Classification of Pancreatic Cancer and Normal Tissue in 2D and 3D Optical Coherence Tomography Images Using Convolutional Neural Networks: A Comparative Study
AI-assisted OCT can accurately differentiate PDAC from normal pancreatic tissue ex vivo, supporting its potential as a rapid intraoperative diagnostic adjunct. Further studies are warranted to assess its in vivo performance and utility in evaluating resection margins.
Authors
- Iakovos Amygdalos (ORCID: https://orcid.org/0000-0002-5138-4214)
- Thomas Vogel (ORCID: https://orcid.org/0000-0002-3275-7329)
- K. Jöchle
- Niels König (ORCID: https://orcid.org/0000-0001-9163-8306)
- Sebastian Cammann (ORCID: https://orcid.org/0000-0002-4614-6692)
- Florian W. R. Vondran (ORCID: https://orcid.org/0000-0001-8355-5017)
- Svetlana Warkentin
- Caroline Girmen (ORCID: https://orcid.org/0000-0003-2081-8814)
- Maria Druzenko
- Martin W. von Websky
- Georg Wiltberger
- Bastian Westerheide
- Robert Schmitt
Institutions
- Fraunhofer Institute for Production Technology IPT (DE)
- RWTH Aachen University (DE)
Publication Details
- Journal
- Cancers
- Published
- 2026-02-25
- DOI
- https://doi.org/10.3390/cancers18050732
- Primary Topic
- Optical Coherence Tomography Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00