Joan C. Vilanova
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
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- Medical Image Segmentation Techniques
Papers in
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- MRI in cancer diagnosis 26
- Radiomics and Machine Learning in Medical Imaging 20
- Medical Imaging Techniques and Applications 17
- Advanced MRI Techniques and Applications 14
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- Medical Image Segmentation Techniques 31
- Co-authors
- Xavier LladóArnau OliverJordi FreixenetJoaquim BarcelóRobert MartíLluís Ramió‐TorrentàÀlex RoviraMariano Cabezas
- Journals
- Radiographics (8 papers)European Radiology (3 papers)Medical Image Analysis (3 papers)Skeletal Radiology (3 papers)Neuroradiology (3 papers)
- Partner nations
- SpainFranceUnited States
In The Last Decade
Joan C. Vilanova
133 papers receiving 3.5k citations
Peers
Comparison fields: 5 of 152
- Radiology, Nuclear Medicine and Imaging 1.3k
- Computer Vision and Pattern Recognition 869
- Neurology 334
- Rheumatology 570
- Pulmonary and Respiratory Medicine 935
Countries citing papers authored by Joan C. Vilanova
This map shows the geographic impact of Joan C. Vilanova'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 Joan C. Vilanova with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joan C. Vilanova more than expected).
Fields of papers citing papers by Joan C. Vilanova
This network shows the impact of papers produced by Joan C. Vilanova. 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 Joan C. Vilanova. The network helps show where Joan C. Vilanova may publish in the future.
Co-authors
The 25 scholars most cited alongside Joan C. Vilanova, 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 | 2024 | 0 | |
| 2 | 2023 | 2 | |
| 3 | 2023 | 1 | |
| 4 | 2023 | 1 | |
| 5 | 2023 | 7 | |
| 6 | 2022 | 15 | |
| 7 | 2021 | 55 | |
| 8 | 2020 | 30 | |
| 9 | 2020 | 4 | |
| 10 | 2019 | 104 | |
| 11 | 2019 | 79 | |
| 12 | 2018 | 2 | |
| 13 | 2015 | 15 | |
| 14 | 2014 | 3 | |
| 15 | 2010 | 3 | |
| 16 | 2010 | 3 | |
| 17 | 2009 | 3 | |
| 18 | 2009 | 117 | |
| 19 | 2007 | 28 | |
| 20 | 2004 | 139 |
About Joan C. Vilanova
Joan C. Vilanova is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Orthopedics and Sports Medicine, Pulmonary and Respiratory Medicine and Rheumatology, having authored 143 papers that have together received 3.6k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (31 papers), Prostate Cancer Diagnosis and Treatment (28 papers), MRI in cancer diagnosis (26 papers), Radiomics and Machine Learning in Medical Imaging (20 papers), Medical Imaging Techniques and Applications (17 papers), AI in cancer detection (14 papers), Advanced MRI Techniques and Applications (14 papers) and Medical Imaging and Analysis (13 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (1.3k citations), Computer Vision and Pattern Recognition (869 citations), Neurology (334 citations), Rheumatology (570 citations) and Pulmonary and Respiratory Medicine (935 citations). Joan C. Vilanova has collaborated with scholars based in Spain, France and United States. Frequent co-authors include Xavier Lladó, Arnau Oliver, Jordi Freixenet, Joaquim Barceló, Robert Martí, Lluís Ramió‐Torrentà, Àlex Rovira, Mariano Cabezas, Antonio Luna and Sergi Valverde. Their work appears in journals such as Radiographics, European Radiology, Medical Image Analysis, Skeletal Radiology and 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.