S.C. Cheran

1.7k citations
12 papers · 258 · h-index 9

Impact in

Papers in

S.C. Cheran

12 papers receiving 223 citations

Peers

S.C. Cheran
Comparison fields: 5 of 41
  • Radiology, Nuclear Medicine and Imaging 167
  • Computer Vision and Pattern Recognition 94
  • Artificial Intelligence 143
  • Pulmonary and Respiratory Medicine 102
  • Neurology 21
Replace R. Magro with:
R. Magro Italy
E. López Torres Italy
Homero Schiabel Brazil
Lilla Boroczky United States
Karthikeyan Ganesan Singapore
K. Thomas Abraham Singapore
Sheila Timp Netherlands
Celia Varela Netherlands
Georg Wimmer Austria
Giang Son Tran Vietnam
S.C. Cheran relative to R. Magro Italy R. Magro's profile →
Citations per field
00.5×1.5×
R. Magro · 1×
Citations per year

Countries citing papers authored by S.C. Cheran

Since Specialization
Citations

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

Fields of papers citing papers by S.C. Cheran

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S.C. Cheran. 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 S.C. Cheran. The network helps show where S.C. Cheran may publish in the future.

Co-authors

The 25 scholars most cited alongside S.C. Cheran, 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 S.C. Cheran Line = papers co-authored together S.C. Cheran links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 200788
2 200688
3 200514
4 200513
5 200512
6 20069
7 20059
8
Early diagnosis of Alzheimer's disease using a grid implementation of statistical parametric mapping analysis.
20069
9 20058
10 20074
11 20053
12
Mass lesion detection in mammographic images using Haralik textural features
20061

About S.C. Cheran

S.C. Cheran is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine and Computer Networks and Communications, having authored 12 papers that have together received 258 indexed citations. Recurring topics across this work include AI in cancer detection (7 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Medical Imaging Techniques and Applications (4 papers), Medical Image Segmentation Techniques (4 papers), Lung Cancer Diagnosis and Treatment (3 papers), Infrared Thermography in Medicine (2 papers), Dental Radiography and Imaging (1 paper) and Computational Physics and Python Applications (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (167 citations), Computer Vision and Pattern Recognition (94 citations), Artificial Intelligence (143 citations), Pulmonary and Respiratory Medicine (102 citations) and Neurology (21 citations). S.C. Cheran has collaborated with scholars based in Italy and Cuba. Frequent co-authors include Sabina Tangaro, Donato Cascio, Francesco De Carlo, R. Bellotti, Alessandra Retico, G. Gargano, P. Cerello, P. Oliva, Giorgio De Nunzio and Giovanni Luca Masala. Their work appears in journals such as Medical Physics, Physica Medica, IEEE Transactions on Nuclear Science, Kent Academic Repository (University of Kent) and IEEE Symposium Conference Record Nuclear Science 2004..

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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