Abstract #4704

Ultra-low-dose Amyloid PET/MRI Reconstruction by Generative Adversarial Network

Jiahong Ouyang¹, Kevin T. Chen², Enhao Gong², John Pauly², and Greg Zaharchuk²

¹Carnegie Mellon University, Pittsburgh, PA, United States, ²Stanford University, Stanford, CA, United States

Amyloid PET is widely used in the early diagnosis of dementia. However, the injection of the radiotracer will lead to radiation exposure to the subject. We proposed a novel method based on Generative Adversarial Network (GAN) with perceptual loss to achieve diagnostic image quality PET images using ultra-low-dose PET images with or without additional MR contrasts as inputs.

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