Deformable image registration by multi-objective optimization using a dual-dynamic transformation model to account for large anatomical differences

Tanja Alderliesten; Jan-Jakob Sonke; Peter A. N. Bosman

doi:10.1117/12.2006783

13 March 2013 Deformable image registration by multi-objective optimization using a dual-dynamic transformation model to account for large anatomical differences

Tanja Alderliesten, Jan-Jakob Sonke, Peter A. N. Bosman

Author Affiliations +

Proceedings Volume 8669, Medical Imaging 2013: Image Processing; 866910 (2013) https://doi.org/10.1117/12.2006783
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

Some of the hardest problems in deformable image registration are problems where large anatomical differences occur between image acquisitions (e.g. large deformations due to images acquired in prone and supine positions and (dis)appearing structures between image acquisitions due to surgery). In this work we developed and studied, within a previously introduced multi-objective optimization framework, a dual-dynamic transformation model to be able to tackle such hard problems. This model consists of two non-fixed grids: one for the source image and one for the target image. By not requiring a fixed, i.e. pre-determined, association of the grid with the source image, we can accommodate for both large deformations and (dis)appearing structures. To find the transformation that aligns the source with the target image we used an advanced, powerful model-based evolutionary algorithm that exploits features of a problem’s structure in a principled manner via probabilistic modeling. The actual transformation is given by the association of coordinates with each point in the two grids. Linear interpolation inside a simplex was used to extend the correspondence (i.e. transformation) as found for the grid to the rest of the volume. As a proof of concept we performed tests on both artificial and real data with disappearing structures. Furthermore, the case of prone-supine image registration for 2D axial slices of breast MRI scans was evaluated. Results demonstrate strong potential of the proposed approach to account for large deformations and (dis)appearing structures in deformable image registration.

Citation Download Citation

Tanja Alderliesten, Jan-Jakob Sonke, and Peter A. N. Bosman "Deformable image registration by multi-objective optimization using a dual-dynamic transformation model to account for large anatomical differences", Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 866910 (13 March 2013); https://doi.org/10.1117/12.2006783

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