Rapid Quantification of Tissue Perfusion Properties with a Two-Stage Look-Up Table

Tissue perfusion properties reveal crucial information pertinent to clinical diagnosis and treatment. Multispectral spatial frequency domain imaging (SFDI) is an emerging imaging technique that has been widely used to quantify tissue perfusion properties. However, slow processing speed limits its usefulness in real-time imaging applications. In this study, we present a two-stage look-up table (LUT) approach that accurately and rapidly quantifies optical (absorption and reduced scattering maps) and perfusion (total hemoglobin and oxygen saturation maps) properties using stage-1 and stage-2 LUTs, respectively, based on reflectance images at 660 and 850 nm. The two-stage LUT can be implemented on both CPU and GPU computing platforms. Quantifying tissue perfusion properties using the simulated diffuse reflectance images, we achieved a quantification speed of 266, 174, and 74 frames per second for three image sizes 512 × 512, 1024 × 1024, and 2048 × 2048 pixels, respectively. Quantification of tissue perfusion properties was highly accurate with only 3.5% and 2.5% error for total hemoglobin and oxygen saturation quantification, respectively. The two-stage LUT has the potential to be integrated with dual-sensor cameras to enable real-time quantification of tissue hemodynamics.