A. Jonathan McLeod

652 citations
37 papers · 493 · h-index 12

Impact in

Papers in

A. Jonathan McLeod

35 papers receiving 467 citations

Peers

A. Jonathan McLeod
Comparison fields: 5 of 81
  • Gastroenterology 39
  • Computer Vision and Pattern Recognition 135
  • Radiology, Nuclear Medicine and Imaging 81
  • Health Informatics 5
  • Pulmonary and Respiratory Medicine 99
Replace Hiroshi Natori with:
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Gabriel Hanssen Kiss Norway
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Ingmar Wegner Germany
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Citations per field
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Citations per year

Countries citing papers authored by A. Jonathan McLeod

Since Specialization
Citations

This map shows the geographic impact of A. Jonathan McLeod'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 A. Jonathan McLeod with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. Jonathan McLeod more than expected).

Fields of papers citing papers by A. Jonathan McLeod

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by A. Jonathan McLeod. 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 A. Jonathan McLeod. The network helps show where A. Jonathan McLeod may publish in the future.

Co-authors

The 25 scholars most cited alongside A. Jonathan McLeod, 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 A. Jonathan McLeod Line = papers co-authored together A. Jonathan McLeod links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1984108
2 201836
3 201736
4 201432
5 201530
6 202028
7 201625
8 201524
9 201323
10 201517
11 201417
12 200016
13 198412
14 20159
15 20148
16 20128
17
MAP-based Brain Tissue Segmentation using Manifold Learning and Hierarchical Max-Flow regularization
20147
18 20176
19 20156
20 20165

About A. Jonathan McLeod

A. Jonathan McLeod is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine, Surgery and Biomedical Engineering, having authored 37 papers that have together received 493 indexed citations. Recurring topics across this work include Cardiac Valve Diseases and Treatments (8 papers), Medical Image Segmentation Techniques (6 papers), Advanced Vision and Imaging (5 papers), Ultrasound Imaging and Elastography (5 papers), Surgical Simulation and Training (4 papers), Advanced MRI Techniques and Applications (4 papers), Cardiac and Coronary Surgery Techniques (3 papers) and Image Enhancement Techniques (3 papers). The work is most often cited by research in Gastroenterology (39 citations), Computer Vision and Pattern Recognition (135 citations), Radiology, Nuclear Medicine and Imaging (81 citations), Health Informatics (5 citations) and Pulmonary and Respiratory Medicine (99 citations). A. Jonathan McLeod has collaborated with scholars based in Canada, United States and China. Frequent co-authors include Terry M. Peters, Ali Shirkhoda, Jesús Zornoza, John S. H. Baxter, Elvis C. S. Chen, Xióngbiāo Luó, Stephen E. Pautler, Martin Rajchl, John T. Moore and Christopher M. Schlachta. Their work appears in journals such as International Journal of Computer Assisted Radiology and Surgery, Radiology, Magnetic Resonance Imaging, Medical Image Analysis and Journal of Telemedicine and Telecare.

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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