Tom Brosch
Impact in
- Neurology top 5%
- Brain Tumor Detection and Classification
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- Medical Image Segmentation Techniques
- Advanced Neural Network Applications
- Digital Imaging for Blood Diseases
Papers in
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- Medical Image Segmentation Techniques 7
- Advanced Neural Network Applications 4
- Digital Imaging for Blood Diseases 2
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- Radiomics and Machine Learning in Medical Imaging 3
- Ultrasound Imaging and Elastography 2
- Co-authors
- Roger Tam (6 shared papers)Anthony Traboulsee (4 shared papers)Youngjin Yoo (3 shared papers)David K.B. Li (3 shared papers)Lisa Tang (3 shared papers)Axel Saalbach (2 shared papers)Alexander Rauscher (2 shared papers)Nathan Cross (1 shared paper)
- Journals
- NeuroImage Clinical (2 papers)IEEE Transactions on Medical Imaging (1 paper)Medical Image Analysis (1 paper)Neural Computation (1 paper)American Journal of Neuroradiology (1 paper)
- Partner nations
- GermanyCanadaUnited States
In The Last Decade
Tom Brosch
19 papers receiving 684 citations
Tom Brosch's Hit Papers
Peers
Comparison fields: 5 of 78
- Neurology 159
- Computer Vision and Pattern Recognition 252
- Radiology, Nuclear Medicine and Imaging 237
- Health Informatics 13
- Health Information Management 27
Countries citing papers authored by Tom Brosch
This map shows the geographic impact of Tom Brosch's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tom Brosch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom Brosch more than expected).
Fields of papers citing papers by Tom Brosch
This network shows the impact of papers produced by Tom Brosch. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tom Brosch. The network helps show where Tom Brosch may publish in the future.
Co-authors
The 25 scholars most cited alongside Tom Brosch, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation Hit paper breakdown → | 2016 | 312 |
| 2 | 2013 | 127 | |
| 3 | 2017 | 63 | |
| 4 | 2014 | 40 | |
| 5 | 2020 | 34 | |
| 6 | 2014 | 32 | |
| 7 | 2021 | 16 | |
| 8 | 2018 | 15 | |
| 9 | 2018 | 14 | |
| 10 | 2022 | 11 | |
| 11 | 2019 | 9 | |
| 12 | 2018 | 9 | |
| 13 | 2023 | 6 | |
| 14 | Comparison of deep learning-based techniques for organ segmentation in abdominal CT images | 2018 | 6 |
| 15 | 2021 | 5 | |
| 16 | 2018 | 4 | |
| 17 | 2020 | 4 | |
| 18 | 2016 | 1 | |
| 19 | 2018 | 1 | |
| 20 | MALWARE REMOVAL - BEYOND CONTENT AND CONTEXT SCANNING | 2007 | 0 |
About Tom Brosch
Tom Brosch is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Pathology and Forensic Medicine and Epidemiology, having authored 20 papers that have together received 709 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (7 papers), Advanced Neural Network Applications (4 papers), AI in cancer detection (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Multiple Sclerosis Research Studies (3 papers), Ultrasound Imaging and Elastography (2 papers), Digital Imaging for Blood Diseases (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). The work is most often cited by research in Neurology (159 citations), Computer Vision and Pattern Recognition (252 citations), Radiology, Nuclear Medicine and Imaging (237 citations), Health Informatics (13 citations) and Health Information Management (27 citations). Tom Brosch has collaborated with scholars based in Germany, Canada and United States. Frequent co-authors include Roger Tam, Anthony Traboulsee, Youngjin Yoo, David K.B. Li, Lisa Tang, Axel Saalbach, Alexander Rauscher, Nathan Cross, Jalal B. Andre and Shannon Kolind. Their work appears in journals such as NeuroImage Clinical, IEEE Transactions on Medical Imaging, Medical Image Analysis, Neural Computation and American Journal of Neuroradiology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.