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Titlebook: Medical Computer Vision: Recognition Techniques and Applications in Medical Imaging; Second International Bjoern H. Menze,Georg Langs,Anton

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Multiple Atlases-Based Joint Labeling of Human Cortical Sulcal Curvesework. Compared to the conventional method, we propose to use neighboring curves for avoiding ambiguity in curve-by-curve labeling and to integrate the labeling results obtained from multiple atlases for consistent labeling. In particular, we compute a histogram of points on the neighboring curves a
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Fast Anatomical Structure Localization Using Top-Down Image Patch Regression automatic processing of large amounts of data. We present a simple, accurate and fast approach with low computational complexity to find anatomical landmarks, based on a multi-scale regression codebook of informative image patches and encoded landmark contexts..From a set of annotated training volu
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Oblique Random Forests for 3-D Vessel Detection Using Steerable Filters and Orthogonal Subspace FiltOne is based on orthogonal subspace filtering where we learn 3-D eigenspace filters from local image patches that return task optimal feature responses. The other uses a specific set of steerable filters that show, qualitatively, similarities to the learned eigenspace filters, but also allow for exp
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Pipeline for Tracking Neural Progenitor Cellsgery of . cell growth experiments. Segmentation algorithms with the ability to adapt to the problem at hand and robust tracking methods play a key role in constructing these lineages. We present here a tracking pipeline based on learning a dictionary of discriminative image patches for segmentation
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Randomness and Sparsity Induced Codebook Learning with Application to Cancer Image Classificationorithm, Randomized Forest Sparse Coding (RFSC), by harvesting the following three concepts: (1) ensemble learning, (2) divide-and-conquer, and (3) sparse coding. Given a set of training data, a randomized tree can be used to perform data partition (divide-and-conquer); after a tree is built, a numbe
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Context Enhanced Graphical Model for Object Localization in Medical Imagesoaches tackling this problem, and focus on the work by Song et.al. [20]. In [20], a new graphical model with additional contrast and interest-region potentials is designed, encoding the higher-order contextual information between regions, on the global and structural levels. A discriminative sparse-
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lly no substantial electronic overlap between the molecules1; interactions are based on mere van der Waals forces in the very large class of neutral molecular crystals (or on a combination of van der Waals and local [closed shell] Coulombic interactions in the barely studied class of ionic organic c
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