18,013 research outputs found

    An Automatic Level Set Based Liver Segmentation from MRI Data Sets

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    A fast and accurate liver segmentation method is a challenging work in medical image analysis area. Liver segmentation is an important process for computer-assisted diagnosis, pre-evaluation of liver transplantation and therapy planning of liver tumors. There are several advantages of magnetic resonance imaging such as free form ionizing radiation and good contrast visualization of soft tissue. Also, innovations in recent technology and image acquisition techniques have made magnetic resonance imaging a major tool in modern medicine. However, the use of magnetic resonance images for liver segmentation has been slow when we compare applications with the central nervous systems and musculoskeletal. The reasons are irregular shape, size and position of the liver, contrast agent effects and similarities of the gray values of neighbor organs. Therefore, in this study, we present a fully automatic liver segmentation method by using an approximation of the level set based contour evolution from T2 weighted magnetic resonance data sets. The method avoids solving partial differential equations and applies only integer operations with a two-cycle segmentation algorithm. The efficiency of the proposed approach is achieved by applying the algorithm to all slices with a constant number of iteration and performing the contour evolution without any user defined initial contour. The obtained results are evaluated with four different similarity measures and they show that the automatic segmentation approach gives successful results

    Blowin' in the wind: both `negative' and `positive' feedback in an obscured high-z Quasar

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    Quasar feedback in the form of powerful outflows is invoked as a key mechanism to quench star formation in galaxies, preventing massive galaxies to over-grow and producing the red colors of ellipticals. On the other hand, some models are also requiring `positive' AGN feedback, inducing star formation in the host galaxy through enhanced gas pressure in the interstellar medium. However, finding observational evidence of the effects of both types of feedback is still one of the main challenges of extragalactic astronomy, as few observations of energetic and extended radiatively-driven winds are available. Here we present SINFONI near infrared integral field spectroscopy of XID2028, an obscured, radio-quiet z=1.59 QSO detected in the XMM-COSMOS survey, in which we clearly resolve a fast (1500 km/s) and extended (up to 13 kpc from the black hole) outflow in the [OIII] lines emitting gas, whose large velocity and outflow rate are not sustainable by star formation only. The narrow component of Ha emission and the rest frame U band flux from HST-ACS imaging enable to map the current star formation in the host galaxy: both tracers independently show that the outflow position lies in the center of an empty cavity surrounded by star forming regions on its edge. The outflow is therefore removing the gas from the host galaxy (`negative feedback'), but also triggering star formation by outflow induced pressure at the edges (`positive feedback'). XID2028 represents the first example of a host galaxy showing both types of feedback simultaneously at work.Comment: 9 pages, 5 figures, accepted for publication in Ap

    Gaussian mixture model based probabilistic modeling of images for medical image segmentation

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    In this paper, we propose a novel image segmentation algorithm that is based on the probability distributions of the object and background. It uses the variational level sets formulation with a novel region based term in addition to the edge-based term giving a complementary functional, that can potentially result in a robust segmentation of the images. The main theme of the method is that in most of the medical imaging scenarios, the objects are characterized by some typical characteristics such a color, texture, etc. Consequently, an image can be modeled as a Gaussian mixture of distributions corresponding to the object and background. During the procedure of curve evolution, a novel term is incorporated in the segmentation framework which is based on the maximization of the distance between the GMM corresponding to the object and background. The maximization of this distance using differential calculus potentially leads to the desired segmentation results. The proposed method has been used for segmenting images from three distinct imaging modalities i.e. magnetic resonance imaging (MRI), dermoscopy and chromoendoscopy. Experiments show the effectiveness of the proposed method giving better qualitative and quantitative results when compared with the current state-of-the-art. INDEX TERMS Gaussian Mixture Model, Level Sets, Active Contours, Biomedical Engineerin

    The MAGNUM survey: Positive feedback in the nuclear region of NGC 5643 suggested by MUSE

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    We study the ionization and kinematics of the ionized gas in the nuclear region of the barred Seyfert 2 galaxy NGC~5643 using MUSE integral field observations in the framework of the MAGNUM (Measuring Active Galactic Nuclei Under MUSE Microscope) survey. The data were used to identify regions with different ionization conditions and to map the gas density and the dust extinction. We find evidence for a double sided ionization cone, possibly collimated by a dusty structure surrounding the nucleus. At the center of the ionization cone, outflowing ionized gas is revealed as a blueshifted, asymmetric wing of the [OIII] emission line, up to projected velocity v(10)~-450 km/s. The outflow is also seen as a diffuse, low luminosity radio and X-ray jet, with similar extension. The outflowing material points in the direction of two clumps characterized by prominent line emission with spectra typical of HII regions, located at the edge of the dust lane of the bar. We propose that the star formation in the clumps is due to `positive feedback' induced by gas compression by the nuclear outflow, providing the first candidate for outflow induced star formation in a Seyfert-like radio quiet AGN. This suggests that positive feedback may be a relevant mechanism in shaping the black hole-host galaxy coevolution.Comment: 9 pages, 7 figures, accepted for publication in A&

    Active skeleton for bacteria modeling

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    The investigation of spatio-temporal dynamics of bacterial cells and their molecular components requires automated image analysis tools to track cell shape properties and molecular component locations inside the cells. In the study of bacteria aging, the molecular components of interest are protein aggregates accumulated near bacteria boundaries. This particular location makes very ambiguous the correspondence between aggregates and cells, since computing accurately bacteria boundaries in phase-contrast time-lapse imaging is a challenging task. This paper proposes an active skeleton formulation for bacteria modeling which provides several advantages: an easy computation of shape properties (perimeter, length, thickness, orientation), an improved boundary accuracy in noisy images, and a natural bacteria-centered coordinate system that permits the intrinsic location of molecular components inside the cell. Starting from an initial skeleton estimate, the medial axis of the bacterium is obtained by minimizing an energy function which incorporates bacteria shape constraints. Experimental results on biological images and comparative evaluation of the performances validate the proposed approach for modeling cigar-shaped bacteria like Escherichia coli. The Image-J plugin of the proposed method can be found online at http://fluobactracker.inrialpes.fr.Comment: Published in Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualizationto appear i
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