Quantitative parameters based on the time-fluorescence of indocyanine green angiography. This graph could be displayed by measuring changes in the fluorescence intensity (FI), allowing evaluation of various quantitative parameters. In the measurement of FI, the basic quantitative factors are the maximal level of FI (F_max) and the interval to FI_max (T_max). Time scales include latency time (the initial fluorescence onset time), the interval to half of FI_max (T_1/2max), and perfusion time ratio (TR). The ascending slope can reflect arterial flow conditions and can be calculated considering both FI and time scale. Adapted from Ahn et al. [9], according to the Creative Commons License.|@|~(^,^)~|@|Colonic perfusion images. (A) White light image, (B) indocyanine green (ICG) fluorescence image, and (C) color map result of artificial intelligence (AI) analysis of ICG pattern. Real-time AI-based quantitative analysis can be used to evaluate the tissue microcirculation and express visually through a color map overlying the surgical field. The visual information can help the surgeons assess the perfusion status during laparoscopic surgery. Adapted from Park et al. [14], according to the Creative Commons License.

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