Intraoperative assessment of tissue can be guided through fluorescence imaging which involves systemic dosing with a fluorophore and subsequent examination of the tissue region of interest with a near-infrared camera. This typically involves administering indocyanine green (ICG) hours or even days before surgery and intraoperative visualization at the time predicted for steady-state signal-to-background status. Here, we describe our efforts to capture and utilize the information contained in the first few minutes after ICG administration from the perspective of both signal processing and surgical practice. We prove a method for characterization of cancerous versus benign rectal lesions now undergoing further development and validation via multicenter clinical phase studies.
Cite
@article{arxiv.2211.05153,
title = {Extracting, Visualizing, and Learning from Dynamic Data: Perfusion in Surgical Video for Tissue Characterization},
author = {Jonathan P. Epperlein and Niall P. Hardy and Pol Mac Aonghusa and Ronan A. Cahill},
journal= {arXiv preprint arXiv:2211.05153},
year = {2022}
}
Comments
Presented and published at IEEE International Conference on Digital Health (ICDH) 2022