Retesh Bajaj
About
Retesh Bajaj is a scholar working on Radiology, Nuclear Medicine and Imaging, Surgery and Cardiology and Cardiovascular Medicine.
According to data from OpenAlex, Retesh Bajaj has authored 26 papers receiving a total of 257 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Radiology, Nuclear Medicine and Imaging, 21 papers in Surgery and 11 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Retesh Bajaj's work include Coronary Interventions and Diagnostics (21 papers), Cardiac Imaging and Diagnostics (21 papers) and Acute Myocardial Infarction Research (5 papers). Retesh Bajaj is often cited by papers focused on Coronary Interventions and Diagnostics (21 papers), Cardiac Imaging and Diagnostics (21 papers) and Acute Myocardial Infarction Research (5 papers). Retesh Bajaj collaborates with scholars based in United Kingdom, Netherlands and United States. Retesh Bajaj's co-authors include Christos V. Bourantas, Anthony Mathur, Andreas Baumbach, Anantharaman Ramasamy, Alexandra J. Lansky, Ryo Torii, Vincenzo Tufaro, Yakup Kilic, David Taube and Paul Brookes and has published in prestigious journals such as Journal of the American College of Cardiology, European Heart Journal and The American Journal of Cardiology.
In The Last Decade
Retesh Bajaj
20 papers receiving 251 citations
Peers
Retesh Bajaj
Naveen Bellam United States
Laust Dupont Rasmussen Denmark
C. Cheshire Australia
Λάμπρος Λάκκας Greece
Paul Galiwango Canada
Osama Okasha United States
Simone Fezzi Italy
C. Bening Germany
Ryota Sakurai United States
Jiang Ming Fam Singapore
Citations per year, relative to Retesh Bajaj Retesh Bajaj (= 1×)
peers
Naveen Bellam
Countries citing papers authored by Retesh Bajaj
Since
Specialization
Citations
This map shows the geographic impact of Retesh Bajaj'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 Retesh Bajaj with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Retesh Bajaj more than expected).
Fields of papers citing papers by Retesh Bajaj
Since
Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences
This network shows the impact of papers produced by Retesh Bajaj. 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 Retesh Bajaj. The network helps show where Retesh Bajaj may publish in the future.
Co-authorship network of co-authors of Retesh Bajaj
This figure shows the co-authorship network connecting the top 25 collaborators of Retesh Bajaj. A scholar is included among the top collaborators of Retesh Bajaj 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 Retesh Bajaj. Retesh Bajaj is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
1.
Revaiah, Pruthvi C., Kotaro Miyashita, Tsung-Ying Tsai, et al.. (2025). Segmental post-percutaneous coronary intervention physiological gradients using ultrasonic or optical flow ratio: insights from ASET JAPAN study. PubMed. 3(1). qyaf017–qyaf017.
2.
Bajaj, Retesh, Alexander Broersen, Tom Johnson, et al.. (2025). Examination of the performance of machine learning-based automated coronary plaque characterization by near-infrared spectroscopy–intravascular ultrasound and optical coherence tomography with histology. European Heart Journal - Digital Health. 6(3). 359–371.
3.
Ramasamy, Anantharaman, Mohamed O. Mohamed, Retesh Bajaj, et al.. (2024). Efficacy of Coronary Calcium Score in Predicting Coronary Artery Morphology in Patients With Obstructive Coronary Artery Disease. Journal of the Society for Cardiovascular Angiography & Interventions. 3(3). 101308–101308.
4.
Bajaj, Retesh, et al.. (2024). POLYCORE: Polygon-based contour refinement for improved Intravascular Ultrasound Segmentation. Computers in Biology and Medicine. 182. 109162–109162.
5.
Ramasamy, Anantharaman, Hessam Sokooti, Xiaotong Zhang, et al.. (2023). Novel near-infrared spectroscopy–intravascular ultrasound-based deep-learning methodology for accurate coronary computed tomography plaque quantification and characterization. European Heart Journal Open. 3(5). oead090–oead090.
6.
Bajaj, Retesh, Xingru Huang, Jill J. Weyers, et al.. (2023). TCT-613 Comparison of Histology-Trained Deep Learning Approach With Human Expert Analysts for Automated Plaque Component Classification in Hybrid Intravascular Ultrasound-Optical Coherence Tomography Images. Journal of the American College of Cardiology. 82(17). B246–B247.
7.
Huang, Xingru, Retesh Bajaj, Yilong Li, et al.. (2023). POST-IVUS: A perceptual organisation-aware selective transformer framework for intravascular ultrasound segmentation. Medical Image Analysis. 89. 102922–102922.
8.
Huang, Xingru, Retesh Bajaj, Wei Cui, et al.. (2023). CARDIAN: a novel computational approach for real-time end-diastolic frame detection in intravascular ultrasound using bidirectional attention networks. Frontiers in Cardiovascular Medicine. 10. 1250800–1250800.
9.
Ramasamy, Anantharaman, Ameer Khan, Jackie Cooper, et al.. (2022). Implications of computed tomography reconstruction algorithms on coronary atheroma quantification: Comparison with intravascular ultrasound. Journal of cardiovascular computed tomography. 17(1). 43–51.
10.
Bajaj, Retesh, Jeroen Eggermont, Stephanie Grainger, et al.. (2022). Machine learning for atherosclerotic tissue component classification in combined near-infrared spectroscopy intravascular ultrasound imaging: Validation against histology. Atherosclerosis. 345. 15–25.
11.
Bajaj, Retesh, Anantharaman Ramasamy, James Brown, et al.. (2022). Treatment Strategies and Outcomes of Emergency Left Main Percutaneous Coronary Intervention. The American Journal of Cardiology. 177. 1–6.
12.
Bajaj, Retesh, et al.. (2022). Intravascular Imaging for Guiding In‐Stent Restenosis and Stent Thrombosis Therapy. Journal of the American Heart Association. 11(22). e026492–e026492.
13.
Tufaro, Vincenzo, Ryo Torii, Bon‐Kwon Koo, et al.. (2021). Wall shear stress estimated by 3D-QCA can predict cardiovascular events in lesions with borderline negative fractional flow reserve. Atherosclerosis. 322. 24–30.
14.
Bajaj, Retesh, Xingru Huang, Yakup Kilic, et al.. (2021). Advanced deep learning methodology for accurate, real-time segmentation of high-resolution intravascular ultrasound images. International Journal of Cardiology. 339. 185–191.
15.
Huang, Xingru, Jackie Cooper, Ajay Jain, et al.. (2021). End‐diastolic segmentation of intravascular ultrasound images enables more reproducible volumetric analysis of atheroma burden. Catheterization and Cardiovascular Interventions. 99(3). 706–713.
16.
Bajaj, Retesh, Anantharaman Ramasamy, Nicolas Foin, et al.. (2021). Computerized technologies informing cardiac catheterization and guiding coronary intervention. American Heart Journal. 240. 28–45.
17.
Kilic, Yakup, Retesh Bajaj, Patrick W. Serruys, et al.. (2020). The Evolution of Data Fusion Methodologies Developed to Reconstruct Coronary Artery Geometry From Intravascular Imaging and Coronary Angiography Data: A Comprehensive Review. Frontiers in Cardiovascular Medicine. 7. 33–33.
18.
Ramasamy, Anantharaman, Chongying Jin, Vincenzo Tufaro, et al.. (2020). Computerised Methodologies for Non-Invasive Angiography-Derived Fractional Flow Reserve Assessment: A Critical Review. Journal of Interventional Cardiology. 2020. 1–10.
19.
Ramasamy, Anantharaman, Retesh Bajaj, Fizzah Choudry, et al.. (2020). Intravascular ultrasound-guided management of ST-elevation myocardial infarction in a patient with lung cancer and myocardial metastasis. European Heart Journal. 41(33). 3201–3201.
20.
Lawrence, Christopher, Michelle Willicombe, Paul Brookes, et al.. (2012). Preformed Complement-Activating Low-Level Donor-Specific Antibody Predicts Early Antibody-Mediated Rejection in Renal Allografts. Transplantation. 95(2). 341–346.
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.
Explore authors with similar magnitude of impact
Breakdown of academic impact, for papers by Naveen Bellam Breakdown of academic impact, for papers by Laust Dupont Rasmussen Breakdown of academic impact, for papers by C. Cheshire Breakdown of academic impact, for papers by Λάμπρος Λάκκας Breakdown of academic impact, for papers by Paul Galiwango Breakdown of academic impact, for papers by Osama Okasha Breakdown of academic impact, for papers by Simone Fezzi Breakdown of academic impact, for papers by C. Bening Breakdown of academic impact, for papers by Ryota Sakurai Breakdown of academic impact, for papers by Jiang Ming Fam