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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.
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Yu-Wei Chang, Giovanni Volpe, 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