Sahli F., Pezzuto S., Perdikaris P. (2024)

?-PINNs: Physics-informed neural networks on complex geometries

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 127

Solomons D., Rodriguez M., Mery-Munoz F., Arrano-Carrasco L., Sahli F., Mendez-Orellana C. (2024)

Assessing Language Lateralization through Gray Matter Volume: Implications for Preoperative Planning in Brain Tumor Surgery

Brain Sciences 14 10

Tac V., Rausch M., Bilionis I., Sahli F., Tepole A. (2024)

Generative hyperelasticity with physics-informed probabilistic diffusion fields

ENGINEERING WITH COMPUTERS

Barahona J., Sahli F., Hurtado D. (2024)

Machine learning modeling of lung mechanics: Assessing the variability and propagation of uncertainty in respiratory-system compliance and airway resistance

Computer Methods and Programs in Biomedicine 243

Garay J., Dunstan J., Uribe S., Sahli F. (2024)

Physics-informed neural networks for parameter estimation in blood flow models

Computers in Biology and Medicine 178

Spieker, V. et al. (2024). Self-supervised k-Space Regularization for Motion-Resolved Abdominal MRI Using Neural Implicit k-Space Representations. In: Linguraru, M.G., et al. Medical Image Computing and Computer Assisted Intervention – MICCAI 2024. MICCAI 2024. Lecture Notes in Computer Science, vol 15007. Springer, Cham. https://doi.org/10.1007/978-3-031-72104-5_59 (2024)

Self-supervised k-Space Regularization for Motion-Resolved Abdominal MRI Using Neural Implicit k-Space Representations

Medical Image Computing and Computer Assisted Intervention – MICCAI 2024. MICCAI 2024. Lecture Notes

Spieker V., Eichhorn H., Stelter J., Huang W., Braren R., Rueckert D., Sahli F., Hammernik K., Prieto C., Karampinos D., Schnabel J (2024)

Self-supervised k-Space Regularization for Motion-Resolved Abdominal MRI Using Neural Implicit k-Space Representations

Medical Image Computing and Computer Assisted Intervention – MICCAI 2024. MICCAI 2024

Tac V., Linka K., Kuhl E., Tepole A., Sahli F. (2023)

Benchmarking physics-informed frameworks for data-driven hyperelasticity

COMPUTATIONAL MECHANICS

Tac V., Rausch M., Tepole A., Sahli F. (2023)

Data-driven anisotropic finite viscoelasticity using neural ordinary differential equations

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 411

Lopez P., Mella H., Uribe S., Hurtado D., Costabal F., Lopez P., Mella H., Uribe S., Lopez P., Mella H., Uribe S., Lopez P., Mella H., Uribe S. (2023)

WarpPINN: Cine-MR image registration with physics-informed neural networks

MEDICAL IMAGE ANALYSIS 89

(2022)

Dassault Systèmes’ Living Heart Project

Tac V., Sahli F., Tepole A. (2022)

Data-driven tissue mechanics with polyconvex neural ordinary differential equations

Computer Methods in Applied Mechanics and Engineering 398 115248

Gander L., Pezzuto S., Gharaviri A., Krause R., Perdikaris P., Sahli F., (2022)

Fast characterization of inducible regions of atrial fibrillation models with multi-fidelity Gaussian process classification

Frontiers in Physiology

Peirlinck M., Yao J., Sahli F., Kuhl E., (2022)

How drugs modulate the performance of the human heart.

Computational Mechanics 69 1397-1411

Ziya Tikenogullari O., Sahli F., Yao J., Marsden A., Kuhl E. (2022)

How viscous is the beating heart? Insights from a computational study

Computational Mechanics 70 565-579

Ruiz-Herrera C., Grandits T., Plank G., Perdikaris P., Sahli F., Pezzuto S. (2022)

Physics?informed neural networks to learn cardiac fiber orientation from multiple electroanatomical maps

Engineering with Computers

Mohamed B., Sahli F., Wang H., Linka K., Peirlinck M., Kuhl E., Perdikaris P. (2021)

COVID-19 dynamics across the US: A deep learning study of human mobility and social behavior

Computer Methods in Applied Mechanics and Engineering

Grandits, Thomas, Simone Pezzuto, Francisco Sahli Costabal, Paris Perdikaris, Thomas Pock, Gernot Plank, Rolf Krause. "Learning atrial fiber orientationsconductivity tensors from intracardiac maps using physics-informed neural networks." In International Conference on Functional Imaging and Modeling of the Heart, pp. 650-658. Springer, Cham, 2021. (2021)

Learning atrial fiber orientations and conductivity tensors from intracardiac maps using physics-informed neural networks

International Conference on Functional Imaging and Modeling of the Heart

Peirlinck M., Sahli F., Yao J., Guccione J.M., Tripathy S., Wang Y., Ozturk D., Segars P., Morrison T.M., Levine S., Kuhl E. (2021)

Precision medicine in human heart modeling

Biomechanics and Modeling in Mechanobiology

Peirlinck M., Sahli F., Kuhl E. (2021)

Sex differences in drug-induced arrhythmogenesis

Frontiers in Physiology

Peirlinck M., Linka, Francisco Sahli Costabal, Ellen Kuhl. "Outbreak dynamics of COVID-19 in Chinathe United States." Biomechanics and modeling in mechanobiology (2020): 1. (2020)

Outbreak dynamics of COVID-19 in China and the United States

Biomechanics and Modeling in Mechanobiology

Linka K., Peirlinck M., Sahli Costabal F., Kuhl E. (2020)

Outbreak dynamics of COVID-19 in Europe and the effect of travel restrictions

Computer Methods in Biomechanics and Biomedical Engineering 23 11 710-717

Sahli F., Yang Y., Perdikaris P., Hurtado D.E., Kuhl E. (2020)

Physics-Informed Neural Networks for Cardiac Activation Mapping

Frontiers in Physics 8 42

Peirlinck M., Linka K., Sahli Costabal F., Bhattacharya J., Bendavid E., Ioannidis J.P.A., Kuhl E. (2020)

Visualizing the invisible: The effect of asymptomatic transmission on the outbreak dynamics of COVID-19

Computer Methods in Applied Mechanics and Engineering 372 113410