Adaptive fusion of texture-based grading: Application to Alzheimer's disease detection

Abstract : Alzheimer's disease is a neurodegenerative process leading to irreversible mental dysfunctions. The development of new biomark-ers is crucial to perform an early detection of this disease. Among new biomarkers proposed during the last decades, patch-based grading framework demonstrated state-of-the-art results. In this paper, we study the potential using texture information based on Gabor lters to improve patch-based grading method performance, with a focus on the hippocam-pal structure. We also propose a novel fusion framework to eciently combine multiple grading maps derived from a Gabor lters bank. Finally , we compare our new texture-based grading biomarker with the state-of-the-art approaches to demonstrate the high potential of the proposed method.
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PatchMI: 3rd International Workshop on Patch-based Techniques in Medical Imaging, Sep 2017, Quebec, Canada
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Contributeur : Kilian Hett <>
Soumis le : mardi 5 septembre 2017 - 14:57:30
Dernière modification le : jeudi 7 septembre 2017 - 11:46:55

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Kilian Hett, Vinh-Thong Ta, José Manjón, Pierrick Coupé. Adaptive fusion of texture-based grading: Application to Alzheimer's disease detection. PatchMI: 3rd International Workshop on Patch-based Techniques in Medical Imaging, Sep 2017, Quebec, Canada. 〈hal-01582003〉

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