Shreyas Vasanawala

11.1k total citations · 3 hit papers
201 papers, 7.4k citations indexed

About

Shreyas Vasanawala is a scholar working on Radiology, Nuclear Medicine and Imaging, Atomic and Molecular Physics, and Optics and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Shreyas Vasanawala has authored 201 papers receiving a total of 7.4k indexed citations (citations by other indexed papers that have themselves been cited), including 151 papers in Radiology, Nuclear Medicine and Imaging, 46 papers in Atomic and Molecular Physics, and Optics and 25 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Shreyas Vasanawala's work include Advanced MRI Techniques and Applications (117 papers), Medical Imaging Techniques and Applications (50 papers) and Atomic and Subatomic Physics Research (45 papers). Shreyas Vasanawala is often cited by papers focused on Advanced MRI Techniques and Applications (117 papers), Medical Imaging Techniques and Applications (50 papers) and Atomic and Subatomic Physics Research (45 papers). Shreyas Vasanawala collaborates with scholars based in United States, Spain and Canada. Shreyas Vasanawala's co-authors include John M. Pauly, Michael Lustig, Marcus T. Alley, Brian A. Hargreaves, Joseph Y. Cheng, Dwight G. Nishimura, Martin Uecker, Mark Murphy, Peng Lai and Albert Hsiao and has published in prestigious journals such as New England Journal of Medicine, Circulation and Journal of Clinical Oncology.

In The Last Decade

Shreyas Vasanawala

195 papers receiving 7.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

ESPIRiT—an eigenvalue approach to autocalibrating parallel MRI: Where SENSE meets GRAPPA

2013 921 citations Martin Uecker, Peng Lai et al. Magnetic Resonance in Medicine profile →
Deep Generative Adversarial Neural Networks for Compressive Sensing MRI

2018 355 citations Morteza Mardani, Joseph Y. Cheng et al. IEEE Transactions on Medical Imaging profile →
Reversal of epigenetic aging and immunosenescent trends in humans

2019 310 citations Gregory M. Fahy, Robert T. Brooke et al. Aging Cell profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shreyas Vasanawala United States	44	5.4k	1.2k	871	844	806	201	7.4k
Berthold Kiefer Germany	39	7.2k 1.3×	1.4k 1.1×	1.3k 1.5×	786 0.9×	373 0.5×	104	9.1k
Krishna S. Nayak United States	40	3.6k 0.7×	814 0.7×	519 0.6×	293 0.3×	1.0k 1.3×	219	5.8k
Yi Wang United States	51	6.8k 1.3×	1.0k 0.8×	782 0.9×	634 0.8×	548 0.7×	331	10.1k
Markus B. Scheidegger Switzerland	21	5.6k 1.0×	1.2k 1.0×	619 0.7×	569 0.7×	1.4k 1.8×	33	6.7k
Peter Börnert Germany	40	6.1k 1.1×	1.6k 1.3×	781 0.9×	489 0.6×	737 0.9×	147	6.8k
Kai Tobias Block United States	34	4.3k 0.8×	985 0.8×	448 0.5×	556 0.7×	246 0.3×	98	5.0k
Vikas Gulani United States	39	5.6k 1.0×	718 0.6×	493 0.6×	751 0.9×	279 0.3×	132	6.8k
Craig H. Meyer United States	44	5.7k 1.0×	1.5k 1.2×	990 1.1×	577 0.7×	1.1k 1.4×	190	8.2k
Charles L. Dumoulin United States	39	3.2k 0.6×	704 0.6×	699 0.8×	1.2k 1.4×	676 0.8×	125	4.8k
Tobias Schaeffter United Kingdom	51	6.1k 1.1×	1.1k 0.9×	1.8k 2.1×	1.3k 1.6×	3.6k 4.4×	318	9.8k

Countries citing papers authored by Shreyas Vasanawala

Since Specialization

Citations

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

Fields of papers citing papers by Shreyas Vasanawala

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shreyas Vasanawala

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Velikina, Julia, Lu Mao, Ruiyang Zhao, et al.. (2024). Multicenter, multivendor validation of liver quantitative susceptibility mapping in patients with iron overload at 1.5 T and 3 T. Magnetic Resonance in Medicine. 93(1). 330–340.

Han, Kyunghwa, et al.. (2024). The Impact of Artificial Intelligence on Radiologists’ Reading Time in Bone Age Radiograph Assessment: A Preliminary Retrospective Observational Study. Journal of Imaging Informatics in Medicine. 38(4). 1915–1923. 1 indexed citations

Lee, Philip K., Nan Wang, Ali Syed, et al.. (2024). Distortionless, free‐breathing, and respiratory resolved 3D diffusion weighted imaging of the abdomen. Magnetic Resonance in Medicine. 92(2). 586–604. 1 indexed citations

Iyer, Siddharth, Mahmut Yurt, Xiaozhi Cao, et al.. (2023). Toward a 1-minute high-resolution brain exam - MR Fingerprinting with fast reconstruction and ML-synthesized contrasts. Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition. 2 indexed citations

Liu, Victoria, et al.. (2023). Multi-Task Accelerated MR Reconstruction Schemes for Jointly Training Multiple Contrasts. Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition. 1 indexed citations

Tan, Fei, Marilynn Chan, Matthew A. Zapala, et al.. (2023). Motion‐compensated low‐rank reconstruction for simultaneous structural and functional UTE lung MRI. Magnetic Resonance in Medicine. 90(3). 1101–1113. 7 indexed citations

Ke, Lei, et al.. (2022). Artifact- and content-specific quality assessment for MRI with image rulers. Medical Image Analysis. 77. 102344–102344. 22 indexed citations

Ong, Frank, et al.. (2022). SLfRank: Shinnar-Le-Roux Pulse Design With Reduced Energy and Accurate Phase Profiles Using Rank Factorization. IEEE Transactions on Medical Imaging. 42(5). 1522–1531. 2 indexed citations

Bush, Adam, Christopher M. Sandino, Frank Ong, et al.. (2020). Rosette Trajectories Enable Ungated, Motion‐Robust, Simultaneous Cardiac and Liver T₂* Iron Assessment. Journal of Magnetic Resonance Imaging. 52(6). 1688–1698. 7 indexed citations

10.

Sandino, Christopher M., Joseph Y. Cheng, Feiyu Chen, et al.. (2020). Compressed Sensing: From Research to Clinical Practice With Deep Neural Networks: Shortening Scan Times for Magnetic Resonance Imaging. IEEE Signal Processing Magazine. 37(1). 117–127. 101 indexed citations

11.

Sandino, Christopher M., Peng Lai, Shreyas Vasanawala, & Joseph Y. Cheng. (2019). Accelerating cardiac cine MRI beyond compressed sensing using DL-ESPIRiT.. arXiv (Cornell University). 1 indexed citations

12.

Fahy, Gregory M., Robert T. Brooke, J. P. Watson, et al.. (2019). Reversal of epigenetic aging and immunosenescent trends in humans. Aging Cell. 18(6). e13028–e13028. 310 indexed citations breakdown →

13.

Chen, Feiyu, Joseph Y. Cheng, Valentina Taviani, et al.. (2019). Data‐driven self‐calibration and reconstruction for non‐cartesian wave‐encoded single‐shot fast spin echo using deep learning. Journal of Magnetic Resonance Imaging. 51(3). 841–853. 21 indexed citations

14.

Tamir, Jonathan I., Valentina Taviani, Marcus T. Alley, et al.. (2019). Targeted rapid knee MRI exam using T₂ shuffling. Journal of Magnetic Resonance Imaging. 49(7). e195–e204. 11 indexed citations

15.

Cheng, Joseph Y., Tao Zhang, Marcus T. Alley, et al.. (2017). Comprehensive Multi-Dimensional MRI for the Simultaneous Assessment of Cardiopulmonary Anatomy and Physiology. Scientific Reports. 7(1). 5330–5330. 37 indexed citations

16.

Chen, Feiyu, Valentina Taviani, Jonathan I. Tamir, et al.. (2017). Self‐Calibrating Wave‐Encoded Variable‐Density Single‐Shot Fast Spin Echo Imaging. Journal of Magnetic Resonance Imaging. 47(4). 954–966. 14 indexed citations

17.

Loening, Andreas M., et al.. (2016). Increased Speed and Image Quality for Pelvic Single-Shot Fast Spin-Echo Imaging with Variable Refocusing Flip Angles and Full-Fourier Acquisition. Radiology. 282(2). 561–568. 18 indexed citations

18.

Wang, Nancy E., et al.. (2016). Predictors of Nondiagnostic Ultrasound for Appendicitis. Journal of Emergency Medicine. 52(3). 318–323. 24 indexed citations

19.

Minamimoto, Ryogo, Steven Hancock, Frederick T. Chin, et al.. (2015). Pilot Comparison of ⁶⁸Ga-RM2 PET and ⁶⁸Ga-PSMA-11 PET in Patients with Biochemically Recurrent Prostate Cancer. Journal of Nuclear Medicine. 57(4). 557–562. 153 indexed citations

20.

Rakow‐Penner, Rebecca, et al.. (2010). Adrenal and renal corticomedullary junction iron deposition in red cell aplasia. Pediatric Radiology. 40(12). 1955–1957. 4 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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