Vision-based finger tracking of breast palpation for improving breast self-examination

We propose to build a system using vision-based motion tracking technology to gather quantitative data about the breast palpation process for analysis of breast self-examination (BSE) technique. By tracking the position of the fingers, the system is able to objectively quantify the procedure of the BSE process, thus can improve our knowledge on the effectiveness of this technique so as to optimize the search strategy and assure full coverage for breast cancer detection. By graphically displaying palpation features to the patient as the BSE is conducted, the system will provide an interactive feedback to the patient and create a prototype for a computer-based BSE training system. In this paper, we describe the vision-based finger tracking technique used in the system, which uses color information in feature extraction and can track 3D positions of the fingers in real time. Experimental results confirm the good performance and effectiveness of the technique. Several issues on implementation of the technique are also discussed