Vikram Chalana

1.8k citations
27 papers · 1.4k indexed · 1 hit paper · h-index 11

Vikram Chalana

27 papers receiving 1.3k citations

Hit Papers

Engineering and Algorithm Design for an Image Processing ...4872002202620102018100200300400

Peers

Vikram Chalana
Comparison fields: 5 of 127
  • Computer Vision and Pattern Recognition 670
  • Radiology, Nuclear Medicine and Imaging 581
  • Biophysics 78
  • Radiation 108
  • Media Technology 59
Replace Isabelle E. Magnin with:
Isabelle E. Magnin France
B. Likar Slovenia
F. Pernuš Slovenia
Dewey Odhner United States
Philipp G. Batchelor United Kingdom
Thomas Koller Switzerland
Aymeric Perchant France
Celina Imielińska United States
Régis Vaillant France
Djamal Boukerroui France
Vikram Chalana relative to Isabelle E. Magnin France Isabelle E. Magnin's profile →
Citations per field
00.5×1.5×2.4×
Isabelle E. Magnin · 1×
Citations per year

Countries citing papers authored by Vikram Chalana

Since Specialization
Citations

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

Fields of papers citing papers by Vikram Chalana

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 200315
2 20034
3 20022
4 200114
5 20002
6 19991
7 199832
8 199816
9 19984
10 199844
11 199741
12 1997412
13 19972
14 199650
15 19966
16 1996222
17
Deformable models for segmentation of medical ultrasound images
19962
18 19961
19 19956
20 19944

About Vikram Chalana

Vikram Chalana is a scholar working on Computer Vision and Pattern Recognition, Biophysics, Radiology, Nuclear Medicine and Imaging, Analytical Chemistry and Urology, having authored 27 papers that have together received 1.4k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (14 papers), Fetal and Pediatric Neurological Disorders (3 papers), Prostate Cancer Diagnosis and Treatment (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), AI in cancer detection (2 papers), Image and Object Detection Techniques (2 papers), Spectroscopy and Chemometric Analyses (2 papers) and Pancreatic and Hepatic Oncology Research (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (670 citations), Radiology, Nuclear Medicine and Imaging (581 citations), Biophysics (78 citations), Radiation (108 citations) and Media Technology (59 citations). Vikram Chalana has collaborated with scholars based in United States, Netherlands and Israel. Frequent co-authors include Y. Kim, David R. Haynor, Yongmin Kim, William E. Lorensen, Will Schroeder, Stephen Aylward, Dimitris Metaxas, Ross Whitaker, Michael Ackerman and Terry S. Yoo. Their work appears in journals such as IEEE Transactions on Medical Imaging, International Journal of Imaging Systems and Technology, Ultrasonic Imaging, Drug Discovery Today and Academic Radiology.

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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