Fig. 12
From: Artificial intelligence with deep learning in nuclear medicine and radiology
Illustration of the deep image prior training procedure for dynamic PET denoising. A static image is used as the input \({z}\) to a network f, initialized with random weights \(\theta\). The network parameters are then iteratively optimized to produce the dynamic image x. After a certain number of iterations, denoised versions of the dynamic PET images are obtained as output. Image from [83]