Handbook of Biomedical Image Analysis Vol. 2 - Segmentation Models Part B (Kluwer, 2005).pdf

Handbook of Biomedical Image Analysis: Segmentation Models (Volume II) is dedicated to the segmentation of complex shapes from the field of imaging sciences using different mathematical techniques. This volume is aimed at researchers and educators in imaging sciences, radiological imaging, clinical and diagnostic imaging, physicists covering different medical imaging modalities, as well as researchers in biomedical engineering, applied mathematics, algorithmic development, computer vision, signal processing, computer graphics and multimedia in general, both in academia and industry.

Key Features:

--- Model-based brain tissue classification

--- Supervised texture classification for intravascular tissue characterization

--- Medical image segmentation: methods and applications in functional imaging

--- Automatic segmentation of pancreatic tumors in CT

--- Computerized analysis and vasodilation parameterization in flow-mediated dilation tests from ultrasonic image sequences

--- Adaptive approaches to optical segmentation in brain MRI Images

--- Automatic analysis of color fundus photographs and its application to the diagnosis of diabetic retinopathy

--- Segmentation issues of carotid plaque analysis in MRI

--- Accurate lumen identification, detection, and quantification in MR plaque volumes

--- Hessian-based multiscale enhancement, description, and quantification of second-order 3D local structures from medical volume data

--- A knowledge-based scheme for digital mammography

--- Simultaneous fuzzy segmentation

--- CAD of mammographic calicification: impact of segmentation