This book offers a unique guide to the entire chain of biomedical imaging, explaining how image formation is done, and how the most appropriate algorithms are used to address demands and diagnoses. It is an exceptional tool for radiologists, research scientists, senior undergraduate and graduate students in health sciences and engineering, and university professors.

InhaltsangabeObject Segmentation and Markov Random Fields.- Fuzzy methods in medical imaging.- Curve Propagation, Level Set Methods and Grouping.- Kernel Methods in Medical Imaging.- Geometric Deformable Models: Overview and Recent Developments.- Active Shape and Appearance Models.- Statistical Atlases.- Statistical Computing on Non-Linear Spaces for Computational Anatomy.- Building Patient-Specific Physical and Physiological Computational Models from Medical Images.- Constructing a Patient-Specific Model Heart from CT Data.- Image-based haemodynamics simulation in intracranial aneursyms.- Atlas-based Segmentation.- Integration of Topological Constraints in Medical Image Segmentation.- Monte Carlo Sampling for the Segmentation of Tubular Structures.- Non-rigid registration using free-form deformations.- Image registration using mutual information.- Physical Model Based Recovery of Displacement and Deformations from 3D medical images.- Cardiovascular Informatics.- Rheumatoid Arthritis Quantifiction using Appearance Models.- Medical Image Processing for Analysis of Colon Motility.- Segmentation of Diseased Livers: A 3D Refinement Approach.- Intra and inter subject analyses of brain functional Magnetic Resonance Images (fMRI).- Diffusion Tensor Estimation, Regularization and Classification.- From Local Q-Ball Estimation to Fibre Crossing Tractography.- Segmentation of clustered cells in microscopy images by geometric PDEs and level sets.- Atlas-based whole-body registration in mice.

Hersteller:
Springer Verlag GmbH
juergen.hartmann@springer.com
Tiergartenstr. 17
DE 69121 Heidelberg