1 research outputs found
Estimation of Tissue Oxygen Saturation from RGB Images based on Pixel-level Image Translation
Intra-operative measurement of tissue oxygen saturation (StO2) has been
widely explored by pulse oximetry or hyperspectral imaging (HSI) to assess the
function and viability of tissue. In this paper we propose a pixel- level
image-to-image translation approach based on conditional Generative Adversarial
Networks (cGAN) to estimate tissue oxygen saturation (StO2) directly from RGB
images. The real-time performance and non-reliance on additional hardware,
enable a seamless integration of the proposed method into surgical and
diagnostic workflows with standard endoscope systems. For validation, RGB
images and StO2 ground truth were simulated and estimated from HSI images
collected by a liquid crystal tuneable filter (LCTF) endoscope for three tissue
types (porcine bowel, lamb uterus and rabbit uterus). The result show that the
proposed method can achieve visually identical images with comparable accuracy