| Rapid three-dimensional multiparametric MRI with quantitative transient-state imaging PA Gómez, M Cencini, M Golbabaee, RF Schulte, C Pirkl, I Horvath, ... Scientific reports 10 (1), 13769, 2020 | 56 | 2020 |
| Accelerated 3D whole-brain T1, T2, and proton density mapping: feasibility for clinical glioma MR imaging CM Pirkl, L Nunez-Gonzalez, F Kofler, S Endt, L Grundl, M Golbabaee, ... Neuroradiology, 1-21, 2021 | 31 | 2021 |
| Compressive MRI quantification using convex spatiotemporal priors and deep encoder-decoder networks M Golbabaee, G Buonincontri, CM Pirkl, MI Menzel, BH Menze, M Davies, ... Medical Image Analysis 69, 101945, 2021 | 21 | 2021 |
| SRflow: Deep learning based super-resolution of 4D-flow MRI data S Shit, J Zimmermann, I Ezhov, JC Paetzold, AF Sanches, C Pirkl, ... Frontiers in Artificial Intelligence, 171, 2022 | 12 | 2022 |
| Learning residual motion correction for fast and robust 3D multiparametric MRI CM Pirkl, M Cencini, JW Kurzawski, D Waldmannstetter, H Li, ... Medical Image Analysis 77, 102387, 2022 | 9 | 2022 |
| Robust, primitive, and unsupervised quality estimation for segmentation ensembles F Kofler, I Ezhov, L Fidon, CM Pirkl, JC Paetzold, E Burian, S Pati, ... Frontiers in Neuroscience 15, 752780, 2021 | 9 | 2021 |
| Deep MR Fingerprinting with total-variation and low-rank subspace priors M Golbabaee, CM Pirkl, MI Menzel, G Buonincontri, PA Gómez arXiv preprint arXiv:1902.10205, 2019 | 8 | 2019 |
| Deep learning-enabled diffusion tensor MR fingerprinting CM Pirkl, I Lipp, G Buonincontri, M Molina-Romero, A Sekuboyina, ... Proc. 27th Annu. Meet (ISMRM), 1102, 2019 | 8 | 2019 |
| Compressive MRI quantification using convex spatiotemporal priors and deep auto-encoders M Golbabaee, G Buonincontri, C Pirkl, M Menzel, B Menze, M Davies, ... arXiv preprint arXiv:2001.08746, 2020 | 6 | 2020 |
| Region of interest focused MRI to synthetic CT translation using regression and segmentation multi-task network SS Kaushik, M Bylund, C Cozzini, DD Shanbhag, SF Petit, JJ Wyatt, ... Physics in Medicine and Biology, 2023 | 5 | 2023 |
| Region of interest focused mri to synthetic ct translation using regression and classification multi-task network S Kaushik, M Bylund, C Cozzini, D Shanbhag, SF Petit, JJ Wyatt, ... arXiv preprint arXiv:2203.16288, 2022 | 5 | 2022 |
| A Plug-and-Play Approach To Multiparametric Quantitative MRI: Image Reconstruction Using Pre-Trained Deep Denoisers K Fatania, CM Pirkl, MI Menzel, P Hall, M Golbabaee 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), 1-4, 2022 | 5 | 2022 |
| 3D Silent Parameter Mapping: Further refinements & quantitative assessment F Wiesinger, G McKinnon, S Kaushik, AB Solana, E Ljungberg, M Vogel, ... Proceedings of the International Society Magnetic Resonance in Medicine 29, 1828, 2021 | 4 | 2021 |
| Nonlinear Equivariant Imaging: Learning Multi-Parametric Tissue Mapping without Ground Truth for Compressive Quantitative MRI K Fatania, KY Chau, CM Pirkl, MI Menzel, P Hall, M Golbabaee arXiv preprint arXiv:2211.12786, 2022 | 3 | 2022 |
| Unmixing tissue compartments via deep learning T1-T2-relaxation correlation imaging S Endt, CM Pirkl, CM Verdun, BH Menze, MI Menzel 17th International Symposium on Medical Information Processing and Analysis …, 2021 | 3 | 2021 |
| Fast high-resolution Electric Properties Mapping using three-dimensional MR Fingerprinting based water fraction estimation (MRF-EPT) M Cencini, M Lancione, L Biagi, R Pasquariello, L Peretti, CM Pirkl, ... | 3* | |
| In-vivo myelin water quantification using diffusion-relaxation correlation MRI: a comparison of 1D and 2D methods S Endt, M Engel, E Naldi, R Assereto, M Molendowska, L Müller, ... | 2 | 2023 |
| Residual learning for 3D motion corrected quantitative MRI: Robust clinical T1, T2 and proton density mapping C Pirkl, M Cencini, JW Kurzawski, D Waldmannstetter, H Li, A Sekuboyina, ... Medical Imaging with Deep Learning, 2021 | 1 | 2021 |
| Unpaired MR image homogenisation by disentangled representations and its uncertainty H Li, S Gopal, A Sekuboyina, J Zhang, C Niu, C Pirkl, J Kirschke, ... Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and …, 2021 | 1 | 2021 |
| Accelerated 3D multiparametric MRI in glioma patients-Initial clinical experience CM Pirkl, L Nuñez-Gonzalez, PA Gómez, S Endt, RF Schulte, ... Int Soc. Mag. Res. Med.(ISMRM) 8, 558-559, 2020 | 1 | 2020 |
