Patryk Rygiel

According to our database, Patryk Rygiel authored at least 18 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Symmetry in the Wild: The Role of Equivariance in Neural Fluid Surrogates.

Patryk Rygiel, Julian Suk, Kak Khee Yeung, Christoph Brune, Jelmer M. Wolterink

CoRR, May, 2026

Application of Fully Convolutional Neural Networks in the Assessment of Cerebral White Matter Involvement in Primary Sjögren's Syndrome.

Michal Sobanski, Milosz Gajowczyk, Patryk Rygiel, Martyna Sobanska, Adrian Korbecki, Kamil Litwinowicz, Arkadiusz Kacala, Justyna Korbecka, Agata Zdanowicz-Ratajczyk, Edyta Dziadkowiak, Maciej Sebastian, Piotr Wiland, Grzegorz Trybek, Agata Sebastian, Joanna Bladowska

Neuroinformatics, March, 2026

Geometric deep learning for local growth prediction on abdominal aortic aneurysm surfaces.

Dieuwertje Alblas, Patryk Rygiel, Julian Suk, Kaj O. Kappe, Marieke Hofman, Christoph Brune, Kak Khee Yeung, Jelmer M. Wolterink

Artif. Intell. Medicine, 2026

2025

Wall Shear Stress Estimation in Abdominal Aortic Aneurysms: Towards Generalisable Neural Surrogate Models.

Patryk Rygiel, Julian Suk, Christoph Brune, Kak Khee Yeung, Jelmer M. Wolterink

CoRR, July, 2025

Learning Hemodynamic Scalar Fields on Coronary Artery Meshes: A Benchmark of Geometric Deep Learning Models.

Guido Nannini, Julian Suk, Patryk Rygiel, Simone Saitta, Luca Mariani, Riccardo Maragna, Andrea Baggiano, Gianluca Pontone, Jelmer M. Wolterink, Alberto Redaelli

CoRR, January, 2025

TopoBench: A Framework for Benchmarking Topological Deep Learning.

Lev Telyatnikov, Guillermo Bernárdez, Marco Montagna, Mustafa Hajij, Martin Carrasco, Pavlo Vasylenko, Mathilde Papillon, Ghada Zamzmi, Michael T. Schaub, Jonas Verhellen, Pavel Snopov, Bertran Miquel-Oliver, Manel Gil-Sorribes, Alexis Molina, Victor Guallar, Theodore Long, Julian Suk, Patryk Rygiel, Alexander V. Nikitin, Giordan Escalona, Michael Banf, Dominik Filipiak, Liliya Imasheva, Max Schattauer, Alvaro L. Martinez, Halley Fritze, Marissa Masden, Valentina Sánchez, Manuel Lecha, Andrea Cavallo, Claudio Battiloro, Matthew Piekenbrock, Mauricio Tec, George Dasoulas, Nina Miolane, Simone Scardapane, Theodore Papamarkou

J. Data-centric Mach. Learn. Res., 2025

Deep vectorised operators for pulsatile hemodynamics estimation in coronary arteries from a steady-state prior.

Julian Suk, Guido Nannini, Patryk Rygiel, Christoph Brune, Gianluca Pontone, Alberto Redaelli, Jelmer M. Wolterink

Comput. Methods Programs Biomed., 2025

Learning hemodynamic scalar fields on coronary artery meshes: A benchmark of geometric deep learning models.

Guido Nannini, Julian Suk, Patryk Rygiel, Simone Saitta, Luca Mariani, Riccardo Maranga, Andrea Baggiano, Gianluca Pontone, Jelmer M. Wolterink, Alberto Redaelli

Comput. Biol. Medicine, 2025

Beyond Pixels: Medical Image Quality Assessment with Implicit Neural Representations.

Caner Özer, Patryk Rygiel, Bram de Wilde, Ilkay Öksüz, Jelmer M. Wolterink

Proceedings of the Machine Learning in Medical Imaging - 16th International Workshop, 2025

GReAT: Leveraging Geometric Artery Data to Improve Wall Shear Stress Assessment.

Julian Suk, Jolanda J. Wentzel, Patryk Rygiel, Joost Daemen, Daniel Rueckert, Jelmer M. Wolterink

Proceedings of the Shape in Medical Imaging, 2025

Active Learning for Deep Learning-Based Hemodynamic Parameter Estimation.

Patryk Rygiel, Julian Suk, Kak Khee Yeung, Christoph Brune, Jelmer M. Wolterink

Proceedings of the Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers, 2025

2024

Estimation of FFR in coronary arteries with deep learning.

Patryk Rygiel

CoRR, 2024

Global Control for Local SO(3)-Equivariant Scale-Invariant Vessel Segmentation.

Patryk Rygiel, Dieuwertje Alblas, Christoph Brune, Kak Khee Yeung, Jelmer M. Wolterink

Proceedings of the Statistical Atlases and Computational Models of the Heart. Workshop, 2024

Neural Fields for Continuous Periodic Motion Estimation in 4D Cardiovascular Imaging.

Simone Garzia, Patryk Rygiel, Sven Dummer, Filippo Cademartiri, Simona Celi, Jelmer M. Wolterink

Proceedings of the Statistical Atlases and Computational Models of the Heart. Workshop, 2024

ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain.

Guillermo Bernárdez, Lev Telyatnikov, Marco Montagna, Federica Baccini, Mathilde Papillon, Miquel Ferriol-Galmés, Mustafa Hajij, Theodore Papamarkou, Maria Sofia Bucarelli, Olga Zaghen, Johan Mathe, Audun Myers, Scott Mahan, Hansen Lillemark, Sharvaree Vadgama, Erik J. Bekkers, Tim Doster, Tegan Emerson, Henry Kvinge, Katrina Agate, Nesreen K. Ahmed, Pengfei Bai, Michael Banf, Claudio Battiloro, Maxim Beketov, Paul Bogdan, Martin Carrasco, Andrea Cavallo, Yun Young Choi, George Dasoulas, Matous Elphick, Giordan Escalona, Dominik Filipiak, Halley Fritze, Thomas Gebhart, Manel Gil-Sorribes, Salvish Goomanee, Victor Guallar, Liliya Imasheva, Andrei Irimia, Hongwei Jin, Graham Johnson, Nikos Kanakaris, Boshko Koloski, Veljko Kovac, Manuel Lecha, Minho Lee, Pierrick Leroy, Theodore Long, German Magai, Alvaro Martinez, Marissa Masden, Sebastian Meznar, Bertran Miquel-Oliver, Alexis Molina, Alexander Nikitin, Marco Nurisso, Matt Piekenbrock, Yu Qin, Patryk Rygiel, Alessandro Salatiello, Max Schattauer, Pavel Snopov, Julian Suk, Valentina Sánchez, Mauricio Tec, Francesco Vaccarino, Jonas Verhellen, Frédéric Wantiez, Alexander Weers, Patrik Zajec, Blaz Skrlj, Nina Miolane

Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM) at ICML 2024, 2024

2023

CenterlinePointNet++: A New Point Cloud Based Architecture for Coronary Artery Pressure Drop and vFFR Estimation.

Patryk Rygiel, Pawel Pluszka, Maciej Zieba, Tomasz K. Konopczynski

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

2022

Coronary Ostia Localization Using Residual U-Net with Heatmap Matching and 3D DSNT.

Milosz Gajowczyk, Patryk Rygiel, Piotr Grodek, Adrian Korbecki, Michal Sobanski, Przemyslaw Podgórski, Tomasz K. Konopczynski

Proceedings of the Machine Learning in Medical Imaging - 13th International Workshop, 2022

Eigenvector Grouping for Point Cloud Vessel Labeling.

Patryk Rygiel, Maciej Zieba, Tomasz K. Konopczynski

Proceedings of the Geometric Deep Learning in Medical Image Analysis, 2022