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IEEE Trans Med Imaging. 2011 Oct;30(10):1852-62. doi: 10.1109/TMI.2011.2156806. Epub 2011 May 19.

A supervised patch-based approach for human brain labeling.

Author information

1
Laboratoire des Sciences de l’Image, de l’Informatique et de la Télédétection (LSIIT), UMR 7005 CNRS-University of Strasbourg, 67412 Illkirch, France. rousseau@unistra.fr

Abstract

We propose in this work a patch-based image labeling method relying on a label propagation framework. Based on image intensity similarities between the input image and an anatomy textbook, an original strategy which does not require any nonrigid registration is presented. Following recent developments in nonlocal image denoising, the similarity between images is represented by a weighted graph computed from an intensity-based distance between patches. Experiments on simulated and in vivo magnetic resonance images show that the proposed method is very successful in providing automated human brain labeling.

PMID:
21606021
PMCID:
PMC3318921
DOI:
10.1109/TMI.2011.2156806
[Indexed for MEDLINE]
Free PMC Article

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