Sundaresan Raman

622 total citations
28 papers, 282 citations indexed

About

Sundaresan Raman is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Sundaresan Raman has authored 28 papers receiving a total of 282 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Radiology, Nuclear Medicine and Imaging, 8 papers in Ophthalmology and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Sundaresan Raman's work include Retinal Imaging and Analysis (8 papers), Retinal Diseases and Treatments (5 papers) and Smart Agriculture and AI (5 papers). Sundaresan Raman is often cited by papers focused on Retinal Imaging and Analysis (8 papers), Retinal Diseases and Treatments (5 papers) and Smart Agriculture and AI (5 papers). Sundaresan Raman collaborates with scholars based in India, United States and United Kingdom. Sundaresan Raman's co-authors include Rephael Wenger, Vinay Chamola, Kim L. Boyer, Gaurang Bansal, Pratik Narang, J Jacob, Sudeep Sarkar, Puneet S. Jolly, Rajiv Raman and Paulo Gotardo and has published in prestigious journals such as PLoS ONE, American Journal of Obstetrics and Gynecology and IEEE Transactions on Medical Imaging.

In The Last Decade

Sundaresan Raman

27 papers receiving 265 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Sundaresan Raman India 10 81 77 51 49 38 28 282
Jupeng Li China 9 78 1.0× 92 1.2× 41 0.8× 6 0.1× 79 2.1× 43 283
Filipe Soares Portugal 9 156 1.9× 83 1.1× 16 0.3× 96 2.0× 55 1.4× 26 269
Kwabena Adu Ghana 9 77 1.0× 77 1.0× 37 0.7× 11 0.2× 110 2.9× 24 287
S. Uma Maheswari India 9 37 0.5× 130 1.7× 33 0.6× 15 0.3× 38 1.0× 34 251
Fengze Liu United States 6 171 2.1× 319 4.1× 6 0.1× 8 0.2× 148 3.9× 10 473
Yunendah Nur Fuadah Indonesia 10 66 0.8× 74 1.0× 10 0.2× 24 0.5× 91 2.4× 36 359
Luis H. S. Vogado Brazil 9 167 2.1× 325 4.2× 67 1.3× 6 0.1× 235 6.2× 22 439
Yehualashet Megersa Ayano Ethiopia 8 50 0.6× 87 1.1× 34 0.7× 3 0.1× 73 1.9× 10 279
J. F. Chang China 3 59 0.7× 53 0.7× 16 0.3× 4 0.1× 83 2.2× 8 206
Ashrani Aizzuddin Abd. Rahni Malaysia 11 121 1.5× 96 1.2× 31 0.6× 63 1.7× 54 320

Countries citing papers authored by Sundaresan Raman

Since Specialization
Citations

This map shows the geographic impact of Sundaresan Raman'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 Sundaresan Raman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sundaresan Raman more than expected).

Fields of papers citing papers by Sundaresan Raman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sundaresan Raman. 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 Sundaresan Raman. The network helps show where Sundaresan Raman may publish in the future.

Co-authorship network of co-authors of Sundaresan Raman

This figure shows the co-authorship network connecting the top 25 collaborators of Sundaresan Raman. A scholar is included among the top collaborators of Sundaresan Raman 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 Sundaresan Raman. Sundaresan Raman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Raman, Sundaresan, Sagnik Sen, Kim Ramasamy, et al.. (2023). Machine Learning-Based Diagnosis and Ranking of Risk Factors for Diabetic Retinopathy in Population-Based Studies from South India. Diagnostics. 13(12). 2084–2084. 5 indexed citations
2.
Surya, Janani, et al.. (2023). Use of artificial intelligence algorithms to predict systemic diseases from retinal images. Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery. 13(5). 3 indexed citations
3.
Raman, Sundaresan, et al.. (2023). An ImageJ macro tool for OCTA-based quantitative analysis of Myopic Choroidal neovascularization. PLoS ONE. 18(4). e0283929–e0283929. 6 indexed citations
4.
Raman, Sundaresan, et al.. (2022). The Need for Artificial Intelligence Based Risk Factor Analysis for Age-Related Macular Degeneration: A Review. Diagnostics. 13(1). 130–130. 9 indexed citations
5.
Raman, Sundaresan, et al.. (2022). LWCNN: a lightweight convolutional neural network for agricultural crop protection. Multimedia Tools and Applications. 81(16). 22323–22334. 7 indexed citations
6.
Natarajan, Radhika, et al.. (2022). Advances in the diagnosis of herpes simplex stromal necrotising keratitis: A feasibility study on deep learning approach. Indian Journal of Ophthalmology. 70(9). 3279–3283. 15 indexed citations
7.
Raman, Sundaresan, Sangeetha Srinivasan, Janani Surya, et al.. (2021). Comparison of Two Ultra-Widefield Cameras With High Image Resolution and Wider View for Identifying Diabetic Retinopathy Lesions. Translational Vision Science & Technology. 10(12). 9–9. 7 indexed citations
8.
Raman, Rajiv, et al.. (2021). Relationship of fractal analysis in retinal microvascularity with demographic and diagnostic parameters. Microvascular Research. 139. 104237–104237. 3 indexed citations
9.
Bansal, Gaurang, et al.. (2020). Deep3DSCan: Deep residual network and morphological descriptor based framework forlung cancer classification and 3D segmentation. IET Image Processing. 14(7). 1240–1247. 51 indexed citations
10.
Raman, Rajiv, et al.. (2020). Comparison of various fractal analysis methods for retinal images. Biomedical Signal Processing and Control. 63. 102245–102245. 7 indexed citations
11.
Goel, Lavika, et al.. (2019). Hybrid computational intelligence algorithms and their applications to detect food quality. Artificial Intelligence Review. 53(2). 1415–1440. 12 indexed citations
12.
Jolly, Puneet S. & Sundaresan Raman. (2016). Analyzing Surface Defects in Apples Using Gabor Features. 178–185. 14 indexed citations
13.
Singh, Shantanu, Sundaresan Raman, Enrico Caserta, et al.. (2010). Analysis of spatial variation of nuclear morphology in tissue microenvironments. 1293–1296. 2 indexed citations
14.
Raman, Sundaresan, et al.. (2009). Distributed visualization framework architecture. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7530. 75300K–75300K. 1 indexed citations
15.
16.
Raman, Sundaresan & Rephael Wenger. (2008). Quality Isosurface Mesh Generation Using an Extended Marching Cubes Lookup Table. Computer Graphics Forum. 27(3). 791–798. 29 indexed citations
17.
Raman, Sundaresan, et al.. (2008). Layers for Effective Volume Rendering. Eurographics. 4 indexed citations
18.
Raman, Sundaresan & J Jacob. (2005). Mydriasis due to Datura inoxia. Emergency Medicine Journal. 22(4). 310–311. 17 indexed citations
19.
Raman, Sundaresan, Sudeep Sarkar, & Kim L. Boyer. (1993). Hypothesizing Structures in Edge-Focused Cerebral Magnetic Resonance Images Using Graph-Theoretic Cycle Enumeration. CVGIP Image Understanding. 57(1). 81–98. 9 indexed citations
20.
Raman, Sundaresan, Sudeep Sarkar, & Kim L. Boyer. (1991). Tissue boundary refinement in magnetic resonance images using contour-based scale space matching. IEEE Transactions on Medical Imaging. 10(2). 109–121. 15 indexed citations

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.

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2026