A Supervised Patch-based Approach for Human Brain Labeling

Overview

Journal IEEE Trans Med Imaging

Date 2011 May 25

PMID 21606021

Citations 98

Authors

Franccois Rousseau

Piotr A Habas

Colin Studholme

Affiliations

Soon will be listed here.

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.

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