| Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv preprint arXiv:1811.02629, 2018 | 2316 | 2018 |
| Assessing reliability and challenges of uncertainty estimations for medical image segmentation A Jungo, M Reyes Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 177 | 2019 |
| Analyzing the quality and challenges of uncertainty estimations for brain tumor segmentation A Jungo, F Balsiger, M Reyes Frontiers in neuroscience, 282, 2020 | 105 | 2020 |
| On the effect of inter-observer variability for a reliable estimation of uncertainty of medical image segmentation A Jungo, R Meier, E Ermis, M Blatti-Moreno, E Herrmann, R Wiest, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 104 | 2018 |
| Fully automated brain resection cavity delineation for radiation target volume definition in glioblastoma patients using deep learning E Ermiş, A Jungo, R Poel, M Blatti-Moreno, R Meier, U Knecht, ... Radiation oncology 15 (1), 1-10, 2020 | 76 | 2020 |
| Towards uncertainty-assisted brain tumor segmentation and survival prediction A Jungo, R McKinley, R Meier, U Knecht, L Vera, J Pérez-Beteta, ... Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2018 | 73 | 2018 |
| Deep learning versus classical regression for brain tumor patient survival prediction Y Suter, A Jungo, M Rebsamen, U Knecht, E Herrmann, R Wiest, M Reyes Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2019 | 61 | 2019 |
| Uncertainty-driven Sanity Check: Application to Postoperative Brain Tumor Cavity Segmentation A Jungo, R Meier, E Ermis, E Herrmann, M Reyes arXiv preprint arXiv:1806.03106, 2018 | 60 | 2018 |
| pymia: A Python package for data handling and evaluation in deep learning-based medical image analysis A Jungo, O Scheidegger, M Reyes, F Balsiger Computer methods and programs in biomedicine 198, 105796, 2021 | 52 | 2021 |
| Pooling-free fully convolutional networks with dense skip connections for semantic segmentation, with application to brain tumor segmentation R McKinley, A Jungo, R Wiest, M Reyes Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2018 | 34 | 2018 |
| Spatially regularized parametric map reconstruction for fast magnetic resonance fingerprinting F Balsiger, A Jungo, O Scheidegger, PG Carlier, M Reyes, B Marty Medical image analysis 64, 101741, 2020 | 28 | 2020 |
| Learning Bloch Simulations for MR Fingerprinting by Invertible Neural Networks F Balsiger, A Jungo, O Scheidegger, B Marty, M Reyes Machine Learning for Medical Image Reconstruction: Third International …, 2020 | 5 | 2020 |
| Perturb-and-MPM: quantifying segmentation uncertainty in dense multi-label CRFs R Meier, U Knecht, A Jungo, R Wiest, M Reyes arXiv preprint arXiv:1703.00312, 2017 | 4 | 2017 |
| Unsupervised out-of-distribution detection for safer robotically guided retinal microsurgery A Jungo, L Doorenbos, T Da Col, M Beelen, M Zinkernagel, ... International journal of computer assisted radiology and surgery, 1-7, 2023 | 2 | 2023 |
| P01. 088 Brain resection cavity delineation for radiation target volume definition in glioblastoma patients using deep learning E Herrmann, E Ermis, A Jungo, M Blatti-Moreno, U Knecht, DM Aebersold, ... Neuro-Oncology 20 (suppl_3), iii250-iii251, 2018 | 2 | 2018 |
| The MICCAI Hackathon on reproducibility, diversity, and selection of papers at the MICCAI conference F Balsiger, A Jungo, J Chen, I Ezhov, S Liu, J Ma, JC Paetzold, ... arXiv preprint arXiv:2103.05437, 2021 | 1 | 2021 |
| Organs at Risk Delineation for Brain Tumor Radiation Planning in Patients with Glioblastoma Using Deep Learning E Rüfenacht, A Jungo, E Ermiş, M Blatti-Moreno, H Hemmatazad, ... International Journal of Radiation Oncology• Biology• Physics 105 (1), E718-E719, 2019 | 1 | 2019 |
| Artificial Intelligence–Enhanced OCT Biomarkers Analysis in Macula-off Rhegmatogenous Retinal Detachment Patients LF Desideri, T Danilovska, E Bernardi, D Artemiev, K Paschon, M Hayoz, ... Translational Vision Science & Technology 13 (10), 21-21, 2024 | | 2024 |
| Artificial Intelligence-Enhanced OCT Biomarkers Analysis in Macula-Off Retinal Detachment Patients LF Desideri, T Danilovska, E Bernardi, D Artemiev, K Paschon, A Jungo, ... Investigative Ophthalmology & Visual Science 65 (7), 2335-2335, 2024 | | 2024 |
| A Multi-criteria Quality Assessment of Automated Alternative Segmentations for Radiation Therapy of Brain Tumor Patients AJ Kamath, R Münger, R Poel, E Rüfenacht, A Jungo, J Willmann, ... | | 2022 |
