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A supervised patch-based approach for human brain labeling

Abstract : We propose in this work a patch-based image labeling method relying on a label propagation frame- work. Based on image intensity similarities between the input image and an anatomy textbook, an original strategy which does not require any non-rigid registration is presented. Following recent devel- opments in non-local 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 MR images show that the proposed method is very successful in providing automated human brain labeling.
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https://hal.archives-ouvertes.fr/hal-00631458
Contributor : François Rousseau Connect in order to contact the contributor
Submitted on : Wednesday, October 12, 2011 - 2:18:15 PM
Last modification on : Tuesday, July 23, 2019 - 1:40:03 PM
Long-term archiving on: : Friday, January 13, 2012 - 3:05:24 AM

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François Rousseau, Piotr Habas, Colin Studholme. A supervised patch-based approach for human brain labeling. IEEE Transactions on Medical Imaging, Institute of Electrical and Electronics Engineers, 2011, 30 (10), http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5771116. ⟨10.1109/TMI.2011.2156806⟩. ⟨hal-00631458⟩

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