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Chapter
Shape Based Conditional Random Fields for Segmenting Intracranial Aneurysms
Studies have found strong correlation between the risk of rupture of intracranial aneurysms and various physical measurements on the aneurysms, such as volume, surface area, neck length, among others. Accuracy...
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Chapter and Conference Paper
Deformable Registration of Organic Shapes via Surface Intrinsic Integrals: Application to Outer Ear Surfaces
We propose a method for the deformable registration of organic surfaces. Meaningful correspondences between a source surface and a target surface are established by means of a rich surface descriptor that inco...
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Chapter and Conference Paper
Layout Consistent Segmentation of 3-D Meshes via Conditional Random Fields and Spatial Ordering Constraints
We address the problem of 3-D Mesh segmentation for categories of objects with known part structure. Part labels are derived from a semantic interpretation of non-overlap** subsurfaces. Our approach models t...
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Chapter and Conference Paper
Feature Driven Rule Based Framework for Automatic Modeling of Organic Shapes in the Design of Personalized Medical Prosthetics
We propose a novel framework for the personalized design of organic shapes that are constrained to exhibit conformity with the underlying anatomy. Such constrained design is significant for several application...
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Chapter and Conference Paper
Automatic Detection of Anatomical Features on 3D Ear Impressions for Canonical Representation
We propose a shape descriptor for 3D ear impressions, derived from a comprehensive set of anatomical features. Motivated by hearing aid (HA) manufacturing, the selection of the anatomical features is carried o...
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Chapter and Conference Paper
An Anatomical Equivalence Class Based Joint Transformation-Residual Descriptor for Morphological Analysis
Existing approaches to computational anatomy assume that a perfectly conforming diffeomorphism applied to an anatomy of interest captures its morphological characteristics relative to a template. However, biol...
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Chapter and Conference Paper
Segmentation and Classification of Breast Tumor Using Dynamic Contrast-Enhanced MR Images
Accuracy of automatic cancer diagnosis is largely determined by two factors, namely, the precision of tumor segmentation, and the suitability of extracted features for discrimination between malignancy and ben...
