Biomedical image analysis has become a major aspect of engineering sciences, and radiology in particular has become a dominant player in the field. Recent developments have made it possible to use biomedical imaging to view the human body from an anatomical or physiological perspective in a non-invasive fashion. Computer-aided diagnosis consists of developing algorithms and intelligent software components that can automatically process images and spot potential irregularities in the health chain.

Object 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.