Synthesizing tau pathology from structural brain imaging using deep learning

Yu-Wei Chang; Giovanni Volpe; Joana B. Pereira

doi:10.1117/12.2678556

28 September 2023 Synthesizing tau pathology from structural brain imaging using deep learning

Yu-Wei Chang, Giovanni Volpe, Joana B. Pereira

Proceedings Volume PC12655, Emerging Topics in Artificial Intelligence (ETAI) 2023; PC1265509 (2023) https://doi.org/10.1117/12.2678556
Event: SPIE Nanoscience + Engineering, 2023, San Diego, California, United States

Abstract

This study proposes a new approach to diagnose Alzheimer's disease by using a generative adversarial network (GAN) applied to T1-weighted scans to predict tau pathology on positron emission tomography (PET) images. We used a cohort of 259 participants across different stages stages of Alzheimer’s disease from the Alzheimer's Disease Neuroimaging Initiative. The proposed 3D pix2pix GAN model was more successful than other models in synthesizing regional tau-PET signals from structural brain scans, holding great promise as a tool for multi-modal diagnosis and allowing to assess the underlying disease’s pathology without the need of exposing patients to radiation.

Conference Presentation

Citation Download Citation

Yu-Wei Chang, Giovanni Volpe, and Joana B. Pereira "Synthesizing tau pathology from structural brain imaging using deep learning", Proc. SPIE PC12655, Emerging Topics in Artificial Intelligence (ETAI) 2023, PC1265509 (28 September 2023); https://doi.org/10.1117/12.2678556

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available