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Prior Knowledge Driven Multiscale Segmentation of Brain MRI
Institution:
 Department of Computer Science and Applied Math, Weizmann Institute of Science, Rehovot, Israel.
Publisher:
 Med Image Comput Comput Assist Interv. MICCAI 2007
Publication Date:
 Oct-2007
Volume Number:
 10
Issue Number:
 2
Pages:
 118-126
Citation:
 Int Conf Med Image Comput Comput Assist Interv. 2007;10(Pt 2):118-26.
PubMed ID:
 18044560
Appears in Collections:
Miscellaneous, SLICER
Sponsors:
 Binational Science foundation, Grant No. 2002/254
European Commission Project IST-2002-506766 Aim Shape
Generated Citation:
 Akselrod-Ballin A., Galun M., Gomori J.M., Brandt A., Basri R. Prior Knowledge Driven Multiscale Segmentation of Brain MRI. Int Conf Med Image Comput Comput Assist Interv. 2007;10(Pt 2):118-26. PMID: 18044560.
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We present a novel automatic multiscale algorithm applied to segmentation of anatomical structures in brain MRI. The algorithm which is derived from algebraic multigrid, uses a graph representation of the image and performs a coarsening process that produces a full hierarchy of segments. Our main contribution is the incorporation of prior knowledge information into the multiscale framework through a Bayesian formulation. The probabilistic information is based on an atlas prior and on a likelihood function estimated from a manually labeled training set. The significance of our new approach is that the constructed pyramid, reflects the prior knowledge formulated. This leads to an accurate and efficient methodology for detection of various anatomical structures simultaneously. Quantitative validation results on gold standard MRI show the benefit of our approach.

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Akselrod-Ballin-MICCAI2007-fig1.jpg (334.871kB)