Andrew J. Bulpitt
- Molecular Biology
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Biomedical Engineering
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- David R. WestheadChris J. NeedhamJames BradfordDerek MageeNeil SumpterDarren TreanorYi SongMatthew A. Care
- Topics
- Medical Image Segmentation Techniques (9 papers)Machine Learning in Bioinformatics (6 papers)Surgical Simulation and Training (6 papers)
- Partner nations
- United KingdomAustraliaIndia
In The Last Decade
Andrew J. Bulpitt
45 papers receiving 905 citations
Peers
Comparison fields: 5 of 139
- Molecular Biology 396
- Artificial Intelligence 225
- Computer Vision and Pattern Recognition 197
- Biomedical Engineering 88
- Radiology, Nuclear Medicine and Imaging 86
Countries citing papers authored by Andrew J. Bulpitt
This map shows the geographic impact of Andrew J. Bulpitt'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 Andrew J. Bulpitt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew J. Bulpitt more than expected).
Fields of papers citing papers by Andrew J. Bulpitt
This network shows the impact of papers produced by Andrew J. Bulpitt. 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 Andrew J. Bulpitt. The network helps show where Andrew J. Bulpitt may publish in the future.
Co-authorship network of co-authors of Andrew J. Bulpitt
This figure shows the co-authorship network connecting the top 25 collaborators of Andrew J. Bulpitt. A scholar is included among the top collaborators of Andrew J. Bulpitt 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 Andrew J. Bulpitt. Andrew J. Bulpitt is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 4 | |
| 4 | A Novel Approach for the Colour Deconvolution of Multiple Histological Stains. | 7 |
| 5 | 4 | |
| 6 | 33 | |
| 7 | 21 | |
| 8 | 3 | |
| 9 | 8 | |
| 10 | 17 | |
| 11 | 14 | |
| 12 | 33 | |
| 13 | Physics-based virtual environment for training core skills in vascular interventional radiological procedures. | 2 |
| 14 | 214 | |
| 15 | A 6DOF gravity compensation scheme for a phantom premium using a neural network. | 2 |
| 16 | 19 | |
| 17 | 80 | |
| 18 | 68 | |
| 19 | 15 | |
| 20 | Learning Models of Animal Behaviour for a Robotic Sheepdog | 2 |
About Andrew J. Bulpitt
Andrew J. Bulpitt is a scholar working on Computer Vision and Pattern Recognition, Family Practice and Artificial Intelligence, having authored 46 papers that have together received 931 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (9 papers), Machine Learning in Bioinformatics (6 papers) and Surgical Simulation and Training (6 papers). The work is most often cited by research in Biophysics (75 citations), Computer Vision and Pattern Recognition (197 citations) and Artificial Intelligence (225 citations). Andrew J. Bulpitt has collaborated with scholars based in United Kingdom, Australia and India. Frequent co-authors include David R. Westhead, Chris J. Needham, James Bradford, Derek Magee, Neil Sumpter, Darren Treanor, Yi Song, Matthew A. Care, Elizabeth Berry and Ruth K. Wilcox. Their work appears in journals such as Nature Biotechnology, Bioinformatics and Journal of Molecular Biology.
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.