Radiomics Analysis of Subcortical Brain Regions Related to Alzheimer Disease

Ahmad Chaddad1, Tamim Niazi2

  • 1University of Quebec, Ecole de Technologie superieure
  • 2McGill University

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Category

Poster Session

Sessions

10:00 - 17:00 | Tue 30 Oct | Foyer | B1P-D

Engineering for Life Sciences

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Abstract

We proposed to investigate radiomic features derived from different subcortical brain regions to identify Alzheimer disease (AD), using a random forest classifier model to identify the most important features. Our result suggests that the hippocampus and amygdala are the regions of the brain most different between AD and healthy control (HC) subjects and that “correlation” and “volume” are the most important features for diagnosing AD. Our findings indicated that radiomic features including the histogram, texture and shape features can effectively predict AD patients.

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