Pavan Annangi

407 total citations
12 papers, 125 citations indexed

About

Pavan Annangi is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Pavan Annangi has authored 12 papers receiving a total of 125 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Radiology, Nuclear Medicine and Imaging, 6 papers in Computer Vision and Pattern Recognition and 4 papers in Artificial Intelligence. Recurrent topics in Pavan Annangi's work include Medical Image Segmentation Techniques (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and COVID-19 diagnosis using AI (3 papers). Pavan Annangi is often cited by papers focused on Medical Image Segmentation Techniques (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and COVID-19 diagnosis using AI (3 papers). Pavan Annangi collaborates with scholars based in India, United States and China. Pavan Annangi's co-authors include Xiwen Sun, Ling Mao, Aamir Raja, Hao Xu, Sheshadri Thiruvenkadam, Xian Tao, Hongqin Xu, Hariharan Ravishankar, Deepa Anand and Sigmund Frigstad and has published in prestigious journals such as Lecture notes in computer science, PubMed and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.

In The Last Decade

Pavan Annangi

12 papers receiving 119 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pavan Annangi India 6 86 43 36 31 17 12 125
Sreenivasa Raju Kalidindi United Kingdom 4 155 1.8× 64 1.5× 58 1.6× 15 0.5× 25 1.5× 4 237
John Ryu United States 5 111 1.3× 26 0.6× 52 1.4× 10 0.3× 40 2.4× 8 213
Hermelinda Abcede United States 3 55 0.6× 23 0.5× 43 1.2× 21 0.7× 27 1.6× 6 212
Ivan A. Blokhin Russia 8 165 1.9× 48 1.1× 42 1.2× 12 0.4× 39 2.3× 44 227
Valeria Chernina Russia 6 136 1.6× 47 1.1× 39 1.1× 11 0.4× 29 1.7× 21 175
Keno März Germany 8 51 0.6× 23 0.5× 34 0.9× 37 1.2× 55 3.2× 15 182
Benjamin Irving United Kingdom 9 130 1.5× 48 1.1× 22 0.6× 43 1.4× 43 2.5× 19 202
Saad Khan United Kingdom 5 157 1.8× 18 0.4× 37 1.0× 22 0.7× 16 0.9× 7 263
Anouk Stein United States 6 186 2.2× 47 1.1× 114 3.2× 49 1.6× 23 1.4× 9 257
Nishanth Arun United States 4 209 2.4× 51 1.2× 125 3.5× 17 0.5× 28 1.6× 7 300

Countries citing papers authored by Pavan Annangi

Since Specialization
Citations

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

Fields of papers citing papers by Pavan Annangi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pavan Annangi

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

All Works

12 of 12 papers shown
1.
Anand, Deepa, et al.. (2022). Benchmarking Self-Supervised Representation Learning from a million Cardiac Ultrasound images. 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 2022. 529–532. 6 indexed citations
2.
Annangi, Pavan, et al.. (2020). AI assisted feedback system for transmit parameter optimization in Cardiac Ultrasound. 1–4. 2 indexed citations
3.
Ravishankar, Hariharan, et al.. (2016). Automated kidney morphology measurements from ultrasound images using texture and edge analysis. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9790. 97901A–97901A. 7 indexed citations
4.
Haque, Hasnine, et al.. (2016). Automated registration of 3D ultrasound and CT/MR images for liver. 1–4. 2 indexed citations
5.
Annangi, Pavan, et al.. (2016). An automated bladder volume measurement algorithm by pixel classification using random forests. PubMed. 2016. 4121–4124. 4 indexed citations
6.
Annangi, Pavan, et al.. (2013). Automated posteriorwall thickness measurement from B-mode ultrasound. 77–80. 2 indexed citations
7.
Pavani, Sri-Kaushik, et al.. (2012). Quality Metric for Parasternal Long Axis B-Mode Echocardiograms. Lecture notes in computer science. 15(Pt 2). 478–485. 5 indexed citations
8.
Liu, Xiaoming, et al.. (2012). Learning-based scan plane identification from fetal head ultrasound images. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8320. 83200A–83200A. 8 indexed citations
9.
Annangi, Pavan, et al.. (2011). Automatic detection and estimation of biparietal diameter from fetal ultrasonography. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7968. 79680I–79680I. 3 indexed citations
10.
Annangi, Pavan, et al.. (2011). Lung partitioning for x-ray CAD applications. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7963. 79631P–79631P. 1 indexed citations
11.
Annangi, Pavan, Sheshadri Thiruvenkadam, Aamir Raja, et al.. (2010). A region based active contour method for x-ray lung segmentation using prior shape and low level features. 892–895. 68 indexed citations
12.

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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