Point Projection Mapping System for Tracking, Registering, Labeling and Validating Optical Tissue Measurements
This addresses the need for accurate validation and labeling in optical tissue sensing for cancer surgery, though it appears incremental as an improved method for an existing bottleneck.
The paper tackles the problem of validating optical tissue sensing techniques for tumor detection by introducing a Point Projection Mapping system that non-destructively tracks measurement locations on tissue specimens, along with a framework for registration and labeling with histopathology results, showing it saves time and resources compared to conventional methods.
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.