Health AI Central
Peer-Reviewed Publication
Eur Heart J Digit Health2026;7(8):ztag138.October 1, 2026Journal Article

Near real-time multi-class segmentation for intravascular optical coherence tomography using knowledge distillation.

Ruben G A van der Waerden1,2, Rick H J A Volleberg1, Pierandrea Cancian3,4,5, Joske L van der Zande1,2, Thijs J Luttikholt1,2, Xiaojin Gu3,4,5, Leah Heil1,2, Jan-Quinten Mol1, Kensuke Nishimiya6, Tomasz Roleder7, Clara I Sánchez3,4, Bram van Ginneken2, Jos Thannhauser1,2, Niels van Royen1, Ivana Išgum3,4,8,9, Simone Saitta3,4,5
1Department of Cardiology, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, the Netherlands.
2Diagnostic Image Analysis Group, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, the Netherlands.
3Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, Amsterdam, the Netherlands.
4Informatics Institute, University of Amsterdam, Amsterdam, the Netherlands.
5Amsterdam Cardiovascular Sciences, Amsterdam UMC, Amsterdam, the Netherlands.
6Department of Cardiovascular Medicine, Tohoku University Graduate School of Medicine, Sendai, Japan.
7Faculty of Medicine, Wrocław University of Science and Technology, Wrocław, Poland.
8Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center University of Amsterdam, Amsterdam, the Netherlands.
9Department of Radiology, Mayo Clinic, Rochester, MN, USA.
PubMed PMC DOI PDF

Abstract

AIMS: Intravascular optical coherence tomography (OCT) enables high-resolution imaging of the coronary vessel wall, but manual image interpretation is time-consuming and existing automated approaches often require high computational resources and exhibit slow inference times, limiting clinical use. We developed OCT-AID-lite, a neural network for near-real-time multi-class OCT segmentation leveragi…

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