Initialize globally before acting locally: Enabling landmark-free 3D US to MRI registration

Rackerseder J, Baust M, Goebl R, Navab N, Hennersperger C (2018)

Publication Type: Conference contribution

Publication year: 2018

Journal

Lecture Notes in Computer Science Springer Verlag

Publisher: Springer Verlag

Book Volume: 11070 LNCS

Pages Range: 827-835

Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Event location: Granada, ESP

ISBN: 9783030009274

DOI: 10.1007/978-3-030-00928-1_93

Abstract

Registration of partial-view 3D US volumes with MRI data is influenced by initialization. The standard of practice is using extrinsic or intrinsic landmarks, which can be very tedious to obtain. To overcome the limitations of registration initialization, we present a novel approach that is based on Euclidean distance maps derived from easily obtainable coarse segmentations. We evaluate our approach on a publicly available brain tumor dataset (RESECT) and show that it is robust regarding minimal to no overlap of target area and varying initial position. We demonstrate that our method provides initializations that greatly increase the capture range of state-of-the-art nonlinear registration algorithms.

Involved external institutions

Technische Universität München (TUM) DE Germany (DE) Konica Minolta Business Solutions Deutschland GmbH DE Germany (DE)

How to cite

APA:

Rackerseder, J., Baust, M., Goebl, R., Navab, N., & Hennersperger, C. (2018). Initialize globally before acting locally: Enabling landmark-free 3D US to MRI registration. In Julia A. Schnabel, Christos Davatzikos, Carlos Alberola-López, Gabor Fichtinger, Alejandro F. Frangi (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 827-835). Granada, ESP: Springer Verlag.

MLA:

Rackerseder, Julia, et al. "Initialize globally before acting locally: Enabling landmark-free 3D US to MRI registration." Proceedings of the 21st International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018, Granada, ESP Ed. Julia A. Schnabel, Christos Davatzikos, Carlos Alberola-López, Gabor Fichtinger, Alejandro F. Frangi, Springer Verlag, 2018. 827-835.

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