  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.
