Resolve Intraoperative Brain Shift as Imitation Game

Zhong X, Bayer S, Ravikumar N, Strobel N, Birkhold A, Kowarschik M, Fahrig R, Maier A (2018)

Publication Type: Conference contribution, Conference Contribution

Publication year: 2018

Event location: Granada conference center

URI: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2018/Zhong18-RIB.pdf

DOI: 10.1007/978-3-030-01045-4_15

Abstract

Soft tissue deformation induced by craniotomy and tissue manipulation (brain shift) limits the use of preoperative image overlay in an image-guided neurosurgery, and therefore reduces the accuracy of the surgery as a consequence. An inexpensive modality to compensate for the brain shift in real-time is Ultrasound (US). The core subject of research in this context is the non-rigid registration of preoperative MR and intraoperative US images. In this work, we propose a learning based approach to address this challenge. Resolving intraoperative brain shift is considered as an imitation game, where the optimal action (displacement) for each landmark on MR is trained with a multi-task network. The result shows a mean target error of 1.21 ± 0.55 mm.

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Siemens Healthineers Germany (DE)

How to cite

APA:

Zhong, X., Bayer, S., Ravikumar, N., Strobel, N., Birkhold, A., Kowarschik, M.,... Maier, A. (2018). Resolve Intraoperative Brain Shift as Imitation Game. In Proceedings of the MICCAI Challenge 2018 for Correction of Brainshift with Intra-Operative Ultrasound (CuRIOUS 2018). Granada conference center.

MLA:

Zhong, Xia, et al. "Resolve Intraoperative Brain Shift as Imitation Game." Proceedings of the MICCAI Challenge 2018 for Correction of Brainshift with Intra-Operative Ultrasound (CuRIOUS 2018), Granada conference center 2018.

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