Enhancing detection of various pancreatic lesions on endoscopic ultrasound through artificial intelligence: a basis for computer‐aided detection systems
We developed and tested deep learning models for real-time detection and segmentation of pancreatic lesions during EUS with promising results. This constitutes the basis for a CADe system for EUS, which could be valuable in future detection and evaluation of pancreatic lesions. Further studies for validation and generalization are underway.
Authors
- Iris Dotan (ORCID: https://orcid.org/0000-0002-8005-7706)
- Orr Green
- Ariel A. Benson (ORCID: https://orcid.org/0000-0002-3138-8568)
- Zohar Levi (ORCID: https://orcid.org/0000-0003-2456-8891)
- Tom Konikoff (ORCID: https://orcid.org/0000-0003-4915-111X)
- Rachel Gingold‐Belfer (ORCID: https://orcid.org/0000-0002-2831-4402)
- Leor Perl (ORCID: https://orcid.org/0000-0002-0625-7937)
- Hunter Sandler
- Nadav Loebl
- Steven Shamah
Institutions
- Tel Aviv University (IL)
- Hebrew University of Jerusalem (IL)
- Hadassah Medical Center (IL)
- Rabin Medical Center (IL)
Publication Details
- Journal
- Journal of Gastroenterology and Hepatology
- Published
- 2024-11-13
- DOI
- https://doi.org/10.1111/jgh.16814
- Citations
- 10
- Primary Topic
- Pancreatic and Hepatic Oncology Research
- Type
- article
- Field-Weighted Citation Impact
- 2.83
Funders
- Ministry of Science, Technology and Space
- Israel Cancer Association