Awais Mansoor
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- Radiomics and Machine Learning in Medical Imaging 4
- COVID-19 diagnosis using AI 4
- Medical Imaging Techniques and Applications 2
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- Medical Image Segmentation Techniques 2
- Image and Signal Denoising Methods 1
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- Lung Cancer Diagnosis and Treatment 4
- Radiation top 10%
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- Oral microbiology and periodontitis research 1
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- Stroke Rehabilitation and Recovery 1
- Co-authors
- Ulaş BağcıDaniel J. MolluraZiyue XuBrent FosterJayaram K. UdupaGeorgios Z. PapadakisLes FolioKenneth N. Olivier
- Cited by
- Radiology, Nuclear Medicine and ImagingComputer Vision and Pattern RecognitionPulmonary and Respiratory Medicine
- Journals
- IEEE Transactions on Medical Imaging (1 paper)Medical Physics (1 paper)Radiographics (1 paper)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Awais Mansoor
10 papers receiving 611 citations
Peers
Comparison fields: 5 of 89
- Radiology, Nuclear Medicine and Imaging 468
- Computer Vision and Pattern Recognition 175
- Pulmonary and Respiratory Medicine 226
- Radiation 37
- Health Informatics 5
Countries citing papers authored by Awais Mansoor
This map shows the geographic impact of Awais Mansoor'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 Awais Mansoor with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Awais Mansoor more than expected).
Fields of papers citing papers by Awais Mansoor
This network shows the impact of papers produced by Awais Mansoor. 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 Awais Mansoor. The network helps show where Awais Mansoor may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Awais Mansoor, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 1 | |
| 2 | 2015 | 30 | |
| 3 | 2015 | 12 | |
| 4 | 2015 | 170 | |
| 5 | 2014 | 259 | |
| 6 | 2014 | 118 | |
| 7 | 2014 | 14 | |
| 8 | 2013 | 12 | |
| 9 | Accurate quantification of brown adipose tissue through PET-guided CT image segmentation | 2013 | 2 |
| 10 | 2009 | 11 |
About Awais Mansoor
Awais Mansoor is a scholar working on Radiology, Nuclear Medicine and Imaging, Periodontics and Biophysics, having authored 10 papers that have together received 629 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (4 papers), Lung Cancer Diagnosis and Treatment (4 papers), COVID-19 diagnosis using AI (4 papers), Medical Imaging Techniques and Applications (2 papers), Medical Image Segmentation Techniques (2 papers), Image and Signal Denoising Methods (1 paper), Oral microbiology and periodontitis research (1 paper) and Stroke Rehabilitation and Recovery (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (468 citations), Computer Vision and Pattern Recognition (175 citations) and Pulmonary and Respiratory Medicine (226 citations). Awais Mansoor has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Ulaş Bağcı, Daniel J. Mollura, Ziyue Xu, Brent Foster, Jayaram K. Udupa, Georgios Z. Papadakis, Les Folio, Kenneth N. Olivier, Jason M. Elinoff and Anthony F. Suffredini. Their work appears in journals such as IEEE Transactions on Medical Imaging, Medical Physics and Radiographics.
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.