Report on the AAPM Grand Challenge on deep generative modeling for learning medical image statistics

arXiv:2405.01822v1 Announce Type: cross
Abstract: The findings of the 2023 AAPM Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics are reported in this Special Report. The goal of this challenge was to promote the development of deep generative models (DGMs) for medical imaging and to emphasize the need for their domain-relevant assessment via the analysis of relevant image statistics. As part of this Grand Challenge, a training dataset was developed based on 3D anthropomorphic breast phantoms from …

abstract arxiv challenge cs.cv deep generative models development dgms eess.iv generative generative modeling generative models image medical modeling physics.med-ph promote report statistics type