Deep Learning in Endoscopic Ultrasound: A Breakthrough in Detecting Distal Cholangiocarcinoma
This study demonstrates the significant potential of AI in EUS imaging for dCCA, presenting a robust tool that enhances diagnostic accuracy and efficiency. The developed MATLAB application serves as a valuable aid for medical professionals, facilitating informed decision-making and improving patient outcomes in the diagnosis of cholangiocarcinoma and related pathologies.
Authors
- Eva H. Dulf (ORCID: https://orcid.org/0000-0002-6540-6525)
- Cristina Pojoga (ORCID: https://orcid.org/0000-0001-9881-4114)
- Rares Ilie Orzan (ORCID: https://orcid.org/0000-0002-8638-496X)
- Renata Agoston
- Andrada Seicean (ORCID: https://orcid.org/0000-0002-5809-1334)
- Noémi Lorenzovici (ORCID: https://orcid.org/0009-0006-2682-4376)
- D. Della Santa
- Thomas-Andrei Zareczky
Institutions
- Technical University of Cluj-Napoca (RO)
- Iuliu Hațieganu University of Medicine and Pharmacy (RO)
- Babeș-Bolyai University (RO)
Publication Details
- Journal
- Cancers
- Published
- 2024-11-11
- DOI
- https://doi.org/10.3390/cancers16223792
- Citations
- 3
- Primary Topic
- Cholangiocarcinoma and Gallbladder Cancer Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.72