Validation of deep learning-based nonspecific estimates for amyloid burden quantification with longitudinal data.

Journal: Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Published Date:

Abstract

PURPOSE: To validate our previously proposed method of quantifying amyloid-beta (Aβ) load using nonspecific (NS) estimates generated with convolutional neural networks (CNNs) using [F]Florbetapir scans from longitudinal and multicenter ADNI data.

Authors

  • Ying-Hwey Nai
    Clinical Imaging Research Centre, Yong Loo Lin School of Medicine, National University of Singapore, Centre for Translational Medicine (MD6), 14 Medical Drive, #B1-01, Singapore, 117599, Singapore. mednyh@nus.edu.sg.
  • Haohui Liu
    Raffles Institution, Singapore, Singapore.
  • Anthonin Reilhac
    Clinical Imaging Research Centre, Yong Loo Lin School of Medicine, National University of Singapore, Centre for Translational Medicine (MD6), 14 Medical Drive, #B1-01, Singapore, 117599, Singapore.