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Abstract #1465

Identifying Alzheimer's Disease Brain Atrophy Subtypes by Deep Learning

Xingjuan Li1, Jurgen Fripp1, Samantha Burnham2, Vincent Doré2, and Pierrick Bourgeat1
1Australian eHealth Research Center, CSIRO, Brisbane, Australia, 2Australian eHealth Research Center, CSIRO, Melbourne, Australia

Understanding the heterogeneity in atrophy changes from Alzheimer's disease (AD) can be an important factor to develop effective drugs and improve patients' outcomes [7]. In this study, we propose a deep learning approach to identify AD subtypes based on T1w magnetic resonance images (MRI). Experimental results show that the proposed method can accurately identify four AD subtypes exhibiting a distinctive cortical atrophy pattern.

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