R. Murugan

1.6k total citations
82 papers, 1.0k citations indexed

About

R. Murugan is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Ophthalmology. According to data from OpenAlex, R. Murugan has authored 82 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Radiology, Nuclear Medicine and Imaging, 27 papers in Computer Vision and Pattern Recognition and 22 papers in Ophthalmology. Recurrent topics in R. Murugan's work include Retinal Imaging and Analysis (25 papers), Brain Tumor Detection and Classification (18 papers) and Retinal Diseases and Treatments (13 papers). R. Murugan is often cited by papers focused on Retinal Imaging and Analysis (25 papers), Brain Tumor Detection and Classification (18 papers) and Retinal Diseases and Treatments (13 papers). R. Murugan collaborates with scholars based in India, Australia and South Korea. R. Murugan's co-authors include Tripti Goel, Seyedali Mirjalili, M. Tanveer, Rahul Sharma, Chin‐Teng Lin, Ponnuthurai Nagaratnam Suganthan, Imran Razzak, Badal Soni, Weiping Ding and Arnab Nandi and has published in prestigious journals such as Expert Systems with Applications, Applied Soft Computing and Frontiers in Oncology.

In The Last Decade

R. Murugan

77 papers receiving 964 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
R. Murugan India 19 494 358 293 229 116 82 1.0k
Tripti Goel India 20 469 0.9× 416 1.2× 348 1.2× 302 1.3× 90 0.8× 79 1.1k
Shamik Tiwari India 18 189 0.4× 280 0.8× 315 1.1× 182 0.8× 13 0.1× 74 975
D. Selvathi India 14 184 0.4× 186 0.5× 326 1.1× 174 0.8× 48 0.4× 78 746
Sandeep Kumar Mathivanan India 17 216 0.4× 310 0.9× 244 0.8× 272 1.2× 15 0.1× 99 929
Varun P. Gopi India 20 762 1.5× 186 0.5× 497 1.7× 135 0.6× 480 4.1× 88 1.4k
Loc Tran United States 10 139 0.3× 147 0.4× 161 0.5× 129 0.6× 70 0.6× 37 498
Niloy Sikder Bangladesh 11 366 0.7× 308 0.9× 209 0.7× 39 0.2× 48 0.4× 19 709
Leandro A. Passos Brazil 15 142 0.3× 211 0.6× 229 0.8× 27 0.1× 54 0.5× 48 666
S. Suganyadevi India 9 176 0.4× 173 0.5× 204 0.7× 90 0.4× 20 0.2× 25 585
Muhammad Yaqub China 16 142 0.3× 222 0.6× 165 0.6× 252 1.1× 5 0.0× 46 856

Countries citing papers authored by R. Murugan

Since Specialization
Citations

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

Fields of papers citing papers by R. Murugan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of R. Murugan

This figure shows the co-authorship network connecting the top 25 collaborators of R. Murugan. A scholar is included among the top collaborators of R. Murugan 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 R. Murugan. R. Murugan 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.
Murugan, R., et al.. (2025). A real-time screening system for diabetic retinopathy grading using a novel multi-scale feature extraction through retinal fundus images. Biomedical Signal Processing and Control. 112. 108548–108548.
2.
3.
Goel, Tripti, et al.. (2025). Unveiling Alzheimer’s disease through brain age estimation using multi-kernel regression network and magnetic resonance imaging. Computer Methods and Programs in Biomedicine. 261. 108617–108617. 2 indexed citations
4.
Goel, Tripti, et al.. (2024). An effective diagnosis of schizophrenia using kernel ridge regression-based optimized RVFL classifier. Applied Soft Computing. 157. 111457–111457. 3 indexed citations
5.
Murugan, R., et al.. (2024). Impact of Artificial Intelligence on Cybersecurity. International Journal of Innovative Research in Computer and Communication Engineering. 12(2). 2 indexed citations
6.
Goel, Tripti, et al.. (2024). Brain Age Estimation Using Universum Learning-Based Kernel Random Vector Functional Link Regression Network. Cognitive Computation. 16(6). 3186–3199. 3 indexed citations
7.
Murugan, R., et al.. (2023). Optimal hybrid feature selection technique for diabetic retinopathy grading using fundus images. Sadhana. 48(3). 11 indexed citations
8.
Elkaeed, Eslam B., R. Murugan, Heba Mohammed Refat M. Selim, et al.. (2023). A multi-class deep learning model for early lung cancer and chronic kidney disease detection using computed tomography images. Frontiers in Oncology. 13. 1193746–1193746. 18 indexed citations
9.
Goel, Tripti, et al.. (2023). Association of white matter volume with brain age classification using deep learning network and region wise analysis. Engineering Applications of Artificial Intelligence. 125. 106596–106596. 11 indexed citations
10.
Murugan, R., Sanjay Sinha, & Savita Savita. (2023). Wideband Technology Design with the Novel Based Technogy : An Antenna Systems. 1475–1479. 1 indexed citations
11.
Murugan, R., et al.. (2022). Diagnosis of heart disease using oversampling methods and decision tree classifier in cardiology. Research on Biomedical Engineering. 39(1). 99–113. 9 indexed citations
12.
Murugan, R., et al.. (2022). Ada-GridRF: A Fast and Automated Adaptive Boost Based Grid Search Optimized Random Forest Ensemble model for Lung Cancer Detection. Physical and Engineering Sciences in Medicine. 45(3). 981–994. 12 indexed citations
13.
Murugan, R., et al.. (2022). Fast and Robust Exudate Detection in Retinal Fundus Images Using Extreme Learning Machine Autoencoders and Modified KAZE Features. Journal of Digital Imaging. 35(3). 496–513. 24 indexed citations
14.
15.
Murugan, R., et al.. (2021). WOANet: Whale optimized deep neural network for the classification of COVID-19 from radiography images. Journal of Applied Biomedicine. 41(4). 1702–1718. 19 indexed citations
16.
Murugan, R., et al.. (2021). A novel four-step feature selection technique for diabetic retinopathy grading. Physical and Engineering Sciences in Medicine. 44(4). 1351–1366. 29 indexed citations
17.
Goel, Tripti, et al.. (2021). Multi-COVID-Net: Multi-objective optimized network for COVID-19 diagnosis from chest X-ray images. Applied Soft Computing. 115. 108250–108250. 28 indexed citations
18.
Goel, Tripti, et al.. (2020). OptCoNet: an optimized convolutional neural network for an automatic diagnosis of COVID-19. Applied Intelligence. 51(3). 1351–1366. 123 indexed citations
19.
Murugan, R., et al.. (2018). An Automatic Localization of Optic Disc in Low Resolution Retinal Images by Modified Directional Matched Filter. The International Arab Journal of Information Technology. 16(1). 1–7. 14 indexed citations
20.
Murugan, R., et al.. (2012). Segmentation algorithms for automatic detection of retinal images using CVIP tools. 2. 229–233. 1 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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