Skip to content
DraconiticResearch
Search Sources API
203,203 studies31 sourcesUpdated 4 min ago
Peer-reviewedCC BY-NC-ND 4.0Scientific Data

Curated endoscopic retrograde cholangiopancreatography images dataset

  • Alda João Andrade1
  • Mónica Martins2
  • André Ferreira2,3
  • Tarcísio Araújo1
  • Luís Lopes1,4,5
  • Victor Alves2
5 affiliations
  1. 1Department of Gastroenterology, Hospital Santa Luzia, ULS Alto Minho, Viana do Castelo, Portugal
  2. 2Center Algoritmi / LASI, University of Minho, Braga, Portugal
  3. 3Institute for Artificial Intelligence in Medicine (IKIM), Essen University Hospital (AöR), University of Duisburg-Essen, Essen, Germany
  4. 4Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
  5. 5ICVS/3B’s - PT Government Associate Laboratory, Braga/Guimarães, Portugal
Read full textPDFDOICite

Abstract

Endoscopic Retrograde Cholangiopancreatography (ERCP) is a key procedure in the diagnosis and treatment of biliary and pancreatic diseases. Artificial intelligence has been pointed as one solution to automatize diagnosis. However, public ERCP datasets are scarce, which limits the use of such approach. To help address these limitations, this study aims to help fill this gap by providing a large and curated dataset. The collection is composed of 19.018 raw images and 19.317 processed sections from 1.602 patients. 5.519 images are labeled, which provides a ready-to-use dataset. All images were manually inspected and annotated by two gastroenterologists with more than 5 years of experience and reviewed by another gastroenterologist with more than 20 years of experience, all with more than 400 ERCP procedures annually. The utility and validity of the dataset is proven by a classification experiment. This collection aims to provide or contribute for a benchmark in automatic ERCP analysis and diagnosis of biliary and pancreatic diseases.

Related

  1. Breaking the compatibility barrier: cholangioscopy-guided laser lithotripsy during enteroscopy-assisted endoscopic retrograde cholangiopancreatography in Roux-en-Y anatomy.
    Alda Andrade, Ana Rita Ribeiro, Jorge Bezerra +4
    EndoscopyPeer-reviewedCC BYFull textGeneral medicineEurope PMC
  2. Safety and Recovery Profile of Propofol-Based Intravenous Sedation for Endoscopic Retrograde Cholangiopancreatography in Adults: A Prospective Single-Center Observational Study
    Muhammad Ahmad Khan, Tariq Mahmood, Mirza Ahmad Raza Baig +2
    CureusPeer-reviewedCC BYFull textGeneral medicineEurope PMC
  3. Cerebral Air Embolism Following Endoscopic Retrograde Cholangiopancreatography Stent Removal: A Rare and Fatal Complication.
    Bavani Senthuran, A Arulmurali, Anuratha Kajendran +2
    Case reports in anesthesiologyPeer-reviewedCC BYFull textGeneral medicineEurope PMC
  4. A Curated Dataset for Question Answering on Laboratory Test Reference Ranges and Interpretation
    Balu Bhasuran, Qiao Jin, Angelique Deville +4
    Scientific DataPeer-reviewedCC BY-NC-ND 4.0Full textEpidemiology & public healthPMC
  5. Development and validation of a deep learning model for differentiating cytomegalovirus and herpes simplex virus esophagitis using endoscopic images
    Ji Eun Kim, Yeong Chan Lee, Young Eun Oh +6
    Scientific ReportsPeer-reviewedCC BY-NC-ND 4.0Full textEpidemiology & public healthCrossref

Cite

BibTeXRIS
BibTeX
@article{andrade2026curated,
  title = {{Curated endoscopic retrograde cholangiopancreatography images dataset}},
  author = {Alda João Andrade and Mónica Martins and André Ferreira and Tarcísio Araújo and Luís Lopes and Victor Alves},
  journal = {Scientific Data},
  year = {2026},
  month = jul,
  doi = {10.1038/s41597-026-07679-1},
  url = {https://doi.org/10.1038/s41597-026-07679-1},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - Curated endoscopic retrograde cholangiopancreatography images dataset
AU  - Alda João Andrade
AU  - Mónica Martins
AU  - André Ferreira
AU  - Tarcísio Araújo
AU  - Luís Lopes
AU  - Victor Alves
PY  - 2026
DA  - 2026/07/04
JO  - Scientific Data
DO  - 10.1038/s41597-026-07679-1
UR  - https://doi.org/10.1038/s41597-026-07679-1
AB  - Endoscopic Retrograde Cholangiopancreatography (ERCP) is a key procedure in the diagnosis and treatment of biliary and pancreatic diseases. Artificial intelligence has been pointed as one solution to automatize diagnosis. However, public ERCP datasets are scarce, which limits the use of such approach. To help address these limitations, this study aims to help fill this gap by providing a large and curated dataset. The collection is composed of 19.018 raw images and 19.317 processed sections from 1.602 patients. 5.519 images are labeled, which provides a ready-to-use dataset. All images were manually inspected and annotated by two gastroenterologists with more than 5 years of experience and reviewed by another gastroenterologist with more than 20 years of experience, all with more than 400 ERCP procedures annually. The utility and validity of the dataset is proven by a classification experiment. This collection aims to provide or contribute for a benchmark in automatic ERCP analysis and diagnosis of biliary and pancreatic diseases.
SN  - 2052-4463
ER  -