Extracting, Visualizing, and Learning from Dynamic Data: Perfusion in Surgical Video for Tissue Characterization

J. Epperlein, N. Hardy, Pól Mac Aonghusa, R. Cahill
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Abstract

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.
从动态数据中提取、可视化和学习:用于组织表征的外科视频灌注
术中组织评估可以通过荧光成像来指导,其中包括用荧光团全身给药,随后用近红外相机检查感兴趣的组织区域。这通常包括在手术前数小时甚至数天给予吲哚菁绿(ICG),并在预测稳态信号-背景状态时进行术中可视化。在这里,我们从信号处理和手术实践的角度描述了我们在ICG给药后最初几分钟内捕获和利用信息的努力。我们证明了一种表征直肠癌变与良性病变的方法,目前正通过多中心临床阶段研究进一步发展和验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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