研究期間：10108~10207;Based on the previous six-year study on near infrared diffuse optic tomography (NIR DOT), this study aims at developing and validating a DOT module incorporated with X-ray mammography to improve both the sensitivity and specificity for breast tumor screening and diagnosis through functional images of DOT. In the study, the NIR dual-direction projection scanning module will be remodeled to consider (i) the acquisition of reflective power emitted from tissue, and (ii) ‘one-stop’ data acquisition for both the mammogram and the DOT. This can improve the artifacts near the upper and lower surfaces in the DOT images, and further expedite the data acquisition procedure for both the mammogram and the DOT within one-stop shot. X-ray mammography has been used to detect breast tumors for decades. There still exists high percentage of faulty diagnosis due to the limitation of structural information. NIR DOT, a functional imaging modality, has been investigated and developed for twenty years. This study aims at developing a dual-modality imaging technique by incorporating the NIR DOT with the X-ray mammography. The structural images of mammogram are used as an initial guess of NIR DOT computation so that the tumor detection can achieve fast convergence and better performance for differentiate tumors from normal tissues. The research proceeds to the development of dual-modality tumor-detection technique based on previous basis, such as direct-current and frequency-domain measurement system, inverse computation scheme for optical-property images, and algorithms for the purpose of rapid convergence, edge-preserving for better tumor detection. The study is first to remodel the NIR-DOT measuring module incorporating with the press plates of X-ray mammography. The module is used to acquire NIR data translating through tissues. While tumor detection is under process, X-ray mammograms and NIR data acquisition are taken in sequence. Then, optical-property (absorption and scattering) images, functional images, can be inversely computed using the detected NIR data and the structural information of mammograms. In the study, the effectiveness of dual-modality diagnosis technique will be justified through clinic trials. To enhance the breast tumor detection in sensitivity and specificity is expected
