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Deformable image registration with automatic non-correspondence detection

 
: Chen, K.; Derksen, A.; Heldmann, S.; Hallmann, M.; Berkels, B.

:

Aujol, J.-F.:
Scale space and variational methods in computer vision. 5th international conference, SSVM 2015 : Lège-Cap Ferret, France, May 31-June 4, 2015; Proceedings
Cham: Springer International Publishing, 2015 (Lecture Notes in Computer Science 9087)
ISBN: 978-3-319-18460-9 (Print)
ISBN: 978-3-319-18461-6 (Online)
S.360-371
International Conference on Scale Space and Variational Methods in Computer Vision (SSVM) <5, 2015, Lège-Cap Ferret>
Englisch
Konferenzbeitrag
Fraunhofer MEVIS ()

Abstract
Image registration aims at establishing pointwise correspondences between given images. However, in many practical applications, no correspondences can be established in certain parts of the images. A typical example is the tumor resection area in pre- and post-operative medical images. In this paper, we introduce a novel variational framework that combines registration with an automatic detection of non-correspondence regions. The formulation of the proposed approach is simple but efficient, and compatible with a large class of image registration similarity measures and regularizers. The resulting minimization problem is solved numerically with a non-alternating gradient flow scheme. Furthermore, the method is validated on synthetic data as well as axial slices of pre-, post- and intra-operative MR T1 head scans.

: http://publica.fraunhofer.de/dokumente/N-352458.html