Sumathi Poobal

1.0k total citations · 1 hit paper
11 papers, 735 citations indexed

About

Sumathi Poobal is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Sumathi Poobal has authored 11 papers receiving a total of 735 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Radiology, Nuclear Medicine and Imaging, 3 papers in Artificial Intelligence and 2 papers in Computer Networks and Communications. Recurrent topics in Sumathi Poobal's work include Radiomics and Machine Learning in Medical Imaging (5 papers), AI in cancer detection (3 papers) and COVID-19 diagnosis using AI (3 papers). Sumathi Poobal is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (5 papers), AI in cancer detection (3 papers) and COVID-19 diagnosis using AI (3 papers). Sumathi Poobal collaborates with scholars based in India and Spain. Sumathi Poobal's co-authors include Arun K Mohan, M. Ramya, G. Ravindran and A. Gopal and has published in prestigious journals such as Alexandria Engineering Journal, Cluster Computing and Indian Journal of Science and Technology.

In The Last Decade

Sumathi Poobal

11 papers receiving 692 citations

Hit Papers

Crack detection using image processing: A critical review... 2017 2026 2020 2023 2017 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sumathi Poobal India 6 552 151 82 67 66 11 735
Rahmat Ali Canada 6 415 0.8× 152 1.0× 63 0.8× 78 1.2× 61 0.9× 11 570
Xiaojun Wei China 12 405 0.7× 154 1.0× 77 0.9× 19 0.3× 32 0.5× 44 585
Yizhou Lin China 8 664 1.2× 163 1.1× 42 0.5× 28 0.4× 57 0.9× 16 792
Arun K Mohan India 4 552 1.0× 150 1.0× 79 1.0× 67 1.0× 66 1.0× 8 679
Mohsen Azimi Iran 8 744 1.3× 168 1.1× 28 0.3× 27 0.4× 56 0.8× 19 884
Matthew J. Thurley Sweden 14 110 0.2× 306 2.0× 240 2.9× 67 1.0× 37 0.6× 33 585
Shang Jiang China 10 461 0.8× 109 0.7× 109 1.3× 137 2.0× 50 0.8× 19 565
Takafumi Nishikawa Japan 11 381 0.7× 79 0.5× 72 0.9× 52 0.8× 34 0.5× 34 611
Wenting Luo China 12 212 0.4× 42 0.3× 96 1.2× 35 0.5× 25 0.4× 31 404

Countries citing papers authored by Sumathi Poobal

Since Specialization
Citations

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

Fields of papers citing papers by Sumathi Poobal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sumathi Poobal

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

All Works

11 of 11 papers shown
1.
Poobal, Sumathi, et al.. (2019). Performance evaluation of machine learning techniques in lung cancer classification from PET/CT images. FME Transaction. 47(3). 418–423. 10 indexed citations
2.
Poobal, Sumathi, et al.. (2018). SVM based lung cancer classification using texture and fractal features from PET/CT images. Indian Journal of Public Health Research & Development. 9(10). 1126–1126. 2 indexed citations
3.
Poobal, Sumathi, et al.. (2018). Coded downlink MIMO MC-CDMA system for cognitive radio network: performance results. Cluster Computing. 22(S4). 8371–8378. 3 indexed citations
4.
Poobal, Sumathi, et al.. (2017). Artificial Neural Network Based Lung Cancer Detection for PET/CT Images. Indian Journal of Science and Technology. 10(42). 1–13. 3 indexed citations
5.
Mohan, Arun K & Sumathi Poobal. (2017). Crack detection using image processing: A critical review and analysis. Alexandria Engineering Journal. 57(2). 787–798. 643 indexed citations breakdown →
6.
Poobal, Sumathi, et al.. (2017). Performance of spectrum sharing cognitive radio network based on MIMO MC-CDMA system for medical image transmission. Cluster Computing. 22(S4). 7705–7712. 7 indexed citations
8.
Gopal, A., et al.. (2012). Classification of color objects like fruits using probability density function (PDF). 34. 1–4. 5 indexed citations
9.
Poobal, Sumathi, et al.. (2008). Arriving At An Optimum Value Of Tolerance Factor For Compressing Medical Images. Zenodo (CERN European Organization for Nuclear Research). 11 indexed citations
10.
Poobal, Sumathi & G. Ravindran. (2007). Comparison Of Compression Ability Using Dct And Fractal Technique On Different Imaging Modalities. Zenodo (CERN European Organization for Nuclear Research). 1(12). 1741–1746. 5 indexed citations
11.
Poobal, Sumathi & G. Ravindran. (2006). Analysis on the effect of tolerance criteria in fractal image compression. 119–124. 3 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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