosterone level continued to decrease, and it returned to normal three weeks postpartum. The follow-up imaging findin...

  14. Item Popularity Prediction in E-commerce Using Image Quality Feature Vectors

    OpenAIRE

    Zakrewsky, Stephen; Aryafar, Kamelia; Shokoufandeh, Ali

    2016-01-01

    Online retail is a visual experience- Shoppers often use images as first order information to decide if an item matches their personal style. Image characteristics such as color, simplicity, scene composition, texture, style, aesthetics and overall quality play a crucial role in making a purchase decision, clicking on or liking a product listing. In this paper we use a set of image features that indicate quality to predict product listing popularity on a major e-commerce website, Etsy. We fir...

  15. IMAGING SPECTROSCOPY AND LIGHT DETECTION AND RANGING DATA FUSION FOR URBAN FEATURES EXTRACTION

    OpenAIRE

    Mohammed Idrees; Helmi Zulhaidi Mohd Shafri; Vahideh Saeidi

    2013-01-01

    This study presents our findings on the fusion of Imaging Spectroscopy (IS) and LiDAR data for urban feature extraction. We carried out necessary preprocessing of the hyperspectral image. Minimum Noise Fraction (MNF) transforms was used for ordering hyperspectral bands according to their noise. Thereafter, we employed Optimum Index Factor (OIF) to statistically select the three most appropriate bands combination from MNF result. The composite image was classified using unsupervised classifica...

  16. Robust Feature Correspondences from a Large Set of Unsorted Wide Baseline Images

    OpenAIRE

    Cao, Yanpeng; McDonald, John

    2009-01-01

    Given a set of unordered images taken in a wide area, an effective solution is proposed for establishing robust feature correspondences among them. Two major improvements are made in our work as follows: firstly, a robust technique is proposed for the self-organization of a large number of images without spatial orderings; secondly, a novel wide-baseline matching approach is developed to obtain good correspondences over images taken from substantially different viewpoints...

  17. A MATLAB Based Algorithm Design for New Structural Feature of Retinal Image Vasculature Pattern

    Directory of Open Access Journals (Sweden)

    Udaya Kumar Naluguru

    2013-01-01

    Full Text Available In this paper we illustrate the different point types in retinal images. The bifurcation structure is composed of a master bifurcation point and three connected neighbors. In this paper we present the illustration of featured based method, which is explained in detail and further image registration results are also discussed in detail. The advantage of the proposed structure-matching approach is the ability to handle translation, rotation and scaling with the available vascular trees of image pairs.

  18. Improved Block Based Feature Level Image Fusion Technique Using Contourlet with Neural Network

    Directory of Open Access Journals (Sweden)

    C.M.Sheela Rani

    2012-08-01

    Full Text Available As multisensory data is made available in many areas such as remote sensing, medical imaging, etc, the sensor fusion has become a new field for research. Multisensor image fusion mainly focuses on combining spatial information of a high resolution panchromatic (PAN image with spectral information of a low resolution multispectral image (MS to produce an image with highest spatial content while preserving spectral resolution. A geometrical transform called contourlet transform (CT is introduced, which represents images containing contours and textures. This paper derived an efficient block based feature level contourlet transform with neural network (BFCN model for image fusion. The proposed BFCN model integrates CT with neural network (NN, which plays a significant role in feature extraction and detection in machine learning applications. In the proposed BFCN model, the two fusion techniques, CT and NN are discussed for fusing the IRS-1D images using LISS III scanner about the locations Hyderabad, Vishakhapatnam, Mahaboobnagar and Patancheru in Andhra Pradesh, India. Also Landsat 7 image data and QuickBird image data are used to perform experiments on the proposed BFCN model. The features under study are contrast visibility, spatial frequency, energy of gradient, variance and edge information. Feed forward back propagation neural network is trained and tested for classification, since the learning capability of NN makes it feasible to customize the image fusion process. The trained NN is then used to fuse the pair of source images. The proposed BFCN model is compared with other techniques to assess the quality of the fused image. Experimental results clearly prove that the proposed BFCN model is an efficient and feasible algorithm for image fusion.

  19. Improved Block Based Feature Level Image Fusion Technique Using Contourlet with Neural Network

    Directory of Open Access Journals (Sweden)

    C.M.Sheela Rani

    2012-09-01

    Full Text Available As multisensory data is made available in many areas such as remote sensing, medical imaging, etc, thesensor fusion has become a new field for research. Multisensor image fusion mainly focuses on combining spatial information of a high resolution panchromatic (PAN image with spectral information of a low resolution multispectral image (MS to produce an image with highest spatial content while preserving spectral resolution. A geometrical transform called contourlet transform (CT is introduced, which represents images containing contours and textures. This paper derived an efficient block based feature level contourlet transform with neural network (BFCN model for image fusion. The proposed BFCN model integrates CT with neural network (NN, which plays a significant role in feature extraction and detection in machine learning applications. In the proposed BFCN model, the two fusion techniques, CT and NN are discussed for fusing the IRS-1D images using LISS III scanner about the locations Hyderabad, Vishakhapatnam, Mahaboobnagar and Patancheru in Andhra Pradesh, India. Also Landsat 7 image data and QuickBird image data are used to perform experiments on the proposed BFCN model. The features under study are contrast visibility, spatial frequency, energy of gradient, variance and edge information. Feed forward back propagation neural network is trained and tested for classification, since the learning capability of NN makes it feasible to customize the image fusion process. The trained NN is then used to fuse the pair of source images. The proposed BFCN model is compared with other techniques to assess the quality of the fused image. Experimental results clearly prove that the proposed BFCN model is an efficient and feasible algorithm for image fusion.

  20. Profiles of US and CT imaging features with a high probability of appendicitis

    Energy Technology Data Exchange (ETDEWEB)

    Randen, A. van; Lameris, W. [University of Amsterdam, Department of Radiology, Academic Medical Center, Amsterdam (Netherlands); University of Amsterdam, Department of Surgery, Academic Medical Center, Amsterdam (Netherlands); Es, H.W. van [St Antonius Hospital, Department of Radiology, Nieuwegein (Netherlands); Hove, W. ten; Bouma, W.H. [Gelre Hospitals, Department of Surgery, Apeldoorn (Netherlands); Leeuwen, M.S. van [University Medical Centre, Department of Radiology, Utrecht (Netherlands); Keulen, E.M. van [Tergooi Hospitals, Department of Radiology, Hilversum (Netherlands); Hulst, V.P.M. van der [Onze Lieve Vrouwe Gasthuis, Department of Radiology, Amsterdam (Netherlands); Henneman, O.D. [Bronovo Hospital, Department of Radiology, The Hague (Netherlands); Bossuyt, P.M. [University of Amsterdam, Department of Clinical Epidemiology, Biostatistics, and Bioinformatics, Academic Medical Center, Amsterdam (Netherlands); Boermeester, M.A. [University of Amsterdam, Department of Surgery, Academic Medical Center, Amsterdam (Netherlands); Stoker, J. [University of Amsterdam, Department of Radiology, Academic Medical Center, Amsterdam (Netherlands)

    2010-07-15

    To identify and evaluate profiles of US and CT features associated with acute appendicitis. Consecutive patients presenting with acute abdominal pain at the emergency department were invited to participate in this study. All patients underwent US and CT. Imaging features known to be associated with appendicitis, and an imaging diagnosis were prospectively recorded by two independent radiologists. A final diagnosis was assigned after 6 months. Associations between appendiceal imaging features and a final diagnosis of appendicitis were evaluated with logistic regression analysis. Appendicitis was assigned to 284 of 942 evaluated patients (30%). All evaluated features were associated with appendicitis. Imaging profiles were created after multivariable logistic regression analysis. Of 147 patients with a thickened appendix, local transducer tenderness and peri-appendiceal fat infiltration on US, 139 (95%) had appendicitis. On CT, 119 patients in whom the appendix was completely visualised, thickened, with peri-appendiceal fat infiltration and appendiceal enhancement, 114 had a final diagnosis of appendicitis (96%). When at least two of these essential features were present on US or CT, sensitivity was 92% (95% CI 89-96%) and 96% (95% CI 93-98%), respectively. Most patients with appendicitis can be categorised within a few imaging profiles on US and CT. When two of the essential features are present the diagnosis of appendicitis can be made accurately. (orig.)

  1. Profiles of US and CT imaging features with a high probability of appendicitis

    International Nuclear Information System (INIS)

    To identify and evaluate profiles of US and CT features associated with acute appendicitis. Consecutive patients presenting with acute abdominal pain at the emergency department were invited to participate in this study. All patients underwent US and CT. Imaging features known to be associated with appendicitis, and an imaging diagnosis were prospectively recorded by two independent radiologists. A final diagnosis was assigned after 6 months. Associations between appendiceal imaging features and a final diagnosis of appendicitis were evaluated with logistic regression analysis. Appendicitis was assigned to 284 of 942 evaluated patients (30%). All evaluated features were associated with appendicitis. Imaging profiles were created after multivariable logistic regression analysis. Of 147 patients with a thickened appendix, local transducer tenderness and peri-appendiceal fat infiltration on US, 139 (95%) had appendicitis. On CT, 119 patients in whom the appendix was completely visualised, thickened, with peri-appendiceal fat infiltration and appendiceal enhancement, 114 had a final diagnosis of appendicitis (96%). When at least two of these essential features were present on US or CT, sensitivity was 92% (95% CI 89-96%) and 96% (95% CI 93-98%), respectively. Most patients with appendicitis can be categorised within a few imaging profiles on US and CT. When two of the essential features are present the diagnosis of appendicitis can be made accurately. (orig.)

  2. A unified framework of image latent feature learning on Sina microblog

    Science.gov (United States)

    Wei, Jinjin; Jin, Zhigang; Zhou, Yuan; Zhang, Rui

    2015-10-01

    Large-scale user-contributed images with texts are rapidly increasing on the social media websites, such as Sina microblog. However, the noise and incomplete correspondence between the images and the texts give rise to the difficulty in precise image retrieval and ranking. In this paper, a hypergraph-based learning framework is proposed for image ranking, which simultaneously utilizes visual feature, textual content and social link information to estimate the relevance between images. Representing each image as a vertex in the hypergraph, complex relationship between images can be reflected exactly. Then updating the weight of hyperedges throughout the hypergraph learning process, the effect of different edges can be adaptively modulated in the constructed hypergraph. Furthermore, the popularity degree of the image is employed to re-rank the retrieval results. Comparative experiments on a large-scale Sina microblog data-set demonstrate the effectiveness of the proposed approach.

  3. Hyperspectral image classification based on spatial and spectral features and sparse representation

    Institute of Scientific and Technical Information of China (English)

    Yang Jing-Hui; Wang Li-Guo; Qian Jin-Xi

    2014-01-01

    To minimize the low classification accuracy and low utilization of spatial information in traditional hyperspectral image classification methods, we propose a new hyperspectral image classification method, which is based on the Gabor spatial texture features and nonparametric weighted spectral features, and the sparse representation classification method (Gabor–NWSF and SRC), abbreviated GNWSF–SRC. The proposed (GNWSF–SRC) method first combines the Gabor spatial features and nonparametric weighted spectral features to describe the hyperspectral image, and then applies the sparse representation method. Finally, the classification is obtained by analyzing the reconstruction error. We use the proposed method to process two typical hyperspectral data sets with different percentages of training samples. Theoretical analysis and simulation demonstrate that the proposed method improves the classification accuracy and Kappa coefficient compared with traditional classification methods and achieves better classification performance.

  4. Scalable Feature Matching by Dual Cascaded Scalar Quantization for Image Retrieval.

    Science.gov (United States)

    Zhou, Wengang; Yang, Ming; Wang, Xiaoyu; Li, Houqiang; Lin, Yuanqing; Tian, Qi

    2016-01-01

    In this paper, we investigate the problem of scalable visual feature matching in large-scale image search and propose a novel cascaded scalar quantization scheme in dual resolution. We formulate the visual feature matching as a range-based neighbor search problem and approach it by identifying hyper-cubes with a dual-resolution scalar quantization strategy. Specifically, for each dimension of the PCA-transformed feature, scalar quantization is performed at both coarse and fine resolutions. The scalar quantization results at the coarse resolution are cascaded over multiple dimensions to index an image database. The scalar quantization results over multiple dimensions at the fine resolution are concatenated into a binary super-vector and stored into the index list for efficient verification. The proposed cascaded scalar quantization (CSQ) method is free of the costly visual codebook training and thus is independent of any image descriptor training set. The index structure of the CSQ is flexible enough to accommodate new image features and scalable to index large-scale image database. We evaluate our approach on the public benchmark datasets for large-scale image retrieval. Experimental results demonstrate the competitive retrieval performance of the proposed method compared with several recent retrieval algorithms on feature quantization. PMID:26656584

  5. Image Information Retrieval From Incomplete Queries Using Color and Shape Features

    Directory of Open Access Journals (Sweden)

    Bikesh Kumar Singh

    2011-12-01

    Full Text Available Content based image retrieval (CBIR is the task of searching digital images from a large database basedon the extraction of features, such as color, texture and shape of the image. Most of the research in CBIRhas been carried out with complete queries which were present in the database. This paper investigatesutility of CBIR techniques for retrieval of incomplete and distorted queries. Studies were made in twocategories of the query: first is complete and second is incomplete. The query image is considered to bedistorted or incomplete image if it has some missing information, some undesirable objects, blurring, noisedue to disturbance at the time of image acquisition etc. Color (hue, saturation and value (HSV color spacemodel and shape (moment invariants and Fourier descriptor features are used to represent the image.The algorithm was tested on database consisting of 1875 images. The results show that retrieval accuracyof incomplete queries is highly increased by fusing color and shape features giving precision of 79.87%.MATLAB ® 7.01 and its image processing toolbox have been used to implement the algorithm.

  6. Learning to rank using user clicks and visual features for image retrieval.

    Science.gov (United States)

    Yu, Jun; Tao, Dacheng; Wang, Meng; Rui, Yong

    2015-04-01

    The inconsistency between textual features and visual contents can cause poor image search results. To solve this problem, click features, which are more reliable than textual information in justifying the relevance between a query and clicked images, are adopted in image ranking model. However, the existing ranking model cannot integrate visual features, which are efficient in refining the click-based search results. In this paper, we propose a novel ranking model based on the learning to rank framework. Visual features and click features are simultaneously utilized to obtain the ranking model. Specifically, the proposed approach is based on large margin structured output learning and the visual consistency is integrated with the click features through a hypergraph regularizer term. In accordance with the fast alternating linearization method, we design a novel algorithm to optimize the objective function. This algorithm alternately minimizes two different approximations of the original objective function by keeping one function unchanged and linearizing the other. We conduct experiments on a large-scale dataset collected from the Microsoft Bing image search engine, and the results demonstrate that the proposed learning to rank models based on visual features and user clicks outperforms state-of-the-art algorithms. PMID:25095275

  7. Vehicle Detection in Still Images by Using Boosted Local Feature Detector

    Institute of Scientific and Technical Information of China (English)

    Qing LIN; Young-joon HAN; Hern-soo HAHN

    2010-01-01

    Vehicle detection in still images is a comparatively difficult task.This paper presents a method for this task by using boosted local pattem detector constructed from two local features including Haar-like and oriented gradient features.The whole process is composed of three stages.In the first stage,local appearance features of vehicles and non-vehicle objects are extracted.Haar-like and oriented gradient features arc extracted separately in this stage as local features.In the second stage,Adaboost algorithm is used to select the mast discriminative features as weak detectors from the two local feature sets,and a strong local pattern detector is built by the weighted combination of these selected weak detectors.Finally,vehicle detection can be performed in still images by using the boosted strong local feature detector.Experiment results show that the local pattern detectur constructed in this way combines the advantages of Haar-like and oriented gradient features,and can achieve better detection results than the datector by using single Haar-like features.

  8. A Fast Image Retrieval Algorithm with Multi-Channel Textural Features in PACS

    Institute of Scientific and Technical Information of China (English)

    ZHANG Dong; YANG Yan; QIN Qian-qing

    2005-01-01

    The paper presents a fast algorithm for image retrieval using multi-channel textural features in medical picture archiving and communication system (PACS). By choosing different linear or nonlinear operators in prediction and update lifting step, the linear or nonlinear M-band wavelet decomposition can be achieved in Mband lifting. It provides the advantages such as fast transform, in-place calculation and integer-integer transform. The set of wavelet moment forms multi-channel textural feature vector related to the texture distribution of each wavelet images. The experimental results of CT image database show that the retrieval approach of multi-channel textural features is effective for image indexing and has lower computational complexity and less memory. It is much easier to implement in hardware and suitable for the applications of real time medical processing system.

  9. Computer simulation on spatial resolution of X-ray bright-field imaging by dynamical diffraction theory for a Laue-case crystal analyzer

    International Nuclear Information System (INIS)

    Recently, dark-field imaging (DFI) and bright-field imaging (BFI) have been proposed and applied to visualize X-ray refraction effects yielded in biomedical objects. In order to clarify the spatial resolution due to a crystal analyzer in Laue geometry, a program based on the Takagi-Taupin equation was modified to be used for carrying out simulations to evaluate the spatial resolution of images coming into a Laue angular analyzer (LAA). The calculation was done with a perfect plane wave for diffraction wave-fields, which corresponded to BFI, under the conditions of 35 keV and a diffraction index 440 for a 2100 μm thick LAA. As a result, the spatial resolution along the g-vector direction showed approximately 37.5 μm. 126 μm-thick LAA showed a spatial resolution better than 3.1 μm under the conditions of 13.7 keV and a diffraction index 220.

  10. CT and MR imaging features of oral and maxillofacial hemangioma and vascular malformation

    International Nuclear Information System (INIS)

    Purpose: To present CT and MR images and compare CT and MRI features of oral and maxillofacial hemangioma and vascular malformation. Material and methods: The clinical materials consisted of nine vascular tumors from nine patients examined by both CT and MR scanners between November 1996 and March 2002. Both CT and MR images were retrospectively evaluated. The following features were evaluated: detectability of the lesion, border of the lesion, tumor margin, inner nature of the lesion, contrast between the lesion and surrounding tissues, degree of CT value or signal intensity of the lesion, enhancement of contrast medium, inner nature of the lesion after contrast medium injection, detectability of phleboliths and detectability of bone resorption. Results: In two patients, we could not detect lesions in any of the CT images because of artifacts from the teeth and/or dental restorations. In contrast, we could detect all lesions on T2-weighted MR images and contrast enhanced T1-weighted MR images. On T2-weighted images with the fat suppression technique, tumors tended to show higher contrast compared to surrounding tissues. Conclusion: T2-weighted images with the fat suppression technique and contrast enhanced T1-weighted images with the fat suppression technique were very useful for the detection of vascular lesions. Observation from optional directions (axial, coronal and sagittal images) seemed appropriate for delineating the extension of the tumor. Phleboliths detectability on CT images was superior to that on MR images

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

    International Nuclear Information System (INIS)

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-11-15

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

  13. Feature-based registration of historical aerial images by Area Minimization

    Science.gov (United States)

    Nagarajan, Sudhagar; Schenk, Toni

    2016-06-01

    The registration of historical images plays a significant role in assessing changes in land topography over time. By comparing historical aerial images with recent data, geometric changes that have taken place over the years can be quantified. However, the lack of ground control information and precise camera parameters has limited scientists' ability to reliably incorporate historical images into change detection studies. Other limitations include the methods of determining identical points between recent and historical images, which has proven to be a cumbersome task due to continuous land cover changes. Our research demonstrates a method of registering historical images using Time Invariant Line (TIL) features. TIL features are different representations of the same line features in multi-temporal data without explicit point-to-point or straight line-to-straight line correspondence. We successfully determined the exterior orientation of historical images by minimizing the area formed between corresponding TIL features in recent and historical images. We then tested the feasibility of the approach with synthetic and real data and analyzed the results. Based on our analysis, this method shows promise for long-term 3D change detection studies.

  14. Feature matching method study for uncorrected fish-eye lens image

    Science.gov (United States)

    Zhang, Baofeng; Jia, Yanhui; Röning, Juha; Feng, Weijia

    2015-01-01

    Because of the further from the center of image the lower resolution and the severe non-linear distortion are the characteristics of uncorrected fish-eye lens image, the traditional feature matching method can't achieve good performance in the applications of fish-eye lens, which correct distortion firstly and then matches the features in image. Center-symmetric Local Binary Pattern (CS-LBP) is a kind of descriptor based on grayscale information from neighborhood, which has high ability of grayscale invariance and rotation invariance. In this paper, CS-LBP will be combined with Scale Invariant Feature Transform (SIFT) to solve the problem of feature point matching on uncorrected fish-eye image. We first extract the interest points in the pair of fish-eye images by SIFT, and then describe the corresponding regions of the interest points through CS-LBP. Finally the similarity of the regions will be evaluated using the chi-square distance to get the only pair of points. For the specified interest point, the corresponding point in another image can be found out. The experimental results show that the proposed method achieves a satisfying matching performance in uncorrected fish-eye lens image. The study of this article will be useful to enhance the applications of fish-eye lens in the field of 3D reconstruction and panorama restoration.

  15. Low Surface Brightness Imaging of the Magellanic System: Imprints of Tidal Interactions between the Clouds in the Stellar Periphery

    Science.gov (United States)

    Besla, Gurtina; Martínez-Delgado, David; van der Marel, Roeland P.; Beletsky, Yuri; Seibert, Mark; Schlafly, Edward F.; Grebel, Eva K.; Neyer, Fabian

    2016-07-01

    We present deep optical images of the Large and Small Magellanic Clouds (LMC and SMC) using a low cost telephoto lens with a wide field of view to explore stellar substructure in the outskirts of the stellar disk of the LMC (Magellanic Irregular does not disprove the hypothesis that their asymmetric structures are driven by dwarf–dwarf interactions.

  16. Joint Applied Optics and Chinese Optics Letters Feature Introduction: Digital Holography and 3D Imaging

    Institute of Scientific and Technical Information of China (English)

    Ting-Chung Poon; Changhe Zhou; Toyohiko Yatagai; Byoungho Lee; Hongchen Zhai

    2011-01-01

    This feature issue is the fifth installment on digital holography since its inception four years ago.The last four issues have been published after the conclusion of each Topical Meeting "Digital Holography and 3D imaging (DH)." However,this feature issue includes a new key feature-Joint Applied Optics and Chinese Optics Letters Feature Issue.The DH Topical Meeting is the world's premier forum for disseminating the science and technology geared towards digital holography and 3D information processing.Since the meeting's inception in 2007,it has steadily and healthily grown to 130 presentations this year,held in Tokyo,Japan,May 2011.

  17. The Research of Feature Extraction Method of Liver Pathological Image Based on Multispatial Mapping and Statistical Properties

    OpenAIRE

    Huiling Liu; Huiyan Jiang; Bingbing Xia; Dehui Yi

    2016-01-01

    We propose a new feature extraction method of liver pathological image based on multispatial mapping and statistical properties. For liver pathological images of Hematein Eosin staining, the image of R and B channels can reflect the sensitivity of liver pathological images better, while the entropy space and Local Binary Pattern (LBP) space can reflect the texture features of the image better. To obtain the more comprehensive information, we map liver pathological images to the entropy space,...

  18. Passive Forensics for Region Duplication Image Forgery Based on Harris Feature Points and Local Binary Patterns

    Directory of Open Access Journals (Sweden)

    Jie Zhao

    2013-01-01

    Full Text Available Nowadays the demand for identifying the authenticity of an image is much increased since advanced image editing software packages are widely used. Region duplication forgery is one of the most common and immediate tampering attacks which are frequently used. Several methods to expose this forgery have been developed to detect and locate the tampered region, while most methods do fail when the duplicated region undergoes rotation or flipping before being pasted. In this paper, an efficient method based on Harris feature points and local binary patterns is proposed. First, the image is filtered with a pixelwise adaptive Wiener method, and then dense Harris feature points are employed in order to obtain a sufficient number of feature points with approximately uniform distribution. Feature vectors for a circle patch around each feature point are extracted using local binary pattern operators, and the similar Harris points are matched based on their representation feature vectors using the BBF algorithm. Finally, RANSAC algorithm is employed to eliminate the possible erroneous matches. Experiment results demonstrate that the proposed method can effectively detect region duplication forgery, even when an image was distorted by rotation, flipping, blurring, AWGN, JPEG compression, and their mixed operations, especially resistant to the forgery with the flat area of little visual structures.

  19. A Composite Approach To The Identification Of High-Level Topological Features In A Histopathologic Image

    Science.gov (United States)

    Kuhn, W. P.; Bartels, H. G.; Bartels, P. H.; Richards, D. L.; Saffer, J. S.; Shoemaker, R. L.

    1988-06-01

    Analysis of the large amounts of image data obtainable from very-high-speed scanning laser microscopes places severe demands on computer software and hardware architectures. The automated calculation of features over entire images can provide quantitative data useful to a pathologist who must make a diagnosis. A program that identifies objects of diagnostic interest in an image must utilize a model of the image. An expert system is an effective method for building abstract models of object hierarchies and for utilizing heuristic information. In this paper we discuss a composite approach to image understanding and assessment that utilizes an expert system to control a set of image processing functions for the recognition of various objects in an image.

  20. A CAD system for B-mode fatty liver ultrasound images using texture features.

    Science.gov (United States)

    Subramanya, M B; Kumar, Vinod; Mukherjee, Shaktidev; Saini, Manju

    2015-02-01

    The present study proposes a computer-aided diagnosis (CAD) system for the diagnosis of grades of fatty liver disease, namely mild, moderate and severe fatty liver along with normal liver tissue. Fifty-three B-mode ultrasound images consisting of 12 normal, 14 mild, 14 moderate and 13 severe fatty liver images are used. Based on the visual interpretations by the radiologists, region of interests (ROIs) from within the liver and one ROI from the diaphragm region are considered from each image. The texture features of these ROIs are combined in three ways to form ratio features, inverse ratio features and additive features. The sub-sets of optimal features are obtained by a differential evolution feature selection (DEFS) algorithm and a support vector machine (SVM) has been used for the classification task. The Laws ratio features have shown better performance with an average accuracy and standard deviation of 84.9±3.2. Hence, the CAD system could be useful to the radiologists in diagnosing grades of fatty liver disease. PMID:25522808