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2018 | OriginalPaper | Chapter

Resolve Intraoperative Brain Shift as Imitation Game

Authors : Xia Zhong, Siming Bayer, Nishant Ravikumar, Norbert Strobel, Annette Birkhold, Markus Kowarschik, Rebecca Fahrig, Andreas Maier

Published in: Simulation, Image Processing, and Ultrasound Systems for Assisted Diagnosis and Navigation

Publisher: Springer International Publishing

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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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Title: Resolve Intraoperative Brain Shift as Imitation Game
Authors: Xia Zhong
Siming Bayer
Nishant Ravikumar
Norbert Strobel
Annette Birkhold
Markus Kowarschik
Rebecca Fahrig
Andreas Maier
Publisher: Springer International Publishing
Book: Simulation, Image Processing, and Ultrasound Systems for Assisted Diagnosis and Navigation
Print ISBN: 978-3-030-01044-7

Electronic ISBN: 978-3-030-01045-4

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-030-01045-4_15

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