Dibyendu Mukherjee
- Ophthalmology top 2%
- Retinal Diseases and Treatments 5
- Glaucoma and retinal disorders 3
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- Video Surveillance and Tracking Methods 7
- Advanced Vision and Imaging 5
- Video Analysis and Summarization 4
- Image Retrieval and Classification Techniques 4
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- Retinal Imaging and Analysis 5
- Media Technology top 10%
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- Bayesian Methods and Mixture Models 6
- Co-authors
- Q. M. Jonathan WuSina FarsiuThanh Minh NguyenGuanghui WangScott W. CousinsJeremy N. KayMatthew L. O’SullivanJingjing Wang
- Cited by
- OphthalmologyComputer Vision and Pattern RecognitionRadiology, Nuclear Medicine and Imaging
- Journals
- SHILAP Revista de lepidopterología (1 paper)PLoS ONE (1 paper)The Journal of Comparative Neurology (2 papers)
- Partner nations
- CanadaUnited StatesChina
In The Last Decade
Dibyendu Mukherjee
29 papers receiving 535 citations
Peers
Comparison fields: 5 of 81
- Ophthalmology 241
- Computer Vision and Pattern Recognition 174
- Radiology, Nuclear Medicine and Imaging 177
- Media Technology 45
- Neurology 27
Countries citing papers authored by Dibyendu Mukherjee
This map shows the geographic impact of Dibyendu Mukherjee'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 Dibyendu Mukherjee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dibyendu Mukherjee more than expected).
Fields of papers citing papers by Dibyendu Mukherjee
This network shows the impact of papers produced by Dibyendu Mukherjee. 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 Dibyendu Mukherjee. The network helps show where Dibyendu Mukherjee may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Dibyendu Mukherjee, 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 | 8 | |
| 2 | 2025 | 1 | |
| 3 | The RUSH2A study: Baseline microperimetry and SD-OCT measures | 2021 | 0 |
| 4 | Meta-learning approach to automatically register multivendor retinal images | 2020 | 2 |
| 5 | 2019 | 4 | |
| 6 | 2019 | 1 | |
| 7 | 2018 | 81 | |
| 8 | 2018 | 7 | |
| 9 | 2017 | 33 | |
| 10 | A quantitative approach to predict differential effects of anti-VEGF treatment on diffuse and focal leakage in patients with diabetic macular edema. | 2016 | 1 |
| 11 | 2016 | 76 | |
| 12 | 2016 | 19 | |
| 13 | 2016 | 79 | |
| 14 | 2015 | 80 | |
| 15 | 2014 | 27 | |
| 16 | 2014 | 1 | |
| 17 | 2013 | 29 | |
| 18 | 2013 | 2 | |
| 19 | 2012 | 3 | |
| 20 | 2010 | 1 |
About Dibyendu Mukherjee
Dibyendu Mukherjee is a scholar working on Computer Vision and Pattern Recognition, Ophthalmology and Radiology, Nuclear Medicine and Imaging, having authored 30 papers that have together received 550 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (7 papers), Bayesian Methods and Mixture Models (6 papers), Retinal Diseases and Treatments (5 papers), Retinal Imaging and Analysis (5 papers), Advanced Vision and Imaging (5 papers), Video Analysis and Summarization (4 papers), Image Retrieval and Classification Techniques (4 papers) and Glaucoma and retinal disorders (3 papers). The work is most often cited by research in Ophthalmology (241 citations), Computer Vision and Pattern Recognition (174 citations) and Radiology, Nuclear Medicine and Imaging (177 citations). Dibyendu Mukherjee has collaborated with scholars based in Canada, United States and China. Frequent co-authors include Q. M. Jonathan Wu, Sina Farsiu, Thanh Minh Nguyen, Guanghui Wang, Scott W. Cousins, Jeremy N. Kay, Matthew L. O’Sullivan, Jingjing Wang, Eleonora M. Lad and James R. Burke. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and The Journal of Comparative Neurology.
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.