Gareth Funka-Lea
- Computer Vision and Pattern Recognition top 0.5%
- Radiology, Nuclear Medicine and Imaging top 2%
- Pulmonary and Respiratory Medicine top 10%
- Biomedical Engineering top 10%
- Artificial Intelligence top 5%
- Co-authors
- Yuri BoykovIsabelle BlochElsa D. AngeliniDavid LesageRůžena BajcsyMarie‐Pierre JollyYefeng ZhengHüseyin Tek
- Topics
- Medical Image Segmentation Techniques (22 papers)Medical Imaging Techniques and Applications (9 papers)Advanced Neural Network Applications (4 papers)
- Journals
- IEEE Transactions on Biomedical EngineeringInternational Journal of Computer VisionMedical Image Analysis
- Partner nations
- United StatesGermanyFrance
In The Last Decade
Gareth Funka-Lea
32 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 116
- Computer Vision and Pattern Recognition 1.7k
- Radiology, Nuclear Medicine and Imaging 790
- Pulmonary and Respiratory Medicine 327
- Biomedical Engineering 324
- Artificial Intelligence 260
Countries citing papers authored by Gareth Funka-Lea
This map shows the geographic impact of Gareth Funka-Lea'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 Gareth Funka-Lea with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gareth Funka-Lea more than expected).
Fields of papers citing papers by Gareth Funka-Lea
This network shows the impact of papers produced by Gareth Funka-Lea. 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 Gareth Funka-Lea. The network helps show where Gareth Funka-Lea may publish in the future.
Co-authorship network of co-authors of Gareth Funka-Lea
This figure shows the co-authorship network connecting the top 25 collaborators of Gareth Funka-Lea. A scholar is included among the top collaborators of Gareth Funka-Lea based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gareth Funka-Lea. Gareth Funka-Lea is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 12 | |
| 3 | 41 | |
| 4 | 6 | |
| 5 | 5 | |
| 6 | 6 | |
| 7 | A review of 3D vessel lumen segmentation techniques: Models, features and extraction schemesbreakdown → | 619 |
| 8 | 15 | |
| 9 | 30 | |
| 10 | 13 | |
| 11 | 5 | |
| 12 | 28 | |
| 13 | 28 | |
| 14 | 24 | |
| 15 | 48 | |
| 16 | 6 | |
| 17 | 4 | |
| 18 | 3 | |
| 19 | Active Color Image Analysis for Recognizing Shadows | 5 |
| 20 | 7 |
About Gareth Funka-Lea
Gareth Funka-Lea is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Computer Graphics and Computer-Aided Design, having authored 32 papers that have together received 2.4k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (22 papers), Medical Imaging Techniques and Applications (9 papers) and Advanced Neural Network Applications (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.7k citations), Radiology, Nuclear Medicine and Imaging (790 citations) and Biophysics (119 citations). Gareth Funka-Lea has collaborated with scholars based in United States, Germany and France. Frequent co-authors include Yuri Boykov, Isabelle Bloch, Elsa D. Angelini, David Lesage, Růžena Bajcsy, Marie‐Pierre Jolly, Yefeng Zheng, Hüseyin Tek, Charles Florin and Leo Grady. Their work appears in journals such as IEEE Transactions on Biomedical Engineering, International Journal of Computer Vision and Medical Image Analysis.
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.