Ester Bonmati
- Health Informatics top 5%
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- Radiomics and Machine Learning in Medical Imaging 5
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- Advanced Neural Network Applications 7
- Medical Image Segmentation Techniques 6
- Neurology top 10%
- Radiation top 10%
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- Prostate Cancer Diagnosis and Treatment 5
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- Surgical Simulation and Training 3
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- Colorectal Cancer Screening and Detection 3
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- Functional Brain Connectivity Studies 3
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- AI in cancer detection 2
- Co-authors
- Yipeng HuDean C. BarrattEli GibsonMatthew J. ClarksonKurinchi Selvan GurusamyBrian R DavidsonStephen P. PereiraSteve Bandula
- Cited by
- Health InformaticsRadiology, Nuclear Medicine and ImagingComputer Vision and Pattern Recognition
- Journals
- Medical Image Analysis (4 papers)International Journal of Computer Assisted Radiology and Surgery (3 papers)Medical Physics (2 papers)
- Partner nations
- United KingdomSpainUnited States
In The Last Decade
Ester Bonmati
22 papers receiving 964 citations
Hit Papers
Peers
Comparison fields: 5 of 86
- Health Informatics 36
- Radiology, Nuclear Medicine and Imaging 564
- Computer Vision and Pattern Recognition 480
- Neurology 78
- Radiation 74
Countries citing papers authored by Ester Bonmati
This map shows the geographic impact of Ester Bonmati'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 Ester Bonmati with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ester Bonmati more than expected).
Fields of papers citing papers by Ester Bonmati
This network shows the impact of papers produced by Ester Bonmati. 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 Ester Bonmati. The network helps show where Ester Bonmati may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ester Bonmati, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 2 | |
| 5 | 2023 | 1 | |
| 6 | 2022 | 5 | |
| 7 | 2021 | 16 | |
| 8 | 2020 | 18 | |
| 9 | 2020 | 20 | |
| 10 | 2020 | 35 | |
| 11 | 2019 | 54 | |
| 12 | 2018 | 23 | |
| 13 | Automatic Multi-Organ Segmentation on Abdominal CT With Dense V-Networksbreakdown → | 2018 | 472 |
| 14 | 2018 | 250 | |
| 15 | 2018 | 4 | |
| 16 | 2018 | 23 | |
| 17 | 2018 | 4 | |
| 18 | 2018 | 6 | |
| 19 | 2017 | 6 | |
| 20 | 2017 | 5 |
About Ester Bonmati
Ester Bonmati is a scholar working on Health Informatics, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 25 papers that have together received 985 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (7 papers), Medical Image Segmentation Techniques (6 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Prostate Cancer Diagnosis and Treatment (5 papers), Surgical Simulation and Training (3 papers), Colorectal Cancer Screening and Detection (3 papers), Functional Brain Connectivity Studies (3 papers) and AI in cancer detection (2 papers). The work is most often cited by research in Health Informatics (36 citations), Radiology, Nuclear Medicine and Imaging (564 citations) and Computer Vision and Pattern Recognition (480 citations). Ester Bonmati has collaborated with scholars based in United Kingdom, Spain and United States. Frequent co-authors include Yipeng Hu, Dean C. Barratt, Eli Gibson, Matthew J. Clarkson, Kurinchi Selvan Gurusamy, Brian R Davidson, Stephen P. Pereira, Steve Bandula, Francesco Giganti and Nooshin Ghavami. Their work appears in journals such as Medical Image Analysis, International Journal of Computer Assisted Radiology and Surgery, Medical Physics, IEEE Transactions on Medical Imaging and Pattern Analysis and Applications.
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.