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. 2022 Jan 11;13(1):e00433. doi: 10.14309/ctg.0000000000000433

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© 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of The American College of Gastroenterology

This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

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Figure 3. — Comparing the delineation performance of the model with that of endoscopists. (a) A case of cancer in the esophagus with white light imaging. (b) Margins of the same lesion under WLI were manually delineated (white polygonal frames, used as the gold standard) by an expert who took the margins of the lesions under NBI, iodine staining, and resection specimen as reference. (c) The AI model correctly detected the lesion by indicating it with a square frame and a polygonal frame (dark cyan). (d) Margins of the same lesion under WLI were delineated AI model (a dark cyan polygonal frame) and the gold standard (white polygonal frames). (e) Margins of the same lesion under WLI were delineated by a senior endoscopist (a blue polygonal frame) and the gold standard (white polygonal frames). (f) Margins of the same lesion under WLI were delineated by an expert endoscopist (a red polygonal frame) and the gold standard (white polygonal frames). AI, artificial intelligence; NBI, narrow-band imaging; WLI, white light imaging.