| Bioconda: a sustainable and comprehensive software distribution for the life sciences B Grüning, R Dale, A Sjödin, J Rowe, BA Chapman, CH Tomkins-Tinch, ... Nature Methods 15, 475-476, 2018 | 328 | 2018 |
| Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge M Veta, YJ Heng, N Stathonikos, BE Bejnordi, F Beca, T Wollmann, ... Medical image analysis 54, 111-121, 2019 | 82 | 2019 |
| Workflows for microscopy image analysis and cellular phenotyping T Wollmann, H Erfle, R Eils, K Rohr, M Gunkel Journal of biotechnology 261, 70-75, 2017 | 15 | 2017 |
| User-Centred Design and Usability Evaluation of a Heart Rate Variability Biofeedback Game T Wollmann, F Abtahi, A Eghdam, F Seoane, K Lindecrantz, M Haag, ... IEEE Access, 2016 | 12 | 2016 |
| GRUU-Net: Integrated convolutional and gated recurrent neural network for cell segmentation T Wollmann, M Gunkel, I Chung, H Erfle, K Rippe, K Rohr Medical image analysis 56, 68-79, 2019 | 10 | 2019 |
| Deep residual Hough voting for mitotic cell detection in histopathology images T Wollmann, K Rohr 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017 …, 2017 | 10 | 2017 |
| Adversarial domain adaptation to improve automatic breast cancer grading in lymph nodes T Wollmann, CS Eijkman, K Rohr 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018 | 8 | 2018 |
| DetNet: Deep neural network for particle detection in fluorescence microscopy images T Wollmann, C Ritter, JN Dohrke, JY Lee, R Bartenschlager, K Rohr 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019 …, 2019 | 7 | 2019 |
| Deep particle tracker: Automatic tracking of particles in fluorescence microscopy images using deep learning R Spilger, T Wollmann, Y Qiang, A Imle, JY Lee, B Müller, OT Fackler, ... Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical …, 2018 | 7 | 2018 |
| Automatic breast cancer grading in lymph nodes using a deep neural network T Wollmann, K Rohr arXiv preprint arXiv:1707.07565, 2017 | 7 | 2017 |
| Multi-channel deep transfer learning for nuclei segmentation in glioblastoma cell tissue images T Wollmann, J Ivanova, M Gunkel, I Chung, H Erfle, K Rippe, K Rohr Bildverarbeitung für die Medizin 2018, 316-321, 2018 | 6 | 2018 |
| Hyperparameter optimization for image analysis: application to prostate tissue images and live cell data of virus-infected cells C Ritter, T Wollmann, P Bernhard, M Gunkel, DM Braun, JY Lee, ... International journal of computer assisted radiology and surgery 14 (11 …, 2019 | 5 | 2019 |
| Comparison of segmentation methods for tissue microscopy images of glioblastoma cells D Baltissen, T Wollmann, M Gunkel, I Chung, H Erfle, K Rippe, K Rohr 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018 | 5 | 2018 |
| Erfolgreiches Lernen durch gamifiziertes E-Learning F Pawelka, T Wollmann, J Stöber, TV Lam Informatik 2014, 2014 | 5 | 2014 |
| Accessible and reproducible mass spectrometry imaging data analysis in Galaxy MC Föll, L Moritz, T Wollmann, MN Stillger, N Vockert, M Werner, ... GigaScience 8 (12), 2019 | 4 | 2019 |
| Black-box hyperparameter optimization for nuclei segmentation in prostate tissue images T Wollmann, P Bernhard, M Gunkel, DM Braun, J Meiners, R Simon, ... Bildverarbeitung für die Medizin 2019, 345-350, 2019 | 4 | 2019 |
| Automatic grading of breast cancer whole-slide histopathology images T Wollmann, K Rohr Bildverarbeitung für die Medizin 2017, 249-253, 2017 | 4 | 2017 |
| Deep Learning Particle Detection for Probabilistic Tracking in Fluorescence Microscopy Images C Ritter, T Wollmann, JY Lee, R Bartenschlager, K Rohr 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 977-980, 2020 | 1 | 2020 |
| Design And Evaluation Of Exergaming Concepts For Heart Rate Variability Biofeedback Training T Wollmann Heidelberg University, 2016 | 1* | 2016 |
| Deep Learning for Detection and Segmentation in High-Content Microscopy Images T Wollmann Heidelberg University, 2020 | | 2020 |
