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Title: Improved Prediction of Cognitive Outcomes via Globally Aligned Imaging Biomarker Enrichments over Progressions
Incomplete or inconsistent temporal neuroimaging records of patients over time pose a major challenge to accurately predict clinical scores for diagnosing Alzheimer’s Disease (AD). In this paper, we present an unsupervised method to learn enriched imaging biomarker representations that can simultaneously capture the information conveyed by all the baseline neuroimaging measures and the progressive variations of the available follow-up measurements of every participant. Our experiments on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset show improved performance in predicting cognitive outcomes thereby demonstrating the effectiveness of our proposed method.  more » « less
Award ID(s):
1837964 1652943 1849359
NSF-PAR ID:
10127254
Author(s) / Creator(s):
; ; ; ; ;
Date Published:
Journal Name:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019
Volume:
LNCS 11767
Page Range / eLocation ID:
140-148
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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