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Accurate tumour margin detection is a crucial step in tumour resection surgeries as progression-free survival is linked to rates of complete resection. Despite this, post-surgical positive margin rates remain high for a host of cancers. While spectroscopic techniques have shown promise as highly accurate diagnostic systems, they are inherently limited by their point-based application. Current spectroscopic diagnostic implementations fail to adequately capture spatial diagnostic information, resulting in these systems operating as one-dimensional tools suboptimal for tumour margin delineation. Here we demonstrate a computer vision-based technique that captures spatial information, enabling the transformation of spectroscopic systems from one-dimensional tools to clinically-relevant two-dimensional diagnostic platforms. We show that through visual tracking of a spectroscopic probe’s location relative to the tissue, we can display spatially co-registered spectroscopic diagnoses over clinical tumour imaging data to enhance tumour margin visualisation and aid tumour resection. Our visual, marker-based tracking approach enables real-time spectroscopic diagnostics and is designed for rapid application to different spectroscopic probe modalities and geometries with robust performance under different lighting conditions and with patient movement during procedures. We demonstrate the utility of this spatial diagnostic platform using a Raman spectroscopy probe for ex vivo margin delineation, with ongoing in vivo investigations for subcutaneous xenograft tumour models in nude mice. The associated software developed for this system permits clinical-user interaction for diagnostic threshold adjustment and tumour boundary delineation, enabling clinical diagnostic control for complex tumour geometries. Our system captures essential spatial diagnostic information, transforming point-based spectroscopic systems into effective platforms for tumour delineation.
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