ArticleGastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association2020
A deep learning method for delineating early gastric cancer resection margin under chromoendoscopy and white light endoscopy.
Article in Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 2 of them syntheses that pooled it.
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Who cites it
35 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Artificial intelligence in gastric cancer: a systematic review of machine learning and deep learning applications.Abdominal radiology (New York) · 2026Pooled it
- Current status and trends of machine learning applied in clinical research of gastric cancer from 2004 to 2023: global bibliometric and visual analysis.Frontiers in oncology · 2025Pooled it
- Application of Artificial Intelligence in the Endoscopic Diagnosis of Gastric Cancer and Precancerous Lesions.Diagnostics (Basel, Switzerland) · 2026Review
- Computer-Aided Diagnosis Using the Large-Scale Visual Language Models in Screening of Digestive Endoscopy.Journal of imaging informatics in medicine · 2026Article
- The application of pre-trained large visual-language models for preliminary diagnosis of esophageal whitish plaques in large-scale esophageal cancer screening.NPJ precision oncology · 2026Article
- Artificial intelligence-assisted diagnosis of early gastric cancer: present practice and future prospects.Annals of medicine · 2025Review
- Utilizing a Novel Convolutional Neural Network for Diagnosis and Lesion Delineation in Colorectal Cancer Screening.Journal of imaging informatics in medicine · 2025Article
- Non-Curative Endoscopic Submucosal Dissection: Current Concepts, Pitfalls and Future Perspectives.Journal of clinical medicine · 2025Review
- A Review of Application of Deep Learning in Endoscopic Image Processing.Journal of imaging · 2024Review
- Enhanced gastric cancer classification and quantification interpretable framework using digital histopathology images.Scientific reports · 2024Article
- A novel artificial intelligence-based endoscopic ultrasonography diagnostic system for diagnosing the invasion depth of early gastric cancer.Journal of gastroenterology · 2024Article
- Global progress and future prospects of early gastric cancer screening.Journal of Cancer · 2024Review
- Deep Learning and Gastric Cancer: Systematic Review of AI-Assisted Endoscopy.Diagnostics (Basel, Switzerland) · 2023Review
- Computer-aided demarcation of early gastric cancer: a pilot comparative study with endoscopists.Journal of gastroenterology · 2023Article
- The Role of Artificial Intelligence in Gastric Cancer: Surgical and Therapeutic Perspectives: A Comprehensive Review.Journal of gastric cancer · 2023Review
- A quick and reliable image-based AI algorithm for evaluating cellular senescence of gastric organoids.Cancer biology & medicine · 2023Article
- The relationship between the esophageal endoscopic submucosal dissection technical difficulty and its intraoperative process.Esophagus : official journal of the Japan Esophageal Society · 2023Article
- A deep-learning based system using multi-modal data for diagnosing gastric neoplasms in real-time (with video).Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2023Article
- Distinguishing bronchoscopically observed anatomical positions of airway under by convolutional neural network.Therapeutic advances in chronic disease · 2023Article
- Artificial intelligence for diagnosing gastric lesions under white-light endoscopy.Surgical endoscopy · 2022Article
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Authors and funding
15 authors.
Funding
Abstract
backgroundAccurate delineation of cancer margins is critical for endoscopic curative resection. This study aimed to train and validate real-time fully convolutional networks for delineating the resection margin of early gastric cancer (EGC) under indigo carmine chromoendoscopy (CE) or white light endoscopy (WLE), and evaluated its performance and that of magnifying endoscopy with narrow-band imaging (ME-NBI).
methodsWe collected CE and WLE images of EGC lesions to train fully convolutional networks ENDOANGEL. ENDOANGEL was tested both on stationary images and endoscopic submucosal dissection (ESD) videos. The accuracy and reliability of ENDOANGEL and NBI-dependent delineation were further evaluated by a novel endoscopy-pathology point-to-point marking.
resultsENDOANGEL had an accuracy of 85.7% in the CE images and 88.9% in the WLE images under an overlap ratio threshold of 0.60 in comparison with the manual markers labeled by the experts. In the ESD videos, the resection margins predicted by ENDOANGEL covered all areas of high-grade intraepithelial neoplasia and cancers. The minimum distance between the margins predicted by ENDOANGEL and the histological cancer boundary was 3.44 ± 1.45 mm which outperformed the resection margin based on ME-NBI.
conclusionsENDOANGEL has the potential to assist endoscopists in delineating the resection extent of EGC under CE or WLE during ESD.
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