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| Research article summary (published 30 May 2002): |
Automatic recognition of cortical sulci of the human brain using a congregation of neural networks.
Full Abstract
This paper describes a complete system allowing automatic recognition of the main sulci of the human cortex. This system relies on a preprocessing of magnetic resonance images leading to abstract structural representations of the cortical folding patterns. The representation nodes are cortical folds, which are given a sulcus name by a contextual pattern recognition method. This method can be interpreted as a graph matching approach, which is driven by the minimization of a global function made up of local potentials. Each potential is a measure of the likelihood of the labelling of a restricted area. This potential is given by a multi-layer perceptron trained on a learning database. A base of 26 brains manually labelled by a neuroanatomist is used to validate our approach. The whole system developed for the right hemisphere is made up of 265 neural networks. The mean recognition rate is 86% for the learning base and 76% for a generalization base, which is very satisfying considering the current weak understanding of the variability of the cortical folding patterns.
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Author information
Author/s: Rivière, Denis (D); Mangin, Jean-François (JF); Papadopoulos-Orfanos, Dimitri (D); Martinez, Jean-Marc (JM); Frouin, Vincent (V); Régis, Jean (J);
Affiliation: Service Hospitalier Frédéric Joliot, CEA, 4 place du Général Leclerc, 91401 Orsay, France. riviere@shfj.cea.fr
Journal and publication information
Publication Type: Journal Article; Review
Journal: Medical image analysis (Med Image Anal), published in England. (Language: eng)
Reference: 2002-Jun; vol 6 (issue 2) : pp 77-92
Dates: Created 2002/06/04; Completed 2002/09/17; Revised 2005/11/16;
PMID: 12044997, status: MEDLINE (last retrieval date: 11/6/2008)
Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.
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