T. Kalaiselvi

798 citations
49 papers · 518 indexed · h-index 12

Impact in

Papers in

    • Medical Image Segmentation Techniques 31
    • Advanced Neural Network Applications 9
    • Image Retrieval and Classification Techniques 8
    • Image and Signal Denoising Methods 3
    • Brain Tumor Detection and Classification 32

T. Kalaiselvi

47 papers receiving 479 citations

Peers

T. Kalaiselvi
Comparison fields: 5 of 78
  • Neurology 316
  • Computer Vision and Pattern Recognition 366
  • Health Informatics 13
  • Urban Studies 31
  • Media Technology 43
Replace P. Sriramakrishnan with:
P. Sriramakrishnan India
Abdel-Badeeh M. Salem Egypt
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Citations per field
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Citations per year

Countries citing papers authored by T. Kalaiselvi

Since Specialization
Citations

This map shows the geographic impact of T. Kalaiselvi'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 T. Kalaiselvi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Kalaiselvi more than expected).

Fields of papers citing papers by T. Kalaiselvi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 11 scholars most cited alongside T. Kalaiselvi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with T. Kalaiselvi Line = papers co-authored together T. Kalaiselvi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201169
2 201060
3 201752
4 201938
5 201534
6 201921
7 202020
8 201120
9 202114
10 202212
11 201911
12 201911
13 201511
14
A Comparative Study of Segmentation Techniques used for MR Brain Images.
200910
15 202210
16 20189
17 20169
18 20168
19 20178
20
A Novel Technique for Finding the Boundary between the Cerebral Hemispheres from MR Axial Head Scans.
20097

About T. Kalaiselvi

T. Kalaiselvi is a scholar working on Computer Vision and Pattern Recognition, Neurology, Artificial Intelligence, Urban Studies and Radiology, Nuclear Medicine and Imaging, having authored 49 papers that have together received 518 indexed citations. Recurring topics across this work include Brain Tumor Detection and Classification (32 papers), Medical Image Segmentation Techniques (31 papers), Advanced Neural Network Applications (9 papers), Image Retrieval and Classification Techniques (8 papers), Advanced Computing and Algorithms (6 papers), AI in cancer detection (4 papers), Multi-Criteria Decision Making (3 papers) and Image and Signal Denoising Methods (3 papers). The work is most often cited by research in Neurology (316 citations), Computer Vision and Pattern Recognition (366 citations), Health Informatics (13 citations), Urban Studies (31 citations) and Media Technology (43 citations). T. Kalaiselvi has collaborated with scholars based in India and United States. Frequent co-authors include K. Somasundaram, P. Sriramakrishnan, S. Padmapriya, Rajeswaran Rangasami, P. Balasubramaniam, N. Shanthi, S. Vijayalakshmi, S. Ramkumar, Seepana Praveenkumar and R. Krishnamoorthy. Their work appears in journals such as International Journal of Imaging Systems and Technology, Computers in Biology and Medicine, Journal of Digital Imaging, International Journal of Computational Methods and Journal of Applied Biomedicine.

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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