Kola Babalola
- Computer Vision and Pattern Recognition top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Neurology
- Biomedical Engineering
- Cognitive Neuroscience
- Co-authors
- T.F. CootesChris TaylorMark JenkinsonCarole TwiningBrian PatenaudeWilliam R. CrumPaul AljabarDavid N. Kennedy
- Topics
- Medical Image Segmentation Techniques (9 papers)Face recognition and analysis (3 papers)Morphological variations and asymmetry (3 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceNeuroImageNeuropsychopharmacology
- Partner nations
- United KingdomNigeriaUnited States
In The Last Decade
Kola Babalola
16 papers receiving 375 citations
Peers
Comparison fields: 5 of 82
- Computer Vision and Pattern Recognition 210
- Radiology, Nuclear Medicine and Imaging 130
- Neurology 51
- Biomedical Engineering 44
- Cognitive Neuroscience 43
Countries citing papers authored by Kola Babalola
This map shows the geographic impact of Kola Babalola'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 Kola Babalola with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kola Babalola more than expected).
Fields of papers citing papers by Kola Babalola
This network shows the impact of papers produced by Kola Babalola. 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 Kola Babalola. The network helps show where Kola Babalola may publish in the future.
Co-authorship network of co-authors of Kola Babalola
This figure shows the co-authorship network connecting the top 25 collaborators of Kola Babalola. A scholar is included among the top collaborators of Kola Babalola 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 Kola Babalola. Kola Babalola is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 4 | |
| 5 | 11 | |
| 6 | 43 | |
| 7 | 23 | |
| 8 | 2 | |
| 9 | 159 | |
| 10 | 61 | |
| 11 | 29 | |
| 12 | Automatic Segmentation of the Caudate Nuclei using Active Appearance Models | 7 |
| 13 | 5 | |
| 14 | 6 | |
| 15 | 4 | |
| 16 | 34 | |
| 17 | Groupwise registration of richly labelled images | 1 |
| 18 | 4 |
About Kola Babalola
Kola Babalola is a scholar working on Computer Vision and Pattern Recognition, Biophysics and Geometry and Topology, having authored 18 papers that have together received 394 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (9 papers), Face recognition and analysis (3 papers) and Morphological variations and asymmetry (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (210 citations), Neurology (51 citations) and Radiology, Nuclear Medicine and Imaging (130 citations). Kola Babalola has collaborated with scholars based in United Kingdom, Nigeria and United States. Frequent co-authors include T.F. Cootes, Chris Taylor, Mark Jenkinson, Carole Twining, Brian Patenaude, William R. Crum, Paul Aljabar, David N. Kennedy, Stephen M. Smith and Julia A. Schnabel. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, NeuroImage and Neuropsychopharmacology.
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.