@article {1446,
	title = {Deep learning-based simultaneous registration and unsupervised non-correspondence segmentation of medical images with pathologies},
	journal = {International Journal of Computer Assisted Radiology and Surgery},
	year = {2022},
	abstract = {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.},
	issn = {1861-6429},
	doi = {10.1007/s11548-022-02577-4},
	author = {Andresen, Julia and Timo Kepp and Jan Ehrhardt and von der Burchard, Claus and Roider, Johann and Heinz Handels}
}
