This research aims to deal with intraoperative multispectral images taken from brain tumour surgeries to investigate the diagnostic and guidance potential of MSI. These images were registered by feature-based (SIFT, PFN), intensity-based (LK) and machine learning (RANSAC-Flow) methods and classified via a CNN and Transformer model using anatomical labels. Based on the results from some initial training, MSI could achieve 95% overall accuracy. After labelling and registration are completed, a brain surgery dataset can be built to support intraoperative decision making.
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Hu et al. (2024) studied this question.
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