Deep learning model DeepNeo predicts neointimal tissue characterization using optical coherence tomography
To the best of our knowledge, DeepNeo is the first deep learning algorithm enabling fully automated segmentation and classification of neointimal tissue with performance comparable to human experts. It could standardize vascular healing assessments after PCI, support therapeutic decisions, and improve risk detection for cardiac events.
Authors
- Tobias Lenz (ORCID: https://orcid.org/0000-0003-3041-8486)
- Heribert Schunkert (ORCID: https://orcid.org/0000-0001-6428-3001)
- Hendrik B. Sager (ORCID: https://orcid.org/0000-0002-0197-6553)
- Thorsten Kessler (ORCID: https://orcid.org/0000-0003-3326-1621)
- Adnan Kastrati (ORCID: https://orcid.org/0000-0003-4341-891X)
- Julia A. Schnabel (ORCID: https://orcid.org/0000-0001-6107-3009)
- Tobias Andreas Rheude (ORCID: https://orcid.org/0000-0002-3426-6080)
- Sebastian Kufner (ORCID: https://orcid.org/0000-0002-8091-4552)
- Valentin Koch (ORCID: https://orcid.org/0009-0003-9678-374X)
- Masaru Seguchi (ORCID: https://orcid.org/0000-0002-5875-613X)
- Carsten Marr (ORCID: https://orcid.org/0000-0003-2154-4552)
- Jens Wiebe (ORCID: https://orcid.org/0000-0003-4170-7347)
- Olle Holmberg (ORCID: https://orcid.org/0000-0001-5558-7628)
- Salvatore Cassese (ORCID: https://orcid.org/0000-0002-8668-4313)
- Philipp Nicol
- Erion Xhepa (ORCID: https://orcid.org/0000-0002-0728-2819)
- Felix Voll (ORCID: https://orcid.org/0000-0003-1034-6147)
- Alp Aytekin (ORCID: https://orcid.org/0000-0001-9450-1591)
- Ece Sancar
- Michael Joner
- E. K. Blum
Institutions
- King's College London (GB)
- Center for Environmental Health (US)
- Helmholtz Zentrum München (DE)
- German Centre for Cardiovascular Research (DE)
- Deutsches Herzzentrum München (DE)
- Data:Lab Munich (Germany) (DE)
- Technical University of Munich (DE)
Publication Details
- Journal
- Communications Medicine
- Published
- 2025-04-17
- DOI
- https://doi.org/10.1038/s43856-025-00835-5
- Citations
- 2
- Primary Topic
- Coronary Interventions and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 4.01
Funders
- European Commission
- Deutsche Forschungsgemeinschaft
- Bundesministerium für Bildung und Forschung
- Deutsche Gesellschaft für Kardiologie-Herz und Kreislaufforschung.
- German Network for Bioinformatics Infrastructure