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A point-of-care handheld region-of-interest (ROI) 3D functional diffuse optical tomography (fDOT) system

Functional Diffuse Optical Tomography (fDOT) has the potential to provide the functional status of tissue by mapping 3D distribution of chromophores concentration in deep tissue non-inversely. Region-of-Interest (ROI) DOT, we presented earlier, uses optical patch using only a few NIR light sources and detectors arranged in a circular pattern for the depth-sensitive 3D DOT imaging of the tissue at a high-speed. However, ROI DOT system is not portable enough to carry with and to operate in an unconstrained setting. In this work, we have developed a handheld ROI fDOT system that allows functional imaging of tissue wirelessly. We have proposed a new embedded system architecture based on the Internet-of-things (IoT) concept. Our low-level embedded system and analog circuit design, and embedded computing algorithm also capable of source modulation, lock-in detection, onboard calibration and basic signal processing for the continuous wave (cw) DOT measurement at a high speed while reducing the overall form factor of the system. The optical probe has two sets of source and detector, each contains four triple-wavelengths NIR LEDs and four silicon-photodiode detectors arranged at two different source-detector separations. The handheld system sends measured data to a server wirelessly in real-time. The server performs high-speed GPU-based ROI 3D fDOT image reconstruction and displays result at 3 frames-per-second. The image reconstruction algorithm solves the diffusion equation using the finite element method and utilizes two depth sensitive measurement sets. The experimental results of regional tissue imaging on eight participants have proven the working of the system.