| Regressing heatmaps for multiple landmark localization using CNNs C Payer, D Štern, H Bischof, M Urschler Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016: 19th …, 2016 | 282 | 2016 |
| Evaluation of algorithms for multi-modality whole heart segmentation: an open-access grand challenge X Zhuang, L Li, C Payer, D Štern, M Urschler, MP Heinrich, J Oster, ... Medical image analysis 58, 101537, 2019 | 202 | 2019 |
| Integrating spatial configuration into heatmap regression based CNNs for landmark localization C Payer, D Štern, H Bischof, M Urschler Medical image analysis 54, 207-219, 2019 | 191 | 2019 |
| Multi-label whole heart segmentation using CNNs and anatomical label configurations C Payer, D Štern, H Bischof, M Urschler Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS …, 2018 | 156 | 2018 |
| VerSe: A vertebrae labelling and segmentation benchmark for multi-detector CT images A Sekuboyina, ME Husseini, A Bayat, M Löffler, H Liebl, H Li, G Tetteh, ... Medical image analysis 73, 102166, 2021 | 80 | 2021 |
| Instance segmentation and tracking with cosine embeddings and recurrent hourglass networks C Payer, D Štern, T Neff, H Bischof, M Urschler Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 77 | 2018 |
| Automated age estimation from MRI volumes of the hand D Štern, C Payer, M Urschler Medical image analysis 58, 101538, 2019 | 59 | 2019 |
| A framework for the generation of digital twins of cardiac electrophysiology from clinical 12-leads ECGs K Gillette, MAF Gsell, AJ Prassl, E Karabelas, U Reiter, G Reiter, ... Medical Image Analysis 71, 102080, 2021 | 57 | 2021 |
| Segmenting and tracking cell instances with cosine embeddings and recurrent hourglass networks C Payer, D Štern, M Feiner, H Bischof, M Urschler Medical image analysis 57, 106-119, 2019 | 56 | 2019 |
| Automatic age estimation and majority age classification from multi-factorial MRI data D Štern, C Payer, N Giuliani, M Urschler IEEE Journal of Biomedical and Health Informatics 23 (4), 1392-1403, 2018 | 56 | 2018 |
| Coarse to Fine Vertebrae Localization and Segmentation with SpatialConfiguration-Net and U-Net. C Payer, D Stern, H Bischof, M Urschler VISIGRAPP (5: VISAPP), 124-133, 2020 | 52 | 2020 |
| Generative adversarial network based synthesis for supervised medical image segmentation T Neff, C Payer, D Stern, M Urschler Proc. OAGM and ARW joint Workshop 3, 4, 2017 | 49 | 2017 |
| Automated age estimation from hand MRI volumes using deep learning D Štern, C Payer, V Lepetit, M Urschler Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016: 19th …, 2016 | 42 | 2016 |
| Automated integer programming based separation of arteries and veins from thoracic CT images C Payer, M Pienn, Z Bálint, A Shekhovtsov, E Talakic, E Nagy, ... Medical image analysis 34, 109-122, 2016 | 37 | 2016 |
| Fast and low-GPU-memory abdomen CT organ segmentation: the flare challenge J Ma, Y Zhang, S Gu, X An, Z Wang, C Ge, C Wang, F Zhang, Y Wang, ... Medical Image Analysis 82, 102616, 2022 | 31 | 2022 |
| Verse: a vertebrae labelling and segmentation benchmark A Sekuboyina, A Bayat, ME Husseini, M Löffler, M Rempfler, J Kukačka, ... | 31 | 2020 |
| Matwo-capsnet: a multi-label semantic segmentation capsules network S Bonheur, D Štern, C Payer, M Pienn, H Olschewski, M Urschler Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 29 | 2019 |
| Multi-factorial age estimation from skeletal and dental MRI volumes D Štern, P Kainz, C Payer, M Urschler Machine Learning in Medical Imaging: 8th International Workshop, MLMI 2017 …, 2017 | 22 | 2017 |
| Quantitative CT‐derived vessel metrics in idiopathic pulmonary fibrosis: A structure–function study J Jacob, M Pienn, C Payer, M Urschler, M Kokosi, A Devaraj, AU Wells, ... Respirology 24 (5), 445-452, 2019 | 20 | 2019 |
| Reducing acquisition time for MRI-based forensic age estimation B Neumayer, M Schloegl, C Payer, T Widek, S Tschauner, T Ehammer, ... Scientific Reports 8 (1), 2063, 2018 | 18 | 2018 |
Martin UrschlerMedical University GrazVerified email at medunigraz.at
