2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDMLR-APPL-BSIP.7
Paper Title EXPLAINING 3D CNNs FOR ALZHEIMER'S DISEASE CLASSIFICATION ON sMRI IMAGES WITH MULTIPLE ROIs
Authors Meghna P Ayyar, Jenny Benois-Pineau, Akka Zemmari, University of Bordeaux, Laboratoire Bordelais de Recherche en Informatique, France; Gwenaelle Catheline, Centre national de la recherche scientifique, Institut de Neurosciences Cognitives et Intégratives d’Aquitaine, France
SessionMLR-APPL-BSIP: Machine learning for biomedical signal and image processing
LocationArea C
Session Time:Wednesday, 22 September, 08:00 - 09:30
Presentation Time:Wednesday, 22 September, 08:00 - 09:30
Presentation Poster
Topic Applications of Machine Learning: Machine learning for biomedical signal and image processing
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Classification of Alzheimer’s disease from 3D structural Magnetic Resonance Imaging (sMRI) with deep neural networks has shown promising results in recent years. The decision interpretation of these networks is essential to aid medical experts to understand and rely on the results provided by such models. In this paper, we propose an adaptation of a recently developed feature-based explanation method and apply it to a 3D CNN architecture for the binary classification of Alzheimer’s disease and Normal Control from the hippocampal ROIs of brain sMRIs. We also compare our method to the state-of-the-art LRP method.