Xiaomei Chi
ABSTRACT
Assessment of the perfusion state for capillaries provides important guidances in diagnosis and treatment of critically ill patients. A high-quality capture of video and image, convenient and effective analysis of vessels are the foundation of microcirculation assessment in clinical application. Here, we experimentally develop a sublingual microcirculation monitoring and imaging system that uses a front-end probe parallel to the bottom of tongue to control the force on sublingual tissues, and propose a U-Net based segmentation approach for extracting the vascular structures. Human sublingual microcirculation videos are acquired from both sidestream dark field and self-built imaging system to train and test the algorithm. The model locates most of blood vessels accurately and the area under receiver operating characteristic curve measure of the model achieves 0.95, which demonstrates an excellent performance and robustness of our algorithm.
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