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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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Submitted on : Tuesday, September 5, 2017 - 2:57:30 PM
Last modification on : Monday, May 10, 2021 - 5:32:02 PM


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  • HAL Id : hal-01582003, version 1



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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