Titlebook: Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2004; 7th International Co Christian Barillot,David R. Haynor,Pierre H

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Automatic Segmentation of Neonatal Brain MRIo its potential for studying early growth patterns and morphologic change in neurodevelopmental disorders. Automatic segmentation of these images is a challenging task mainly due to the low intensity contrast and the non-uniformity of white matter intensities, where white matter can be divided into

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Segmentation of 3D Probability Density Fields by Surface Evolution: Application to Diffusion MRIcations in medical images processing, in particular for diffusion magnetic resonance imaging where each voxel is assigned with a function describing the average motion of water molecules. Being able to automatically extract relevant anatomical structures of the white matter, such as the ., would dra

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Improved EM-Based Tissue Segmentation and Partial Volume Effect Quantification in Multi-sequence Bramodel in MRI, and employs a probabilistic brain atlas as a prior to produce a segmentation of white matter, grey matter and cerebro-spinal fluid (CSF). However, several artifacts can alter the segmentation process. For example, CSF is not a well defined class because of the large quantity of voxels

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A Semi-automatic Endocardial Border Detection Method for 4D Ultrasound Dataerating on 2D slices of the 3D+T data, for the estimation of LV volume, with minimal user interaction. It shows good correlations with MRI ED and ES volumes (r=0.938) and low interobserver variability (y=1.005x-16.7, r=0.943) over full-cycle volume estimations. It shows a high consistency in trackin

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Vessel Segmentation Using a Shape Driven Flowegment due to their branching and thinning geometry as well as the decrease in image contrast from the root of the vessel to its thin branches. Using image intensity alone to deform a model for the task of segmentation often results in leakages at areas where the image information is ambiguous. To a

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Learning Coupled Prior Shape and Appearance Models for Segmentationand orientations. The shape and intensity spaces are unified by implicitly representing shapes as “images” in the space of distance transforms. A stochastic chord-based matching algorithm is developed to align photo-realistic training examples under a common reference frame. Then dense local deforma