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Proceedings Paper

Competitive segmentation of the hippocampus and the amygdala from MRI data: validation on young healthy controls and Alzheimer’s disease patients
Author(s): Marie Chupin; Dominique Hasboun; Romain Mukuna-Bantumbakulu; Eric Bardinet; Sylvain Baillet; Serge Kinkingnéhun; Louis Lemieux; Bruno Dubois; Line Garnero
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Paper Abstract

The hippocampus (Hc) and the amygdala (Am) are two cerebral structures that play a central role in main cognitive processes. Their segmentation allows atrophy in specific neurological illnesses to be quantified, but is made difficult by the complexity of the structures. In this work, a new algorithm for the simultaneous segmentation of Hc and Am based on competitive homotopic region deformations is presented. The deformations are constrained by relational priors derived from anatomical knowledge, namely probabilities for each structure around automatically retrieved landmarks at the border of the objects. The approach is designed to perform well on data from diseased subjects. The segmentation is initialized by extracting a bounding box and positioning two seeds; total execution time for both sides is between 10 and 15 minutes including initialization for the two structures. We present the results of validation based on comparison with manual segmentation, using volume error, spatial overlap and border distance measures. For 8 young healthy subjects the mean volume error was 7% for Hc and 11% for Am, the overlap: 84% for Hc and 83% for Am, the maximal distance: 4.2mm for Hc and 3.1mm for Am; for 4 Alzheimer's disease patients the mean volume error was 9% for Hc and Am, the overlap: 83% for Hc and 78% for Am, the maximal distance: 6mm for Hc and 4.4mm for Am. We conclude that the performance of the proposed method compares favourably with that of other published approaches in terms of accuracy and has a short execution time.

Paper Details

Date Published: 10 March 2006
PDF: 11 pages
Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61440K (10 March 2006); doi: 10.1117/12.653400
Show Author Affiliations
Marie Chupin, Univ. College London (United Kingdom)
Lab. de Neurosciences Cognitives et Imagerie Cérébrale, CNRS (France)
IFR 49 Imagerie NeuroFonctionnelle (France)
Dominique Hasboun, Lab. de Neurosciences Cognitives et Imagerie Cérébrale, CNRS (France)
IFR 49 Imagerie NeuroFonctionnelle (France)
Romain Mukuna-Bantumbakulu, INSERM (France)
IFR 49 Imagerie NeuroFonctionnelle (France)
Eric Bardinet, Lab. de Neurosciences Cognitives et Imagerie Cérébrale, CNRS (France)
IFR 49 Imagerie NeuroFonctionnelle (France)
Sylvain Baillet, Lab. de Neurosciences Cognitives et Imagerie Cérébrale, CNRS (France)
IFR 49 Imagerie NeuroFonctionnelle (France)
Serge Kinkingnéhun, INSERM (France)
IFR 49 Imagerie NeuroFonctionnelle (France)
Louis Lemieux, Univ. College London (United Kingdom)
Bruno Dubois, INSERM (France)
IFR 49 Imagerie NeuroFonctionnelle (France)
Line Garnero, Lab. de Neurosciences Cognitives et Imagerie Cérébrale, CNRS (France)
IFR 49 Imagerie NeuroFonctionnelle (France)


Published in SPIE Proceedings Vol. 6144:
Medical Imaging 2006: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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