Computational Photography-Enhanced Fluorescence Imaging for Surgical Application

Fluorescence Imaging is an important tool to visualize blood vessels and tissues in surgical operations. Despite the urgent, global need for this technology, the complex and proprietary optical system design makes commercial systems prohibitively expensive, and has prevented large-scale adoption of this technology, most notably in low-income regions. This work demonstrates a novel application of computational photography principles to the design of medical fluorescence imaging device and its application of visualizing blood vessels and tissues. The optical design utilizes off-shelf components that largely simplifies the optical structure and lowers the overall system complexity. Advanced computational algorithms are developed to enable real-time, high-quality fluorescence imaging capabilities comparable to a commercial system. Preliminary surgical application of this device is demonstrated on animal tissue samples. The device provides a $5-\mathrm{mm}$ penetration depth, shown from visualizing structures beneath varying thickness of tissue on chicken samples. It also demonstrates sub-millimeter resolution from experiments involving pig coronary vessels, thus proving this prototype device’s value in providing important structural information to surgeons. An interdisciplinary work combining elements of optics, computer vision, and medical device engineering, this new type of fluorescence imaging system based on computational photography algorithms simplifies the optical design, reduces costs, and enhances the accessibility of advanced imaging technologies in medical contexts with a high potential for production to benefit patients especially in low-income regions and for non-operatingroom applications.