| Robust vessel segmentation in fundus images A Budai, R Bock, A Maier, J Hornegger, G Michelson International journal of biomedical imaging 2013 (1), 154860, 2013 | 677 | 2013 |
| A gentle introduction to deep learning in medical image processing A Maier, C Syben, T Lasser, C Riess Zeitschrift für Medizinische Physik 29 (2), 86-101, 2019 | 650 | 2019 |
| Automatic classification of defective photovoltaic module cells in electroluminescence images S Deitsch, V Christlein, S Berger, C Buerhop-Lutz, A Maier, F Gallwitz, ... Solar Energy 185, 455-468, 2019 | 518* | 2019 |
| Multi-scale deep reinforcement learning for real-time 3D-landmark detection in CT scans FC Ghesu, B Georgescu, Y Zheng, S Grbic, A Maier, J Hornegger, ... IEEE transactions on pattern analysis and machine intelligence 41 (1), 176-189, 2017 | 349 | 2017 |
| A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging Z Xiong, Q Xia, Z Hu, N Huang, C Bian, Y Zheng, S Vesal, N Ravikumar, ... Medical image analysis 67, 101832, 2021 | 347 | 2021 |
| Automatic classification of cancerous tissue in laserendomicroscopy images of the oral cavity using deep learning M Aubreville, C Knipfer, N Oetter, C Jaremenko, E Rodner, J Denzler, ... Scientific reports 7 (1), 11979, 2017 | 305 | 2017 |
| Deep learning computed tomography: Learning projection-domain weights from image domain in limited angle problems T Würfl, M Hoffmann, V Christlein, K Breininger, Y Huang, M Unberath, ... IEEE transactions on medical imaging 37 (6), 1454-1463, 2018 | 280 | 2018 |
| Robust non-rigid registration through agent-based action learning J Krebs, T Mansi, H Delingette, L Zhang, FC Ghesu, S Miao, AK Maier, ... Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017 | 278 | 2017 |
| Learning to recognize abnormalities in chest x-rays with location-aware dense networks S Guendel, S Grbic, B Georgescu, S Liu, A Maier, D Comaniciu Progress in Pattern Recognition, Image Analysis, Computer Vision, and …, 2019 | 236 | 2019 |
| PEAKS–A system for the automatic evaluation of voice and speech disorders A Maier, T Haderlein, U Eysholdt, F Rosanowski, A Batliner, M Schuster, ... Speech Communication 51 (5), 425-437, 2009 | 234 | 2009 |
| Deep learning computed tomography T Würfl, FC Ghesu, V Christlein, A Maier Medical Image Computing and Computer-Assisted Intervention-MICCAI 2016: 19th …, 2016 | 218 | 2016 |
| Learning with known operators reduces maximum error bounds AK Maier, C Syben, B Stimpel, T Würfl, M Hoffmann, F Schebesch, W Fu, ... Nature machine intelligence 1 (8), 373-380, 2019 | 200 | 2019 |
| Classification of breast cancer histology images using transfer learning S Vesal, N Ravikumar, AA Davari, S Ellmann, A Maier Image Analysis and Recognition: 15th International Conference, ICIAR 2018 …, 2018 | 186 | 2018 |
| Towards more reality in the recognition of emotional speech B Schuller, D Seppi, A Batliner, A Maier, S Steidl 2007 IEEE international conference on acoustics, speech and signal …, 2007 | 186 | 2007 |
| Age and gender recognition for telephone applications based on gmm supervectors and support vector machines T Bocklet, A Maier, JG Bauer, F Burkhardt, E Noth 2008 IEEE International Conference on Acoustics, Speech and Signal …, 2008 | 182 | 2008 |
| Medical imaging systems: An introductory guide A Maier, S Steidl, V Christlein, J Hornegger Springer, 2018 | 181 | 2018 |
| CONRAD—A software framework for cone‐beam imaging in radiology A Maier, HG Hofmann, M Berger, P Fischer, C Schwemmer, H Wu, ... Medical physics 40 (11), 111914, 2013 | 170 | 2013 |
| Evaluation of speech intelligibility for children with cleft lip and palate by means of automatic speech recognition M Schuster, A Maier, T Haderlein, E Nkenke, U Wohlleben, F Rosanowski, ... International Journal of Pediatric Otorhinolaryngology 70 (10), 1741-1747, 2006 | 156 | 2006 |
| Writer identification using GMM supervectors and exemplar-SVMs V Christlein, D Bernecker, F Hönig, A Maier, E Angelopoulou Pattern Recognition 63, 258-267, 2017 | 145 | 2017 |
| A benchmark for visual identification of defective solar cells in electroluminescence imagery C Buerhop-Lutz, S Deitsch, A Maier, F Gallwitz, S Berger, B Doll, J Hauch, ... 35th European PV Solar Energy Conference and Exhibition 12871289, 1287-1289, 2018 | 141 | 2018 |
Joachim HorneggerProfessor of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg確認したメール アドレス: fau.de