Report on the AAPM deep-learning sparse-view CT grand challenge.
Journal:
Medical physics
Published Date:
Feb 9, 2022
Abstract
PURPOSE: The purpose of the challenge is to find the deep-learning (DL) technique for sparse-view computed tomography (CT) image reconstruction that can yield the minimum root mean square error (RMSE) under ideal conditions, thereby addressing the question of whether or not DL can solve inverse problems in imaging.