A supervised patch-based approach for human brain labeling

François Rousseau (1) , Piotr Habas (2) , Colin Studholme (2)

1 LSIIT - Laboratoire des Sciences de l'Image, de l'Informatique et de la Télédétection
2 BICG, Dept. of Pediatrics

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.

Domaines: Traitement des images [eess.IV]

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