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Published in:
2007 | OriginalPaper | Chapter
LOCUS: LOcal Cooperative Unified Segmentation of MRI Brain Scans
Authors : B. Scherrer, M. Dojat, F. Forbes, C. Garbay
Published in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007
Publisher: Springer Berlin Heidelberg
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We propose to carry out cooperatively both tissue and structure segmentations by distributing a set of
local
and
cooperative
models in a unified MRF framework. Tissue segmentation is performed by partitionning the volume into subvolumes where local MRFs are estimated in cooperation with their neighbors to ensure consistency. Local estimation fits precisely to the local intensity distribution and thus handles nonuniformity of intensity without any bias field modelization. Structure segmentation is performed via local MRFs that integrate localization constraints provided by
a priori
general fuzzy description of brain anatomy. Structure segmentation is not reduced to a postprocessing step but cooperates with tissue segmentation to gradually and conjointly improve models accuracy. The evaluation was performed using phantoms and real 3T brain scans. It shows good results and in particular robustness to nonuniformity and noise with a low computational cost.