Heatmaps autoencoders robustly capture Alzheimer’s disease’s brain alterations

Di Wang; Nicolas Honnorat; Anoop Benet Nirmala; Peter T. Fox; Sudha Seshadri; Mohamad Habes

doi:10.1117/12.3008579

2 April 2024 Heatmaps autoencoders robustly capture Alzheimer’s disease’s brain alterations

Di Wang, Nicolas Honnorat, Anoop Benet Nirmala, Peter T. Fox, Sudha Seshadri, Mohamad Habes

Author Affiliations +

Proceedings Volume 12930, Medical Imaging 2024: Clinical and Biomedical Imaging; 129302C (2024) https://doi.org/10.1117/12.3008579
Event: SPIE Medical Imaging, 2024, San Diego, California, United States

Conference Poster

Abstract

Deep neural networks have achieved unprecedented success in diagnosing patients with Alzheimer’s Disease from their MRI scans. Unfortunately, the decisions taken by these complex nonlinear architectures are difficult to interpret. Heatmap methods were introduced to visualize the deep learning models that are trained after classifying groups, but very few quantitative comparisons have been conducted so far to determine what approaches would be the most accurate in representing patterns learned by a deep learning model. In this work, we propose to use autoencoders to fuse the maps generated by different heatmap methods to produce a more reliable brain map. We establish that combining the heatmaps produced by Layer-wise Relevance Propagation, Integrated Gradients, and the Guided Grad-CAM method for a CNN trained using 502 T1 MRI scans provided by the Alzheimer’s Disease Neuroimaging Initiative produces brain maps better capturing the Alzheimer’s Disease effects reported in a large independent meta-analysis combining 77 voxel-based morphometry studies. These results suggest that our nonlinear maps fusion is a promising approach to take advantage of the great variety of heatmap methods recently published and produce a map with robust feature representation and less noise.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Di Wang, Nicolas Honnorat, Anoop Benet Nirmala, Peter T. Fox, Sudha Seshadri, and Mohamad Habes "Heatmaps autoencoders robustly capture Alzheimer’s disease’s brain alterations", Proc. SPIE 12930, Medical Imaging 2024: Clinical and Biomedical Imaging, 129302C (2 April 2024); https://doi.org/10.1117/12.3008579

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