Point Projection Mapping System for Tracking, Registering, Labeling, and Validating Optical Tissue Measurements

Area of Science:

• Biomedical optics
• Surgical oncology
• Computational pathology

Background:

• Accurate validation of optical tissue-sensing techniques is crucial for reliable tumor detection in cancer surgery.
• Histological correlation is essential for precise data labeling in machine learning models for tissue classification.

Purpose of the Study:

• To introduce a novel Point Projection Mapping system for non-destructive tracking of optical measurements on tissue specimens.
• To propose and validate a framework for accurate registration and labeling with histopathology results.
• To enhance the accuracy and robustness of validating optical tissue-sensing techniques.

Main Methods:

• Development of a Point Projection Mapping system for precise spatial tracking of optical measurements.
• Implementation of a registration and validation framework linking optical data to histopathology.
• Case study validation of the proposed framework on tissue specimens.

Main Results:

• Demonstrated non-destructive tracking of measurement locations on tissue specimens.
• Validated a framework for accurate registration and labeling with histopathology.
• Showcased a more robust and accurate method for tracking and validation compared to conventional techniques.

Conclusions:

• The Point Projection Mapping system and associated framework offer a significant improvement for validating optical tissue-sensing techniques.
• This approach facilitates more reliable data labeling for machine learning in cancer diagnostics.
• The method contributes to saving time and resources in surgical oncology research and practice.