Tal Arbel
Impact in
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- Medical Image Segmentation Techniques
- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
- Face recognition and analysis
- Neurology top 2%
- Brain Tumor Detection and Classification
Papers in
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- Medical Image Segmentation Techniques 43
- Advanced Image and Video Retrieval Techniques 20
- Face recognition and analysis 12
- Face and Expression Recognition 11
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- AI in cancer detection 16
- Co-authors
- M. Jorge Cardoso (7 shared papers)D. Louis Collins (32 shared papers)Douglas L. Arnold (35 shared papers)Matthew Toews (12 shared papers)Frank P. Ferrie (8 shared papers)Doina Precup (17 shared papers)Nagesh K. Subbanna (9 shared papers)James J. Clark (16 shared papers)
- Journals
- IEEE Transactions on Medical Imaging (9 papers)Lecture notes in computer science (50 papers)Computer Vision and Image Understanding (5 papers)Medical Image Analysis (5 papers)International Journal of Computer Vision (3 papers)
- Partner nations
- CanadaUnited KingdomUnited States
In The Last Decade
Tal Arbel
119 papers receiving 3.3k citations
Tal Arbel's Hit Papers
Peers
Comparison fields: 5 of 150
- Computer Vision and Pattern Recognition 1.7k
- Neurology 430
- Radiology, Nuclear Medicine and Imaging 992
- Health Informatics 55
- Artificial Intelligence 755
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 127 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 | 1004 |
| 2 | 2010 | 134 | |
| 3 | 2020 | 127 | |
| 4 | 2016 | 88 | |
| 5 | 2008 | 86 | |
| 6 | 2016 | 86 | |
| 7 | 2009 | 77 | |
| 8 | 1999 | 67 | |
| 9 | 2004 | 60 | |
| 10 | 2012 | 60 | |
| 11 | 2013 | 60 | |
| 12 | 2001 | 53 | |
| 13 | 2013 | 51 | |
| 14 | 2017 | 51 | |
| 15 | 2018 | 46 | |
| 16 | 2019 | 39 | |
| 17 | 2012 | 38 | |
| 18 | Prediction of Disease Progression in Multiple Sclerosis Patients using Deep Learning Analysis of MRI Data | 2019 | 37 |
| 19 | 2017 | 37 | |
| 20 | 2006 | 36 |
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 127 papers that have together received 3.3k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (43 papers), Brain Tumor Detection and Classification (22 papers), Advanced Image and Video Retrieval Techniques (20 papers), AI in cancer detection (16 papers), Robotics and Sensor-Based Localization (15 papers), Face recognition and analysis (12 papers), Radiomics and Machine Learning in Medical Imaging (12 papers) and Face and Expression Recognition (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.7k citations), Neurology (430 citations), Radiology, Nuclear Medicine and Imaging (992 citations), Health Informatics (55 citations) and Artificial Intelligence (755 citations). Tal Arbel has collaborated with scholars based in Canada, United Kingdom and United States. Frequent co-authors include M. Jorge Cardoso, D. Louis Collins, Douglas L. Arnold, Matthew Toews, Frank P. Ferrie, Doina Precup, Nagesh K. Subbanna, James J. Clark, Catherine Laporte and Dante De Nigris. Their work appears in journals such as IEEE Transactions on Medical Imaging, Lecture notes in computer science, Computer Vision and Image Understanding, Medical Image Analysis 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.