Reza Azad
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- Advanced Neural Network Applications 7
- Medical Image Segmentation Techniques 6
- Neurology top 5%
- Brain Tumor Detection and Classification 6
- Health Informatics top 5%
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- Radiomics and Machine Learning in Medical Imaging 9
- COVID-19 diagnosis using AI 5
- Artificial Intelligence top 5%
- AI in cancer detection 10
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- Cell Image Analysis Techniques 4
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- Vehicle License Plate Recognition 3
- Co-authors
- Dorit MerhofEhsan Khodapanah AghdamAmirhossein KazerouniMoein HeidariMohsen FayyazIlker HacihalilogluJulien Cohen‐AdadMilad Soltany
- Journals
- Medical Image Analysis (4 papers)Computational Visual Media (2 papers)IEEE Access (1 paper)
- Partner nations
- GermanyIranUnited States
In The Last Decade
Reza Azad
22 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 131
- Computer Vision and Pattern Recognition 635
- Neurology 253
- Health Informatics 32
- Radiology, Nuclear Medicine and Imaging 480
- Artificial Intelligence 441
Countries citing papers authored by Reza Azad
This map shows the geographic impact of Reza Azad'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 Reza Azad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Reza Azad more than expected).
Fields of papers citing papers by Reza Azad
This network shows the impact of papers produced by Reza Azad. 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 Reza Azad. The network helps show where Reza Azad may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Reza Azad, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 0 | |
| 5 | 2025 | 0 | |
| 6 | 2024 | 1 | |
| 7 | Medical Image Segmentation Review: The Success of U-Netbreakdown → | 2024 | 231 |
| 8 | 2024 | 1 | |
| 9 | 2024 | 2 | |
| 10 | 2023 | 45 | |
| 11 | Advances in medical image analysis with vision Transformers: A comprehensive reviewbreakdown → | 2023 | 188 |
| 12 | Diffusion models in medical imaging: A comprehensive surveybreakdown → | 2023 | 290 |
| 13 | 2023 | 3 | |
| 14 | HiFormer: Hierarchical Multi-scale Representations Using Transformers for Medical Image Segmentationbreakdown → | 2023 | 260 |
| 15 | 2023 | 4 | |
| 16 | 2023 | 10 | |
| 17 | 2023 | 39 | |
| 18 | 2022 | 77 | |
| 19 | 2021 | 35 | |
| 20 | A novel and robust method for automatic license plate recognition system based on pattern recognition | 2013 | 20 |
About Reza Azad
Reza Azad is a scholar working on Neurology, Biophysics and Computer Vision and Pattern Recognition, having authored 28 papers that have together received 1.4k indexed citations. Recurring topics across this work include AI in cancer detection (10 papers), Radiomics and Machine Learning in Medical Imaging (9 papers), Advanced Neural Network Applications (7 papers), Brain Tumor Detection and Classification (6 papers), Medical Image Segmentation Techniques (6 papers), COVID-19 diagnosis using AI (5 papers), Cell Image Analysis Techniques (4 papers) and Vehicle License Plate Recognition (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (635 citations), Neurology (253 citations) and Health Informatics (32 citations). Reza Azad has collaborated with scholars based in Germany, Iran and United States. Frequent co-authors include Dorit Merhof, Ehsan Khodapanah Aghdam, Amirhossein Kazerouni, Moein Heidari, Mohsen Fayyaz, Ilker Hacihaliloglu, Julien Cohen‐Adad, Milad Soltany, Amirali Molaei and Sanaz Karimijafarbigloo. Their work appears in journals such as Medical Image Analysis, Computational Visual Media, IEEE Access, Nano Letters and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.