Zilverling

P.T. Rygiel MSc (Patryk)

Promovendus
EEMCS-AM-MIA
Zilverling 2110
p.t.rygiel@utwente.nl
+31534891422
Visitekaartje

Expertises

  • Computer Science

    • Geometric Deep Learning
    • Implicit Neural Representation
    • Computer Assisted Tomography
    • Deep Learning Model
    • Monitoring Strategy
    • Transformer Model
    • Validation Set
    • Vessel Segmentation

Organisaties

Publicaties

2026

GReAT: Leveraging Geometric Artery Data to Improve Wall Shear Stress Assessment (2026)In Shape in Medical Imaging: International Workshop, ShapeMI 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 23, 2025, Proceedings (pp. 277-291) (Lecture Notes in Computer Science; Vol. 16171). Springer. Suk, J., Wentzel, J. J., Rygiel, P., Daemen, J., Rueckert, D. & Wolterink, J. M.https://doi.org/10.1007/978-3-032-06774-6_21Symmetry in the Wild: The Role of Equivariance in Neural Fluid Surrogates (2026)[Working paper › Preprint]. ArXiv.org. Rygiel, P., Suk, J., Yeung, K. K., Brune, C. & Wolterink, J. M.https://doi.org/10.48550/arXiv.2605.18816Application of Fully Convolutional Neural Networks in the Assessment of Cerebral White Matter Involvement in Primary Sjögren’s Syndrome (2026)Neuroinformatics, 24(1). Article 3. Sobański, M., Gajowczyk, M., Rygiel, P., Sobańska, M., Korbecki, A., Litwinowicz, K., Kacała, A., Korbecka, J., Zdanowicz-Ratajczyk, A., Dziadkowiak, E., Sebastian, M., Wiland, P., Trybek, G., Sebastian, A. & Bladowska, J.https://doi.org/10.1007/s12021-025-09762-1Geometric deep learning for local growth prediction on abdominal aortic aneurysm surfaces (2026)Artificial intelligence in medicine, 172. Article 103323. Alblas, D., Rygiel, P., Suk, J., Kappe, K. O., Hofman, M., Brune, C., Yeung, K. K. & Wolterink, J. M.https://doi.org/10.1016/j.artmed.2025.103323Beyond Pixels: Medical Image Quality Assessment with Implicit Neural Representations (2026)In Machine Learning in Medical Imaging: 16th International Workshop, MLMI 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 23, 2025, Proceedings (pp. 359-368) (Lecture Notes in Computer Science; Vol. 16241). Springer. Özer, C., Rygiel, P., de Wilde, B., Öksüz, I. & Wolterink, J. M.https://doi.org/10.1007/978-3-032-09513-8_35

2025

Deep vectorised operators for pulsatile hemodynamics estimation in coronary arteries from a steady-state prior (2025)Computer methods and programs in biomedicine, 271. Article 108958. Suk, J., Nannini, G., Rygiel, P., Brune, C., Pontone, G., Redaelli, A. & Wolterink, J. M.https://doi.org/10.1016/j.cmpb.2025.108958Learning hemodynamic scalar fields on coronary artery meshes: A benchmark of geometric deep learning models (2025)Computers in biology and medicine, 195. Article 110477. Nannini, G., Suk, J., Rygiel, P., Saitta, S., Mariani, L., Maranga, R., Baggiano, A., Pontone, G., Wolterink, J. M. & Redaelli, A.https://doi.org/10.1016/j.compbiomed.2025.110477Wall Shear Stress Estimation in Abdominal Aortic Aneurysms: Towards Generalisable Neural Surrogate Models (2025)[Working paper › Preprint]. ArXiv.org. Rygiel, P., Suk, J., Brune, C., Yeung, K. K. & Wolterink, J. M.https://doi.org/10.48550/arXiv.2507.22817Geometric deep learning for local growth prediction on abdominal aortic aneurysm surfaces (2025)[Working paper › Preprint]. ArXiv.org. Alblas, D., Rygiel, P., Suk, J., Kappe, K. O., Hofman, M., Brune, C., Yeung, K. K. & Wolterink, J. M.https://doi.org/10.48550/arXiv.2506.08729Neural Fields for Continuous Periodic Motion Estimation in 4D Cardiovascular Imaging (2025)In Statistical Atlases and Computational Models of the Heart. Workshop, CMRxRecon and MBAS Challenge Papers. - 15th International Workshop, STACOM 2024, Held in Conjunction with MICCAI 2024, Revised Selected Papers: 15th International Workshop, STACOM 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Revised Selected Papers (pp. 378-389) (Lecture Notes in Computer Science; Vol. 15448 LNCS). Springer (E-pub ahead of print/First online). Garzia, S., Rygiel, P., Dummer, S., Cademartiri, F., Celi, S. & Wolterink, J. M.https://doi.org/10.1007/978-3-031-87756-8_37

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