Abstract
Tissue deformation during brain tumor removal often renders the original surgical plan invalid. This can greatly affect the quality of resection, and thus threaten the patient’s survival rate. Therefore, correction of such deformation is needed, which can be achieved through image registration between pre- and intra-operative images. We proposed a novel automatic inter-modal affine registration technique based on the correlation ratio (CR) similarity metric. The technique was demonstrated through registering intra-operative ultrasound (US) scans with magnetic resonance (MR) images of patients, who underwent brain gliomas resection. By using landmark-based mean target registration errors (TRE) for evaluation, our technique has achieved a result of 2.32 ± 0.68 mm from the initial 5.13 ± 2.78 mm.
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Acknowledgement
This work is funded by Natural Science Engineering Council of Canada (NSERC) grant RGPIN-2015-04136. The authors would like to thank anonymous reviewers for their valuable feedback.
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Masoumi, N., Xiao, Y., Rivaz, H. (2018). MARCEL (Inter-Modality Affine Registration with CorrELation Ratio): An Application for Brain Shift Correction in Ultrasound-Guided Brain Tumor Resection. In: Crimi, A., Bakas, S., Kuijf, H., Menze, B., Reyes, M. (eds) Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2017. Lecture Notes in Computer Science(), vol 10670. Springer, Cham. https://doi.org/10.1007/978-3-319-75238-9_5
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DOI: https://doi.org/10.1007/978-3-319-75238-9_5
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