Reza Azad
- Computer Vision and Pattern Recognition top 2%
- Radiology, Nuclear Medicine and Imaging top 5%
- Artificial Intelligence top 5%
- Neurology top 5%
- Biomedical Engineering
- Co-authors
- Dorit MerhofEhsan Khodapanah AghdamAmirhossein KazerouniMoein HeidariMohsen FayyazIlker HacihalilogluJulien Cohen‐AdadMilad Soltany
- Topics
- AI in cancer detection (10 papers)Radiomics and Machine Learning in Medical Imaging (9 papers)Advanced Neural Network Applications (7 papers)
- 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
- Radiology, Nuclear Medicine and Imaging 480
- Artificial Intelligence 441
- Neurology 253
- Biomedical Engineering 195
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 of co-authors of Reza Azad
This figure shows the co-authorship network connecting the top 25 collaborators of Reza Azad. A scholar is included among the top collaborators of Reza Azad based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Reza Azad. Reza Azad is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | Medical Image Segmentation Review: The Success of U-Netbreakdown → | 231 |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 45 | |
| 11 | Advances in medical image analysis with vision Transformers: A comprehensive reviewbreakdown → | 188 |
| 12 | Diffusion models in medical imaging: A comprehensive surveybreakdown → | 290 |
| 13 | 3 | |
| 14 | HiFormer: Hierarchical Multi-scale Representations Using Transformers for Medical Image Segmentationbreakdown → | 260 |
| 15 | 4 | |
| 16 | 10 | |
| 17 | 39 | |
| 18 | 77 | |
| 19 | 35 | |
| 20 | A novel and robust method for automatic license plate recognition system based on pattern recognition | 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) and Advanced Neural Network Applications (7 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 Nano Letters, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Access.
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.