| Self-supervision with superpixels: Training few-shot medical image segmentation without annotation C Ouyang, C Biffi, C Chen, T Kart, H Qiu, D Rueckert Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 218 | 2020 |
| Self-supervised learning for few-shot medical image segmentation C Ouyang, C Biffi, C Chen, T Kart, H Qiu, D Rueckert IEEE Transactions on Medical Imaging 41 (7), 1837-1848, 2022 | 80 | 2022 |
| Deep Learning‐Based Automated Abdominal Organ Segmentation in the UK Biobank and German National Cohort Magnetic Resonance Imaging Studies T Kart, M Fischer, T Küstner, T Hepp, F Bamberg, S Winzeck, B Glocker, ... Investigative Radiology 56 (6), 401-408, 2021 | 47 | 2021 |
| DeepMCAT: large-scale deep clustering for medical image categorization T Kart, W Bai, B Glocker, D Rueckert Deep Generative Models, and Data Augmentation, Labelling, and Imperfections …, 2021 | 12 | 2021 |
| Monitoring gold nanoparticle distribution with high resolution using photo-magnetic imaging AT Luk, F Nouizi, M Marks, T Kart, G Gulsen Optical Interactions with Tissue and Cells XXVII 9706, 74-79, 2016 | 12 | 2016 |
| Fourier transform optical profilometry using fiber optic Lloyd’s mirrors T Kart, G Kösoğlu, H Yüksel, MN İnci Applied optics 53 (35), 8175-8181, 2014 | 11 | 2014 |
| Automated imaging-based abdominal organ segmentation and quality control in 20,000 participants of the UK Biobank and German National Cohort Studies T Kart, M Fischer, S Winzeck, B Glocker, W Bai, R Bülow, C Emmel, ... Scientific Reports 12 (1), 18733, 2022 | 9 | 2022 |
| Training deep segmentation networks on texture-encoded input: application to neuroimaging of the developing neonatal brain AE Fetit, J Cupitt, T Kart, D Rueckert Medical Imaging with Deep Learning, 230-240, 2020 | 9 | 2020 |
| Better together: data harmonization and cross-study analysis of abdominal MRI data from UK biobank and the German National Cohort S Gatidis, T Kart, M Fischer, S Winzeck, B Glocker, W Bai, R Bülow, ... Investigative radiology 58 (5), 346-354, 2023 | 4 | 2023 |
| MetaDetector: Detecting Outliers by Learning to Learn from Self-supervision J Tan, T Kart, B Hou, J Batten, B Kainz International Conference on Medical Image Computing and Computer-Assisted …, 2021 | 3 | 2021 |
| Automated breast cancer lesion detection on breast MRI using artificial intelligence. N Tapia Negrete, R Takhtawala, M Shaver, T Kart, Y Zhang, MJ Kim, ... Journal of Clinical Oncology 37 (15_suppl), e14612-e14612, 2019 | 3 | 2019 |
| Modelling relations between blood pressure, cardiovascular phenotype, and clinical factors using large scale imaging data T Kart, M Alkhodari, W Lapidaire, P Leeson European Heart Journal-Cardiovascular Imaging 24 (10), 1361-1362, 2023 | 2 | 2023 |
| Automated artificial intelligence quantification of fibroglandular tissue on breast MRI. R Takhtawala, N Tapia Negrete, M Shaver, T Kart, Y Zhang, VY Park, ... Journal of Clinical Oncology 37 (15_suppl), e12071-e12071, 2019 | 2 | 2019 |
| Hyperscore: a unified measure to model hypertension progression using multi-modality measurements and semi-supervised learning M Alkhodari, W Lapidaire, Z Xiong, T Kart, Y Iturria-Medina, ... 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2023 | 1 | 2023 |
| Quality Control Matters: Automated Magnetic Resonance Imaging-based Abdominal Organ Segmentation in 20,000 Participants of the UK Biobank and German National Cohort Studies. T Kart, M Fischer, S Winzeck, B Glocker, W Bai, R Bülow, C Emmel, ... | 1 | 2022 |
| 3D optical profilometry using a fiber optic Lloyd's mirror T Kart, G Kosoglu, H Yuksel, MN Inci Interferometry XVII: Advanced Applications 9204, 45-51, 2014 | 1 | 2014 |
| Classification of Amyloid Beta Deposition Patterns: Comparison of Customized Deep Learning Approaches (vol 78, pg 539, 2019) P Chang, T Kart, D Chow, E Monuki, Z Tang, M Keiser, B Dugger JOURNAL OF NEUROPATHOLOGY AND EXPERIMENTAL NEUROLOGY 79 (9), 1027-1027, 2020 | | 2020 |
| Classification of Amyloid Beta Deposition Patterns: Comparison of Customized Deep Learning Approaches P Chang, T Kart, D Chow, E Monuki, Z Tang, M Keiser, B Dugger JOURNAL OF NEUROPATHOLOGY AND EXPERIMENTAL NEUROLOGY 78 (6), 539-540, 2019 | | 2019 |
Daniel RueckertTechnical University of Munich and Imperial College London在 tum.de 的电子邮件经过验证
