AUTHOR=Andresen Julia , Uzunova Hristina , Ehrhardt Jan , Kepp Timo , Handels Heinz TITLE=Image registration and appearance adaptation in non-correspondent image regions for new MS lesions detection JOURNAL=Frontiers in Neuroscience VOLUME=16 YEAR=2022 URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2022.981523 DOI=10.3389/fnins.2022.981523 ISSN=1662-453X ABSTRACT=

Manual detection of newly formed lesions in multiple sclerosis is an important but tedious and difficult task. Several approaches for automating the detection of new lesions have recently been proposed, but they tend to either overestimate the actual amount of new lesions or to miss many lesions. In this paper, an image registration convolutional neural network (CNN) that adapts the baseline image to the follow-up image by spatial deformations and simulation of new lesions is proposed. Simultaneously, segmentations of new lesions are generated, which are shown to reliably estimate the real new lesion load and to separate stable and progressive patients. Several applications of the proposed network emerge: image registration, detection and segmentation of new lesions, and modeling of new MS lesions. The modeled lesions offer the possibility to investigate the intensity profile of new lesions.