BibTeX
@MISC{Disease_topic,
author = {Of Alzheimer's Disease and Université De Bordeaux},
title = {Topic},
year = {}
}
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Abstract
Detection of Alzheimer's disease at the first stages of the pathology is an important task to accelerate the development of new therapies and improve treatment. However, the early detection of this pathology is complex because the associated anatomical changes are very subtle. Recently, we developed a new method enables to provide accurate detection of Alzheimer’s disease based on structural MRI [1]. This method obtained very competitive results compared to state-‐of-‐the-‐art method. However, the accuracy of early detection of this method is not yet clinically usable and can be further improved [2]. The candidate will investigate the possibility to use/fuse information derived from sevral MRI modalities in order to improve the accuracy of early detection. The optimization of features extraction, features fusion, and features classification procedures will be studied. The candidate will benefit from the expertise in image processing of the LaBRI (Computer science laboratory of Bordeaux) and from the clinical expertise on Alzheimer’s disease of the Hospital of Bordeaux.
Keyphrases
early detection alzheimer disease computer science laboratory first stage clinical expertise image processing sevral mri modality structural mri new therapy important task competitive result feature classification procedure art method fuse information feature extraction accurate detection new method enables associated anatomical change
