Guttikonda, SureshSureshGuttikondaNeidhardt, MaximilianMaximilianNeidhardtSprenger, JohannaJohannaSprengerPetersen, JohannesJohannesPetersenDetter, ChristianChristianDetterSchlaefer, AlexanderAlexanderSchlaefer2026-01-232026-01-232025-12-01Current Directions in Biomedical Engineering 11 (2): 57-60 (2025)https://hdl.handle.net/11420/61071Intraoperative fluorescent cardiac imaging enables quality control following coronary bypass grafting surgery.We can estimate local quantitative indicators, such as cardiac perfusion, by tracking local feature points. However, heart motion and significant fluctuations in image characteristics caused by vessel structural enrichment limit traditional tracking methods. We propose a particle filtering tracker based on cyclicconsistency checks to robustly track particles sampled to follow target landmarks. Our method tracks 117 targets simultaneously at 25.4 fps, allowing real-time estimates during interventions. It achieves a tracking error of (5.00 ± 0.22 px) and outperforms other deep learning trackers (22.3 ± 1.1 px) and conventional trackers (58.1 ± 27.1 px).en2364-5504Current directions in biomedical engineering20252Walter de Gruyter GmbHhttps://creativecommons.org/licenses/by/4.0/Technology::616: Diseases::616.0: Pathology, Deseaeses, Treatment::616.07: PathologyTechnology::617: Surgery, Regional Medicine, Dentistry, Ophthalmology, Otology, Audiology::617.9: Operative Surgery and Special Fields of SurgeryTechnology::621: Applied Physics::621.3: Electrical Engineering, Electronic EngineeringRobust tracking with particle filtering for fluorescent cardiac imagingJournal Articlehttps://doi.org/10.15480/882.1656510.1515/cdbme-2025-031510.15480/882.1656510.15480/882.16476Journal Article