Abhirup Banerjee

1.9k total citations
51 papers, 473 citations indexed

About

Abhirup Banerjee is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Abhirup Banerjee has authored 51 papers receiving a total of 473 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Cardiology and Cardiovascular Medicine, 20 papers in Radiology, Nuclear Medicine and Imaging and 19 papers in Computer Vision and Pattern Recognition. Recurrent topics in Abhirup Banerjee's work include Medical Image Segmentation Techniques (17 papers), 3D Shape Modeling and Analysis (8 papers) and Cardiac Imaging and Diagnostics (7 papers). Abhirup Banerjee is often cited by papers focused on Medical Image Segmentation Techniques (17 papers), 3D Shape Modeling and Analysis (8 papers) and Cardiac Imaging and Diagnostics (7 papers). Abhirup Banerjee collaborates with scholars based in United Kingdom, India and Australia. Abhirup Banerjee's co-authors include Pradipta Maji, Vicente Grau, Marcel Beetz, Louise S. Mackenzie, Bart Vorselaars, Surajit Ray, Michail Mamalakis, Mark Baker, Robin P. Choudhury and Ernesto Zacur and has published in prestigious journals such as Scientific Reports, International Journal of Molecular Sciences and IEEE Transactions on Image Processing.

In The Last Decade

Abhirup Banerjee

44 papers receiving 463 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Abhirup Banerjee United Kingdom 12 208 139 110 95 57 51 473
Ali M. Hasan Iraq 11 204 1.0× 256 1.8× 183 1.7× 31 0.3× 13 0.2× 33 515
Qing Cao China 8 116 0.6× 105 0.8× 42 0.4× 51 0.5× 11 0.2× 22 310
Saša Grbić United States 16 496 2.4× 183 1.3× 174 1.6× 124 1.3× 27 0.5× 31 857
Jiamin Liu China 10 202 1.0× 35 0.3× 41 0.4× 53 0.6× 12 0.2× 27 568
Mousumi Bhaduri Canada 12 158 0.8× 123 0.9× 75 0.7× 94 1.0× 4 0.1× 20 381
John Guttag United States 5 132 0.6× 168 1.2× 71 0.6× 10 0.1× 29 0.5× 12 370
Chirag Agarwal United States 11 65 0.3× 68 0.5× 118 1.1× 38 0.4× 88 1.5× 45 424
Amine Amyar United States 9 508 2.4× 80 0.6× 259 2.4× 39 0.4× 9 0.2× 22 592
Zhanhao Mo China 13 436 2.1× 103 0.7× 271 2.5× 30 0.3× 41 0.7× 28 805
Yongjian Nian China 13 92 0.4× 105 0.8× 74 0.7× 89 0.9× 3 0.1× 56 562

Countries citing papers authored by Abhirup Banerjee

Since Specialization
Citations

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

Fields of papers citing papers by Abhirup Banerjee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Abhirup Banerjee

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

All Works

20 of 20 papers shown
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Sharp, Alexander, Michael T. Pope, Milena Leo, et al.. (2025). Diagnostic performance of single-lead electrocardiograms from a smartwatch and a smartring for cardiac arrhythmia detection. Heart Rhythm O2. 6(6). 808–817. 1 indexed citations
4.
Li, Lei, et al.. (2025). Large Language Model-Informed ECG Dual Attention Network for Heart Failure Risk Prediction. IEEE Transactions on Big Data. 11(3). 948–960. 4 indexed citations
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Pope, Michael T., Milena Leo, Alexander Sharp, et al.. (2024). “Real‐world” performance of the Confirm Rx™ SharpSense AF detection algorithm: UK Confirm Rx study. Journal of Arrhythmia. 40(5). 1093–1101. 1 indexed citations
7.
Leo, Milena, Abhirup Banerjee, Michael T. Pope, et al.. (2024). Role of impedance drop and lesion size index (LSI) to guide catheter ablation for atrial fibrillation. Pacing and Clinical Electrophysiology. 47(10). 1404–1411. 1 indexed citations
8.
Shanmuganathan, Mayooran, Matthew K. Burrage, Alessandra Borlotti, et al.. (2024). Cardiovascular Magnetic Resonance Before Invasive Coronary Angiography in Suspected Non–ST-Segment Elevation Myocardial Infarction. JACC. Cardiovascular imaging. 17(9). 1044–1058. 3 indexed citations
9.
Mamalakis, Michail, Abhirup Banerjee, Surajit Ray, et al.. (2024). Deep multi-metric training: the need of multi-metric curve evaluation to avoid weak learning. Neural Computing and Applications. 36(30). 18841–18862.
10.
Choudhury, Robin P., et al.. (2024). Patient-specific in silico 3D coronary model in cardiac catheterisation laboratories. Frontiers in Cardiovascular Medicine. 11. 1398290–1398290. 3 indexed citations
11.
Perone, Ylenia, Shishir Shetty, Maria Qurashi, et al.. (2023). Impact of COVID-19 on 1-Year Survival Outcomes in Hepatocellular Carcinoma: A Multicenter Cohort Study. Cancers. 15(13). 3378–3378. 3 indexed citations
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Beetz, Marcel, Yilong Yang, Abhirup Banerjee, Lei Li, & Vicente Grau. (2023). 3D Shape-Based Myocardial Infarction Prediction Using Point Cloud Classification Networks. PubMed. 2023. 1–4. 3 indexed citations
14.
Shanmuganathan, Mayooran, Rafail A. Kotronias, Matthew K. Burrage, et al.. (2023). Acute changes in myocardial tissue characteristics during hospitalization in patients with COVID-19. Frontiers in Cardiovascular Medicine. 10. 1097974–1097974. 4 indexed citations
15.
Alkhodari, Mohanad, Winok Lapidaire, Zhaohan Xiong, et al.. (2023). HyperScore: A unified measure to model hypertension progression using multi-modality measurements and semi-supervised learning. 1886–1889. 1 indexed citations
16.
Banerjee, Abhirup, Amina Sâad, Ahmet Imrali, et al.. (2022). Differentiating Ductal Adenocarcinoma of the Pancreas from Benign Conditions Using Routine Health Records: A Prospective Case-Control Study. Cancers. 15(1). 280–280. 3 indexed citations
17.
Banerjee, Abhirup, Michail Mamalakis, Surajit Ray, et al.. (2022). Development of a Mortality Prediction Model in Hospitalised SARS-CoV-2 Positive Patients Based on Routine Kidney Biomarkers. International Journal of Molecular Sciences. 23(13). 7260–7260. 4 indexed citations
18.
Ray, Surajit, Abhirup Banerjee, Andrew J. Swift, et al.. (2022). A robust COVID-19 mortality prediction calculator based on Lymphocyte count, Urea, C-Reactive Protein, Age and Sex (LUCAS) with chest X-rays. Scientific Reports. 12(1). 18220–18220. 4 indexed citations
19.
Banerjee, Abhirup & Pradipta Maji. (2020). A Spatially Constrained Probabilistic Model for Robust Image Segmentation. IEEE Transactions on Image Processing. 29. 4898–4910. 7 indexed citations
20.
Banerjee, Abhirup & Pradipta Maji. (2013). Rough Sets for Bias Field Correction in MR Images Using Contraharmonic Mean and Quantitative Index. IEEE Transactions on Medical Imaging. 32(11). 2140–2151. 16 indexed citations

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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