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.
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© 2001 Springer-Verlag Berlin Heidelberg
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Wallace, J., Homayoun, M.N., Pan, L., Thakor, N.V. (2001). Fuzzy C-means Clustering Analysis to Monitor Tissue Perfusion with Near Infrared Imaging. In: Niessen, W.J., Viergever, M.A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2001. MICCAI 2001. Lecture Notes in Computer Science, vol 2208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45468-3_167
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DOI: https://doi.org/10.1007/3-540-45468-3_167
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