Kamlesh Pawar

649 citations
16 papers · 416 indexed · h-index 9
Topics
Advanced MRI Techniques and Applications (12 papers)Medical Imaging Techniques and Applications (9 papers)Radiomics and Machine Learning in Medical Imaging (3 papers)
Partner nations
AustraliaIndiaGermany

In The Last Decade

Kamlesh Pawar

15 papers receiving 413 citations

Peers

Kamlesh Pawar
Comparison fields: 5 of 124
  • Radiology, Nuclear Medicine and Imaging 181
  • Biomedical Engineering 72
  • Computer Vision and Pattern Recognition 69
  • Molecular Biology 38
  • Plant Science 37
Replace Lijun Shen with:
Lijun Shen China
Fares Bougourzi France
Yuki Suzuki Japan
Jun Lyu China
Axel Saalbach Germany
Ghulam Gilanie Pakistan
Mohammadreza Soltaninejad United Kingdom
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Kamlesh Pawar relative to Lijun Shen China Lijun Shen's profile →
Citations per field
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Lijun Shen · 1×
Citations per year

Countries citing papers authored by Kamlesh Pawar

Since Specialization
Citations

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

Fields of papers citing papers by Kamlesh Pawar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kamlesh Pawar

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

All Works

16 of 16 papers shown
#WorkIndexed citations
1 0
2 15
3 98
4 8
5 10
6 13
7 32
8 7
9
Enforcing Structural Similarity in Deep Learning MR Image Reconstruction
1
10 39
11 11
12
ReconNet: A Deep Learning Framework for Transforming MR Image Reconstruction to Pixel Classification
1
13 178
14 1
15
(RATE) Rapid MRI Acquisition Using Tailored Signal Excitation Modules: A K-Space Aliasing Method to Accelerate MRI Scans
1
16
Simultaneous Image and K-space Domain Aliasing for Accelerating Dynamic MRI Scans
1

About Kamlesh Pawar

Kamlesh Pawar is a scholar working on Radiology, Nuclear Medicine and Imaging, Radiation and Computer Vision and Pattern Recognition, having authored 16 papers that have together received 416 indexed citations. Recurring topics across this work include Advanced MRI Techniques and Applications (12 papers), Medical Imaging Techniques and Applications (9 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (181 citations), Health Informatics (8 citations) and Computer Vision and Pattern Recognition (69 citations). Kamlesh Pawar has collaborated with scholars based in Australia, India and Germany. Frequent co-authors include Gary F. Egan, Jingxin Zhang, Zhaolin Chen, Shenjun Zhong, N. Jon Shah, Alexandra Carey, Mehrtash Harandi, Shenpeng Li, Ruth Oliver and M. Cholewa. Their work appears in journals such as PLoS ONE, IEEE Access and European Journal of Nuclear Medicine and Molecular Imaging.

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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