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. 2024 May 23;7:138. doi: 10.1038/s41746-024-01134-4

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© The Author(s) 2024

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 1 — Overview of DeepCoro’s algorithmic pipeline and example of outputs from each algorithm of a 76 frames coronary angiography video. In practice, steps 3 through 6 must be performed for all stenosis boxes detected at step 2, but the figure shows an example using frame 36 as a reference frame. White box: Stenosis localisation box. Green background box: DeepCoro’s input representing videos of left or right coronary angiograms. Grey background box: DeepCoro’s intermediary output. Orange background box: DeepCoro’s final output representing a continuous stenosis percentage as well as the underlying coronary artery segment with the stenosis. RCA Right Coronary Artery.