Deep learning-based simultaneous registration and unsupervised non-correspondence segmentation of medical images with pathologies.
Journal:
International journal of computer assisted radiology and surgery
Published Date:
Mar 3, 2022
Abstract
PURPOSE: The registration of medical images often suffers from missing correspondences due to inter-patient variations, pathologies and their progression leading to implausible deformations that cause misregistrations and might eliminate valuable information. Detecting non-corresponding regions simultaneously with the registration process helps generating better deformations and has been investigated thoroughly with classical iterative frameworks but rarely with deep learning-based methods.
