Mohammad Hamghalam
Impact in
- Neurology top 10%
- Brain Tumor Detection and Classification
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- Advanced Neural Network Applications
- Digital Imaging for Blood Diseases
- Medical Image Segmentation Techniques
- Generative Adversarial Networks and Image Synthesis
Papers in
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- Medical Image Segmentation Techniques 7
- Advanced Neural Network Applications 7
- Digital Imaging for Blood Diseases 2
- Generative Adversarial Networks and Image Synthesis 2
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- Brain Tumor Detection and Classification 7
- Co-authors
- Baiying Lei (3 shared papers)Tianfu Wang (2 shared papers)Amber L. Simpson (5 shared papers)Ahmad Ayatollahi (2 shared papers)Sattar Mirzakuchaki (1 shared paper)Hamid Ghadiri (1 shared paper)Jing Qin (1 shared paper)Ali Babaei Jandaghi (2 shared papers)
In The Last Decade
Mohammad Hamghalam
16 papers receiving 183 citations
Peers
Comparison fields: 5 of 49
- Neurology 68
- Computer Vision and Pattern Recognition 137
- Biophysics 21
- Media Technology 23
- Radiology, Nuclear Medicine and Imaging 56
Countries citing papers authored by Mohammad Hamghalam
This map shows the geographic impact of Mohammad Hamghalam'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 Mohammad Hamghalam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammad Hamghalam more than expected).
Fields of papers citing papers by Mohammad Hamghalam
This network shows the impact of papers produced by Mohammad Hamghalam. 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 Mohammad Hamghalam. The network helps show where Mohammad Hamghalam may publish in the future.
Co-authors
The 24 scholars most cited alongside Mohammad Hamghalam, 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 | 2020 | 30 | |
| 2 | 2019 | 23 | |
| 3 | 2022 | 21 | |
| 4 | 2009 | 19 | |
| 5 | 2024 | 18 | |
| 6 | 2009 | 17 | |
| 7 | 2021 | 15 | |
| 8 | 2020 | 11 | |
| 9 | 2020 | 9 | |
| 10 | 2019 | 8 | |
| 11 | 2024 | 6 | |
| 12 | 2017 | 4 | |
| 13 | 2023 | 3 | |
| 14 | 2018 | 2 | |
| 15 | 2025 | 1 | |
| 16 | 2024 | 1 | |
| 17 | 2025 | 0 |
About Mohammad Hamghalam
Mohammad Hamghalam is a scholar working on Computer Vision and Pattern Recognition, Neurology, Artificial Intelligence, Surgery and Radiology, Nuclear Medicine and Imaging, having authored 17 papers that have together received 188 indexed citations. Recurring topics across this work include Brain Tumor Detection and Classification (7 papers), Medical Image Segmentation Techniques (7 papers), Advanced Neural Network Applications (7 papers), AI in cancer detection (3 papers), Digital Imaging for Blood Diseases (2 papers), Abdominal Trauma and Injuries (2 papers), Cell Image Analysis Techniques (2 papers) and Generative Adversarial Networks and Image Synthesis (2 papers). The work is most often cited by research in Neurology (68 citations), Computer Vision and Pattern Recognition (137 citations), Biophysics (21 citations), Media Technology (23 citations) and Radiology, Nuclear Medicine and Imaging (56 citations). Mohammad Hamghalam has collaborated with scholars based in Iran, Canada and China. Frequent co-authors include Baiying Lei, Tianfu Wang, Amber L. Simpson, Ahmad Ayatollahi, Sattar Mirzakuchaki, Hamid Ghadiri, Jing Qin, Ali Babaei Jandaghi, Robert B. Moreland and David Gómez. Their work appears in journals such as Multimedia Tools and Applications, Computers in Biology and Medicine, Neural Networks, BioMedical Engineering OnLine and Canadian Association of Radiologists Journal.
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.