Expertise

  • Computer Science

    • Vessel Segmentation
  • Engineering

    • Models
    • Periodic Motion
  • Medicine and Dentistry

    • Abdominal Aortic Aneurysm
    • Coronary Artery
    • Hemodynamic
    • Steady State
    • Cardiovascular Disease

Organisations

Publications

2024

Deep vectorised operators for pulsatile hemodynamics estimation in coronary arteries from a steady-state prior (2024)[Working paper › Preprint]. ArXiv.org. Suk, J., Nannini, G., Rygiel, P., Brune, C., Pontone, G., Redaelli, A. & Wolterink, J. M.https://doi.org/10.48550/arXiv.2410.11920Neural Fields for Continuous Periodic Motion Estimation in 4D Cardiovascular Imaging (2024)[Working paper › Preprint]. ArXiv.org. Garzia, S., Rygiel, P., Dummer, S., Cademartiri, F., Celi, S. & Wolterink, J. M.https://doi.org/10.48550/arXiv.2407.20728AAA-100: A Curated Dataset of 3D Watertight Abdominal Aortic Aneurysm Models (2024)[Dataset Types › Dataset]. Zenodo. Rygiel, P., Alblas, D., Brune, C., Smorenburg, S., Yeung, K. K. & Wolterink, J. M.https://doi.org/10.5281/zenodo.10932956Global Control for Local SO(3)-Equivariant Scale-Invariant Vessel Segmentation (2024)[Working paper › Preprint]. ArXiv.org. Rygiel, P., Alblas, D., Brune, C., Yeung, K. K. & Wolterink, J. M.https://doi.org/10.48550/arXiv.2403.15314

Other contributions

  • Rygiel, P., Płuszka, P., Zieba, M., Konopczyński, T. (2023). CenterlinePointNet++: A New Point Cloud Based Architecture for Coronary Artery Pressure Drop and vFFR Estimation. In: Greenspan, H., et al. Medical Image Computing and Computer Assisted Intervention – MICCAI 2023. MICCAI 2023. Lecture Notes in Computer Science, vol 14226. Springer, Cham. https://doi.org/10.1007/978-3-031-43990-2_73
  • Rygiel Patryk, Zieba Maciej and Konopczynski Tomasz. “Eigenvector Grouping for Point Cloud Vessel Labeling.” Proceedings of the First International Workshop on Geometric Deep Learning in Medical Image Analysis, edited by Erik Bekkers et al., vol. 194, PMLR, 2022, pp. 72–84, https://proceedings.mlr.press/v194/rygiel22a.html.
  • Gajowczyk Milosz*, Rygiel Patryk*, Grodek Piotr, Korbecki Adrian, Sobanski Michal, Podgorski Przemyslaw and Konopczynski Tomasz. “Coronary Ostia Localization Using Residual U-Net with Heatmap Matching and 3D DSNT.” Machine Learning in Medical Imaging (MLMI 2022) held with MICCAI 2022, edited by Chunfeng Lian et al., Springer Nature Switzerland, 2022, pp. 318–27. (* equal contribution) 

Research profiles

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