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Abstract The Mumford-Shah functional and related algorithms for image segmentation involve a tradeoff between a two-dimensional image structure and one-dimensional parametric curves (contours) that su...
The Mumford-Shah functional minimization, and related algorithms for image segmentation, involve a tradeoff between a twodimensional image structure and one-dimensional parametric curves (contours) th...
We address the issue of textured image segmentation in the context of the Gabor feature space of images. Gabor filters tuned to a set of orientations, scales and frequencies are applied to the images...
Fluorescence microscope images capture information from an entire field of view, which often comprises several cells scattered on the slide. We have previously trained classifiers to accurately pre...
We present a method for semiautomatic segmentation of brain structures such as thalamus from MRI images based on the concept of geometric surface flow. Given an MRI image, the user can interactively i...
In contemporary image and vision analysis, stochastic approaches demonstrate great flexibility in representing and modeling complex phenomena, while variational-PDE methods gain enormous computational...
Important attributes of 3D brain cortex segmentation algorithms include robustness, accuracy, computational efficiency, and facilitation of user interaction, yet few algorithms incorporate all of thes...
This paper presents the implementation and quantitative evaluation of a multiphase three-dimensional deformable model in a level set framework for automated segmentation of brain MRIs. The segmentatio...
Segmentation of molecular images is a difficult task due to the low signal-to-noise ratio of images. A novel two-dimensional fuzzy C-means (2DFCM) algorithm is proposed for the molecular image segment...
We propose a semi-automatic thalamus and thalamus nuclei segmentation algorithm from Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) based on the mean-shift algorithm. Comparing with existing tha...
We propose a new context-sensitive active contour for 2D corpus callosum segmentation. After a seed contour consisting of interconnected parts is being initialized by the user, each part will start to...
White matter fiber clustering aims to get insight about anatomical structures in order to generate atlases, perform clear visualizations, and compute statistics across subjects, all important and curr...
We propose to segment two-dimensional CT scans traumatic brain injuries with various methods. These methods are hybrid, feature extraction, level sets, region growing, and watershed which are analysed...
The noninvasive assessment of cardiac function is of first importance for the diagnosis of cardiovascular diseases. Among all medical scanners only a few enables radiologists to evaluate the local car...
We propose a constrained version of Mumford and Shah's (1989) segmentation model with an information-theoretic point of view in order to devise a systematic procedure to segment brain magnetic resonan...

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