Abstract
During surgery, conventional or minimally invasive, a surgeon.s ability to identify biological tissue properties is critical. Near Infrared (NIR) Imaging, a continuous, non-invasive imaging modality, offers a surgeon an augmented perception of the tissue characteristics (oxygenation, edema, etc.) In this paper, we present our NIR imaging setup and cluster analysis for localizing areas of similar NIR light absorbance, which relates directly to the tissue.s Hb, HbO2, and H2O content. Through NIR imaging, a surgeon is equipped with auxiliary information to determine the extent and location of tissue injury.
Cite
CITATION STYLE
Wallace, J., Homayoun Mozaffari, N., Pan, L., & Thakor, N. V. (2001). Fuzzy C-means clustering analysis to monitor tissue perfusion with near infrared imaging. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2208, pp. 1213–1214). Springer Verlag. https://doi.org/10.1007/3-540-45468-3_167
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