James C. Gee

54.0k citations
370 papers · 33.1k indexed · 9 hit papers · h-index 64

James C. Gee

360 papers receiving 32.5k citations

Hit Papers

Social Linguistics and Literacies31320062026201220192.0k4.0k6.0k

Peers

James C. Gee
Comparison fields: 5 of 217
  • Radiology, Nuclear Medicine and Imaging 14.3k
  • Computational Mathematics 305
  • Cognitive Neuroscience 9.3k
  • Neurology 2.5k
  • Computer Vision and Pattern Recognition 5.3k
Replace Ron Kikinis with:
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Roger P. Woods United States
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Paul A. Yushkevich United States
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Citations per field
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Citations per year

Countries citing papers authored by James C. Gee

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network

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.

Border = papers with James C. Gee Line = papers co-authored together James C. Gee links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20252
2 20252
3 20245
4 202415
5 202325
6 20232
7 20227
8 20226
9 20227
10 202111
11 202087
12 20206
13 20191
14 201956
15 201840
16 201713
17
Automated Quantification of Morphologic Features and Vasculature of Choroid on Enhanced Depth Imaging Optical Coherence Tomography (EDI-OCT)
20161
18
Multi-modal Automatic Montaging of Adaptive Optics Retinal Images
201620
19 201522
20 200796

About James C. Gee

James C. Gee is a scholar working on Computational Mathematics, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 370 papers that have together received 33.1k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (99 papers), Advanced Neuroimaging Techniques and Applications (90 papers), Functional Brain Connectivity Studies (51 papers), Advanced MRI Techniques and Applications (39 papers), Radiomics and Machine Learning in Medical Imaging (30 papers), Medical Imaging Techniques and Applications (27 papers), Fetal and Pediatric Neurological Disorders (26 papers) and Dementia and Cognitive Impairment Research (21 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (14.3k citations), Computational Mathematics (305 citations) and Cognitive Neuroscience (9.3k 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 J. Tustison, Philip A. Cook, Sean Ho, Joseph Piven, Guido Gerig, Rachel G. Smith, Heather C. Hazlett and Charles L. Epstein. Their work appears in journals such as NeuroImage, Academic Radiology, Medical Image Analysis, IEEE Transactions on Medical Imaging and NeuroImage Clinical.

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.

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