Automatic non-linear MRI-ultrasound registration for the correction of intra-operative brain deformations

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Abstract

Movements of brain tissue during neurosurgical procedures reduce the effectiveness of using pre-operative images for intra-operative surgical guidance. In this paper, we explore the use of acquiring intraoperative ultrasound (US) images for the quantification of and correction for non-linear brain deformations. We will present a multi-modal, automatic registration strategy that matches pre-operative images (e.g. MRI) to intra-operative ultrasound to correct for the non-linear brain deformations. The strategy involves using the predicted appearance of neuroanatomical structures in ultrasound images to build “pseudo ultrasound” images based on pre-operative segmented MRI. These images can then be registered to intra-operative US in a strategy based on crosscorrelation measurements generated from the ANIMAL [1] registration package. The feasibility of the theory is demonstrated through its application to clinical patient data acquired during 12 neurosurgical procedures. Qualitative examination of the results indicate that the system is able to correct for non-linear brain deformations.

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APA

Arbel, T., Morandi, X., Comeau, R. M., & Louis Collins, D. (2001). Automatic non-linear MRI-ultrasound registration for the correction of intra-operative brain deformations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2208, pp. 913–922). Springer Verlag. https://doi.org/10.1007/3-540-45468-3_109

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