Renji endoscopic submucosal dissection video data set for early gastric cancer
Abstract In recent years, the progress of artificial intelligence has greatly advanced computer-assisted intervention, surgical learning, and postoperative surgical video analysis techniques, greatly improving the skill levels of surgeons and overall outcomes. Deep learning based endoscopic surgery...
Saved in:
| Main Authors: | , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-02-01
|
| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-04573-0 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850067633083252736 |
|---|---|
| author | Jinnan Chen Xiangning Zhang Chunjiang Gu Tang Cao Jinneng Wang Zhao Li Yiming Song Liuyi Yang Zhengjie Zhang Qingwei Zhang Dahong Qian Xiaobo Li |
| author_facet | Jinnan Chen Xiangning Zhang Chunjiang Gu Tang Cao Jinneng Wang Zhao Li Yiming Song Liuyi Yang Zhengjie Zhang Qingwei Zhang Dahong Qian Xiaobo Li |
| author_sort | Jinnan Chen |
| collection | DOAJ |
| description | Abstract In recent years, the progress of artificial intelligence has greatly advanced computer-assisted intervention, surgical learning, and postoperative surgical video analysis techniques, greatly improving the skill levels of surgeons and overall outcomes. Deep learning based endoscopic surgery phase recognition has a very high dependency on large-scale datasets and annotations. This study introduces the Renji endoscopic submucosal dissection (ESD) video dataset for early gastric cancer (EGC), comprising 20 ESD endoscopic videos and 66,656 phase recognition annotations jointly annotated by three endoscopists. To the best of our knowledge, this is the first publicly available ESD dataset for the treatment of EGC, and we believe this work will contribute to the standardization of ESD dataset construction. The dataset and annotations are publicly available in Figshare. |
| format | Article |
| id | doaj-art-45f654327321489b9b43e96ad9141dfd |
| institution | DOAJ |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-45f654327321489b9b43e96ad9141dfd2025-08-20T02:48:16ZengNature PortfolioScientific Data2052-44632025-02-011211610.1038/s41597-025-04573-0Renji endoscopic submucosal dissection video data set for early gastric cancerJinnan Chen0Xiangning Zhang1Chunjiang Gu2Tang Cao3Jinneng Wang4Zhao Li5Yiming Song6Liuyi Yang7Zhengjie Zhang8Qingwei Zhang9Dahong Qian10Xiaobo Li11Division of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive DiseaseSchool of Biomedical Engineering, Shanghai Jiao Tong UniversityDepartment of Gastroenterology, Liangping District Peoples Hospital of ChongqingDepartment of Gastroenterology, The First Branch, The First Affiliated Hospital of Chongqing Medical UniversityDepartment of Gastroenterology, Beibei Hospital of Chongqing Medical University (The Ninth People’s Hospital of Chongqing)Division of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive DiseaseDivision of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive DiseaseDivision of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive DiseaseSchool of Biomedical Engineering, Shanghai Jiao Tong UniversityDivision of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive DiseaseSchool of Biomedical Engineering, Shanghai Jiao Tong UniversityDivision of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive DiseaseAbstract In recent years, the progress of artificial intelligence has greatly advanced computer-assisted intervention, surgical learning, and postoperative surgical video analysis techniques, greatly improving the skill levels of surgeons and overall outcomes. Deep learning based endoscopic surgery phase recognition has a very high dependency on large-scale datasets and annotations. This study introduces the Renji endoscopic submucosal dissection (ESD) video dataset for early gastric cancer (EGC), comprising 20 ESD endoscopic videos and 66,656 phase recognition annotations jointly annotated by three endoscopists. To the best of our knowledge, this is the first publicly available ESD dataset for the treatment of EGC, and we believe this work will contribute to the standardization of ESD dataset construction. The dataset and annotations are publicly available in Figshare.https://doi.org/10.1038/s41597-025-04573-0 |
| spellingShingle | Jinnan Chen Xiangning Zhang Chunjiang Gu Tang Cao Jinneng Wang Zhao Li Yiming Song Liuyi Yang Zhengjie Zhang Qingwei Zhang Dahong Qian Xiaobo Li Renji endoscopic submucosal dissection video data set for early gastric cancer Scientific Data |
| title | Renji endoscopic submucosal dissection video data set for early gastric cancer |
| title_full | Renji endoscopic submucosal dissection video data set for early gastric cancer |
| title_fullStr | Renji endoscopic submucosal dissection video data set for early gastric cancer |
| title_full_unstemmed | Renji endoscopic submucosal dissection video data set for early gastric cancer |
| title_short | Renji endoscopic submucosal dissection video data set for early gastric cancer |
| title_sort | renji endoscopic submucosal dissection video data set for early gastric cancer |
| url | https://doi.org/10.1038/s41597-025-04573-0 |
| work_keys_str_mv | AT jinnanchen renjiendoscopicsubmucosaldissectionvideodatasetforearlygastriccancer AT xiangningzhang renjiendoscopicsubmucosaldissectionvideodatasetforearlygastriccancer AT chunjianggu renjiendoscopicsubmucosaldissectionvideodatasetforearlygastriccancer AT tangcao renjiendoscopicsubmucosaldissectionvideodatasetforearlygastriccancer AT jinnengwang renjiendoscopicsubmucosaldissectionvideodatasetforearlygastriccancer AT zhaoli renjiendoscopicsubmucosaldissectionvideodatasetforearlygastriccancer AT yimingsong renjiendoscopicsubmucosaldissectionvideodatasetforearlygastriccancer AT liuyiyang renjiendoscopicsubmucosaldissectionvideodatasetforearlygastriccancer AT zhengjiezhang renjiendoscopicsubmucosaldissectionvideodatasetforearlygastriccancer AT qingweizhang renjiendoscopicsubmucosaldissectionvideodatasetforearlygastriccancer AT dahongqian renjiendoscopicsubmucosaldissectionvideodatasetforearlygastriccancer AT xiaoboli renjiendoscopicsubmucosaldissectionvideodatasetforearlygastriccancer |