John Heine
Impact in
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- Digital Radiography and Breast Imaging
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- Medical Imaging Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
Papers in
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- Digital Radiography and Breast Imaging 35
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- AI in cancer detection 19
- Co-authors
- Robert P. Velthuizen (5 shared papers)Laurence P. Clarke (6 shared papers)M.L. Silbiger (1 shared paper)Robert W. Thatcher (1 shared paper)Mohan Vaidyanathan (1 shared paper)Lawrence Hall (1 shared paper)Marc A. Camacho (1 shared paper)Poonam Malhotra (2 shared papers)
- Journals
- Medical Physics (11 papers)Academic Radiology (7 papers)Cancer Epidemiology Biomarkers & Prevention (6 papers)BioMedical Engineering OnLine (4 papers)Breast Cancer Research (3 papers)
- Partner nations
- United StatesChinaJapan
In The Last Decade
John Heine
70 papers receiving 1.9k citations
John Heine's Hit Papers
Peers
Comparison fields: 5 of 122
- Pulmonary and Respiratory Medicine 897
- Radiology, Nuclear Medicine and Imaging 520
- Computer Vision and Pattern Recognition 448
- Artificial Intelligence 565
- Neurology 128
Countries citing papers authored by John Heine
This map shows the geographic impact of John Heine'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 John Heine with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Heine more than expected).
Fields of papers citing papers by John Heine
This network shows the impact of papers produced by John Heine. 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 John Heine. The network helps show where John Heine may publish in the future.
Co-authors
The 25 scholars most cited alongside John Heine, 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 76 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | MRI segmentation: Methods and applications Hit paper breakdown → | 1995 | 514 |
| 2 | 2015 | 143 | |
| 3 | 2009 | 111 | |
| 4 | 1999 | 69 | |
| 5 | 2002 | 67 | |
| 6 | 2012 | 65 | |
| 7 | 2017 | 62 | |
| 8 | 2008 | 54 | |
| 9 | 2002 | 47 | |
| 10 | 2015 | 44 | |
| 11 | 1997 | 44 | |
| 12 | 2014 | 42 | |
| 13 | 2002 | 40 | |
| 14 | 2017 | 38 | |
| 15 | 2000 | 38 | |
| 16 | 2012 | 37 | |
| 17 | 2011 | 33 | |
| 18 | 1998 | 30 | |
| 19 | 2013 | 30 | |
| 20 | 2010 | 29 |
About John Heine
John Heine is a scholar working on Pulmonary and Respiratory Medicine, Artificial Intelligence, Oncology, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 76 papers that have together received 2.0k indexed citations. Recurring topics across this work include Digital Radiography and Breast Imaging (35 papers), AI in cancer detection (19 papers), Global Cancer Incidence and Screening (7 papers), Gene expression and cancer classification (6 papers), Medical Imaging Techniques and Applications (6 papers), Image and Signal Denoising Methods (6 papers), Cancer Risks and Factors (5 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). The work is most often cited by research in Pulmonary and Respiratory Medicine (897 citations), Radiology, Nuclear Medicine and Imaging (520 citations), Computer Vision and Pattern Recognition (448 citations), Artificial Intelligence (565 citations) and Neurology (128 citations). John Heine has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Robert P. Velthuizen, Laurence P. Clarke, M.L. Silbiger, Robert W. Thatcher, Mohan Vaidyanathan, Lawrence Hall, Marc A. Camacho, Poonam Malhotra, Celine M. Vachon and Christopher G. Scott. Their work appears in journals such as Medical Physics, Academic Radiology, Cancer Epidemiology Biomarkers & Prevention, BioMedical Engineering OnLine and Breast Cancer Research.
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.