Tal Arbel
Impact in
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- Medical Image Segmentation Techniques
- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
- Neurology top 2%
- Brain Tumor Detection and Classification
Papers in
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- Medical Image Segmentation Techniques 37
- Advanced Image and Video Retrieval Techniques 18
- Face recognition and analysis 10
- Face and Expression Recognition 9
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- AI in cancer detection 9
- Co-authors
- M. Jorge Cardoso (8 shared papers)D. Louis Collins (25 shared papers)Matthew Toews (11 shared papers)Douglas L. Arnold (21 shared papers)Frank P. Ferrie (7 shared papers)Nagesh K. Subbanna (8 shared papers)Doina Precup (14 shared papers)James J. Clark (15 shared papers)
- Journals
- IEEE Transactions on Medical Imaging (9 papers)Medical Image Analysis (5 papers)Computer Vision and Image Understanding (5 papers)Image and Vision Computing (3 papers)International Journal of Computer Vision (3 papers)
- Partner nations
- CanadaUnited StatesUnited Kingdom
In The Last Decade
Tal Arbel
95 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 149
- Computer Vision and Pattern Recognition 1.5k
- Neurology 355
- Radiology, Nuclear Medicine and Imaging 987
- Health Informatics 45
- Artificial Intelligence 661
Countries citing papers authored by Tal Arbel
This map shows the geographic impact of Tal Arbel'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 Tal Arbel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tal Arbel more than expected).
Fields of papers citing papers by Tal Arbel
This network shows the impact of papers produced by Tal Arbel. 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 Tal Arbel. The network helps show where Tal Arbel may publish in the future.
Co-authors
The 25 scholars most cited alongside Tal Arbel, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 97 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support Hit paper breakdown → | 2017 | 970 |
| 2 | 2020 | 120 | |
| 3 | 2010 | 116 | |
| 4 | 2016 | 79 | |
| 5 | 2016 | 79 | |
| 6 | 2009 | 71 | |
| 7 | 2008 | 67 | |
| 8 | 1999 | 60 | |
| 9 | 2013 | 52 | |
| 10 | 2012 | 52 | |
| 11 | 2004 | 49 | |
| 12 | 2001 | 49 | |
| 13 | 2013 | 45 | |
| 14 | 2017 | 44 | |
| 15 | 2012 | 36 | |
| 16 | 2020 | 36 | |
| 17 | Prediction of Disease Progression in Multiple Sclerosis Patients using Deep Learning Analysis of MRI Data | 2019 | 32 |
| 18 | 2017 | 31 | |
| 19 | 2018 | 31 | |
| 20 | 2006 | 31 |
About Tal Arbel
Tal Arbel is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Neurology and Aerospace Engineering, having authored 97 papers that have together received 2.8k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (37 papers), Advanced Image and Video Retrieval Techniques (18 papers), Brain Tumor Detection and Classification (16 papers), Robotics and Sensor-Based Localization (13 papers), Medical Imaging Techniques and Applications (10 papers), Face recognition and analysis (10 papers), Face and Expression Recognition (9 papers) and AI in cancer detection (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.5k citations), Neurology (355 citations), Radiology, Nuclear Medicine and Imaging (987 citations), Health Informatics (45 citations) and Artificial Intelligence (661 citations). Tal Arbel has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include M. Jorge Cardoso, D. Louis Collins, Matthew Toews, Douglas L. Arnold, Frank P. Ferrie, Nagesh K. Subbanna, Doina Precup, James J. Clark, Catherine Laporte and Dante De Nigris. Their work appears in journals such as IEEE Transactions on Medical Imaging, Medical Image Analysis, Computer Vision and Image Understanding, Image and Vision Computing and International Journal of Computer Vision.
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.