Automatic segmentation of age-related white matter changes on flair images: method and multicentre validation

Abstract : White matter hyperintensities (WMH) are commonly seen on T2-weighted images in elderly people. They are considered as a potential marker of vascular pathology and have been associated with motor and cognitive deficits. In this paper, non linear diffusion was applied to FLAIR images and combined with precise anatomical knowledge extracted from T1-weighted images to automatically segment WMH. Evaluation was performed on 24 patients with mild cognitive impairment (MCI) from 5 different centres. Results showed excellent volume agreement with manual delineation (Pearson coefficient: r=0.98, p<;0.001) and substantial spatial correspondence (Similarity index: 66%±17%). Our method appeared robust to acquisition differences across the centres.
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Communication dans un congrès
ISBI 2011 - 8th IEEE International Symposium on Biomedical Imaging: from Nano to Macro, Mar 2011, Chicago, United States. IEEE, pp.2014 - 2017, 2011, 〈10.1109/ISBI.2011.5872807〉
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https://hal.inria.fr/hal-00817386
Contributeur : Thomas Samaille <>
Soumis le : mercredi 24 avril 2013 - 15:04:23
Dernière modification le : jeudi 11 janvier 2018 - 06:25:29

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Thomas Samaille, Olivier Colliot, Didier Dormont, Marie Chupin. Automatic segmentation of age-related white matter changes on flair images: method and multicentre validation. ISBI 2011 - 8th IEEE International Symposium on Biomedical Imaging: from Nano to Macro, Mar 2011, Chicago, United States. IEEE, pp.2014 - 2017, 2011, 〈10.1109/ISBI.2011.5872807〉. 〈hal-00817386〉

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