Image-guided Raman spectroscopy probe-tracking for tumor margin delineation

Journal article

Validation of newly developed optical tissue sensing techniques for tumor detection during cancer surgery requires an accurate correlation with histological results. Additionally, such accurate correlation facilitates precise data labeling for developing high-performance machine-learning tissue classification models. In this paper, a newly developed Point Projection Mapping system will be introduced, which allows non-destructive tracking of the measurement locations on tissue specimens. Additionally, a framework for accurate registration, validation, and labeling with histopathology results is proposed and validated on a case study. The proposed framework provides a more robust and accurate method for tracking and validation of optical tissue sensing techniques, which saves time and resources compared to conventional techniques available

Authors: Horgan, CC; Bergholt, MS; Thin, MZ; Nagelkerke, A; Kennedy, R

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Society of Photo-optical Instrumentation Engineers
• Journal: Journal of Biomedical Optics
• Volume: 26
• Issue: 03
• Pages: 036002-036002
• Publication date: 2021-03-13
• DOI: 10.1117/1.jbo.26.3.036002
• EISSN: 1560-2281
• ISSN: 1083-3668
• Language: English
• Keywords: Fluorescence; Fluorescence-lifetime imaging microscopy; Ex vivo; Optics; Medicine; Computer science; Raman spectroscopy; Biomedical engineering; In vivo; Protoporphyrin IX; Biology; Physics; Nuclear medicine; Materials science; Imaging phantom; Margin (machine learning)