We have developed 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 BSE so as to optimize the search strategy and assure full coverage for breast cancer detection. By visually displaying all the touched position information to the patient as the BSE is being conducted, the system can 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 are shown to confirm the performance and effectiveness of the technique. Several issues on implementation of the technique are also discussed.
['Jianchao Zeng', 'Yue Joseph Wang', 'Matthew T. Freedman', 'Seong K. Mun']
Color-feature-based finger tracking for breast palpation quantification