Development of a robust and fast calibration procedure for diffuse optical tomography

Near infrared (NIR) diffuse optical tomography has demonstrated great potential in the initial diagnosis of tumor and the assessment of tumor vasculature response to neoadjuvant chemotherapy. A fast and robust data processing is critical to move this technique from lab research to bench-side application. Our lab developed frequency-domain diffuse optical tomography system for clinical applications. So far, we still collect data at hospital and do the data processing off-line. In this paper, a robust calibration procedure and fast processing program were developed to overcome this limitation. Because each detection channel had its own electronic delay, the calibration procedure measured amplitude linearity and phase linearity of each channel, and formed a look-up table. The experimental measurements were corrected by the table and the fitting accuracy improved by 45.8%. To further improve the processing speed, the data collection and processing program were converted to C++ from matlab program. The overall processing speed was improved by two times. We expect the new processing program can move diffuse optical tomography one step close to bench-side clinical applications.