James C. Gee
Impact in
- Radiology, Nuclear Medicine and Imaging top 0.02%
- Advanced Neuroimaging Techniques and Applications
- Advanced MRI Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
- Computer Vision and Pattern Recognition top 0.05%
- Medical Image Segmentation Techniques
Papers in
-
- Medical Image Segmentation Techniques 191
-
- Advanced Neuroimaging Techniques and Applications 63
- Retinal Imaging and Analysis 18
- Radiomics and Machine Learning in Medical Imaging 15
- Advanced MRI Techniques and Applications 11
- Co-authors
- Brian Avants (106 shared papers)Paul A. Yushkevich (55 shared papers)Nicholas James Tustison (55 shared papers)Philip A. Cook (36 shared papers)Murray Grossman (53 shared papers)Charles L. Epstein (8 shared papers)Sean Ho (2 shared papers)Guido Gerig (2 shared papers)
- Journals
- NeuroImage (27 papers)Academic Radiology (11 papers)IEEE Transactions on Medical Imaging (11 papers)Medical Image Analysis (9 papers)Lecture notes in computer science (71 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
James C. Gee
423 papers receiving 39k citations
James C. Gee's Hit Papers
Peers
Comparison fields: 5 of 198
- Radiology, Nuclear Medicine and Imaging 10k
- Computer Vision and Pattern Recognition 9.8k
- Cognitive Neuroscience 7k
- Psychiatry and Mental health 4.3k
- Neurology 1.5k
Countries citing papers authored by James C. Gee
This map shows the geographic impact of James C. Gee'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 James C. Gee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James C. Gee more than expected).
Fields of papers citing papers by James C. Gee
This network shows the impact of papers produced by James C. Gee. 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 James C. Gee. The network helps show where James C. Gee may publish in the future.
Co-authors
The 25 scholars most cited alongside James C. Gee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 438 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability Hit paper breakdown → | 2006 | 7175 |
| 2 | N4ITK: Improved N3 Bias Correction Hit paper breakdown → | 2010 | 4541 |
| 3 | Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain Hit paper breakdown → | 2007 | 4206 |
| 4 | A reproducible evaluation of ANTs similarity metric performance in brain image registration Hit paper breakdown → | 2010 | 3561 |
| 5 | Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration Hit paper breakdown → | 2009 | 1847 |
| 6 | A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain Hit paper breakdown → | 2023 | 553 |
| 7 | Large-scale evaluation of ANTs and FreeSurfer cortical thickness measurements Hit paper breakdown → | 2014 | 536 |
| 8 | 2001 | 520 | |
| 9 | The optimal template effect in hippocampus studies of diseased populations Hit paper breakdown → | 2009 | 505 |
| 10 | The Insight ToolKit image registration framework Hit paper breakdown → | 2014 | 491 |
| 11 | An Open Source Multivariate Framework for n-Tissue Segmentation with Evaluation on Public Data Hit paper breakdown → | 2011 | 472 |
| 12 | 2006 | 392 | |
| 13 | 2004 | 375 | |
| 14 | Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge Hit paper breakdown → | 2011 | 371 |
| 15 | 2005 | 366 | |
| 16 | A multimodal cell census and atlas of the mammalian primary motor cortex Hit paper breakdown → | 2021 | 351 |
| 17 | 2010 | 345 | |
| 18 | 2000 | 276 | |
| 19 | 2014 | 237 | |
| 20 | 2007 | 231 |
About James C. Gee
James C. Gee is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience, Psychiatry and Mental health and Health Informatics, having authored 438 papers that have together received 39.7k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (191 papers), Advanced Neuroimaging Techniques and Applications (63 papers), Dementia and Cognitive Impairment Research (34 papers), Functional Brain Connectivity Studies (25 papers), Retinal Imaging and Analysis (18 papers), Neurobiology of Language and Bilingualism (17 papers), Radiomics and Machine Learning in Medical Imaging (15 papers) and Advanced MRI Techniques and Applications (11 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (10k citations), Computer Vision and Pattern Recognition (9.8k citations), Cognitive Neuroscience (7k citations), Psychiatry and Mental health (4.3k citations) and Neurology (1.5k citations). James C. Gee has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Brian Avants, Paul A. Yushkevich, Nicholas James Tustison, Philip A. Cook, Murray Grossman, Charles L. Epstein, Sean Ho, Guido Gerig, Joseph Piven and Rachel G. Smith. Their work appears in journals such as NeuroImage, Academic Radiology, IEEE Transactions on Medical Imaging, Medical Image Analysis and Lecture notes in computer science.
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.