Stephen Cauley

6.0k total citations · 1 hit paper
84 papers, 3.5k citations indexed

About

Stephen Cauley is a scholar working on Radiology, Nuclear Medicine and Imaging, Atomic and Molecular Physics, and Optics and Computational Theory and Mathematics. According to data from OpenAlex, Stephen Cauley has authored 84 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Radiology, Nuclear Medicine and Imaging, 23 papers in Atomic and Molecular Physics, and Optics and 9 papers in Computational Theory and Mathematics. Recurrent topics in Stephen Cauley's work include Advanced MRI Techniques and Applications (64 papers), Advanced Neuroimaging Techniques and Applications (30 papers) and Medical Imaging Techniques and Applications (27 papers). Stephen Cauley is often cited by papers focused on Advanced MRI Techniques and Applications (64 papers), Advanced Neuroimaging Techniques and Applications (30 papers) and Medical Imaging Techniques and Applications (27 papers). Stephen Cauley collaborates with scholars based in United States, Germany and United Kingdom. Stephen Cauley's co-authors include Lawrence L. Wald, Matthew S. Rosen, Kawin Setsompop, Bruce R. Rosen, Bo Zhu, Jeremiah Zhe Liu, Berkin Bilgic̦, Jon̈athan R. Polimeni, Himanshu Bhat and Elfar Adalsteinsson and has published in prestigious journals such as Nature, Journal of Applied Physics and NeuroImage.

In The Last Decade

Stephen Cauley

79 papers receiving 3.4k citations

Hit Papers

Image reconstruction by domain-transform manifold learning 2018 2026 2020 2023 2018 250 500 750 1000
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.

  1. Image reconstruction by domain-transform manifold learning
    2018 1.1k citations Bo Zhu, Jeremiah Zhe Liu et al. Nature profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stephen Cauley United States 28 2.8k 637 628 267 253 84 3.5k
Krishna S. Nayak United States 40 3.6k 1.3× 814 1.3× 519 0.8× 270 1.0× 262 1.0× 219 5.8k
Rudolf Stollberger Austria 28 2.5k 0.9× 295 0.5× 535 0.9× 242 0.9× 317 1.3× 181 3.8k
Dan Ma United States 35 3.9k 1.4× 532 0.8× 247 0.4× 343 1.3× 150 0.6× 91 4.5k
Li Feng United States 29 3.0k 1.1× 840 1.3× 343 0.5× 147 0.6× 111 0.4× 104 3.6k
Ricardo Otazo United States 33 4.3k 1.6× 1.1k 1.7× 586 0.9× 430 1.6× 291 1.2× 107 5.0k
Michael R. Thompson United States 7 1.9k 0.7× 409 0.6× 332 0.5× 336 1.3× 123 0.5× 10 2.5k
Arthur F. Gmitro United States 32 1.7k 0.6× 305 0.5× 1.0k 1.6× 245 0.9× 233 0.9× 132 4.0k
Berkin Bilgic̦ United States 33 3.1k 1.1× 556 0.9× 188 0.3× 286 1.1× 206 0.8× 135 3.6k
James G. Pipe United States 32 3.7k 1.3× 709 1.1× 307 0.5× 274 1.0× 177 0.7× 93 4.5k
Nicole Seiberlich United States 35 4.7k 1.7× 995 1.6× 451 0.7× 506 1.9× 121 0.5× 132 5.2k

Countries citing papers authored by Stephen Cauley

Since Specialization
Citations

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

Fields of papers citing papers by Stephen Cauley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stephen Cauley

This figure shows the co-authorship network connecting the top 25 collaborators of Stephen Cauley. A scholar is included among the top collaborators of Stephen Cauley 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 Stephen Cauley. Stephen Cauley 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
1.
Franson, Dominique, Hongli Fan, Clemente Velasco‐Annis, et al.. (2025). Variable Flip Angle Optimization for Fetal Brain Imaging With Reduced Specific Absorption Rate. NMR in Biomedicine. 38(7). e70075–e70075. 1 indexed citations
2.
Lo, Wei‐Ching, Bryan Clifford, Min Lang, et al.. (2024). Evaluation of Scout Accelerated Motion Estimation and Reduction (SAMER) MPRAGE for Visual Grading and Volumetric Measurement of Brain Tissue. Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition. 1 indexed citations
3.
Lang, Min, Bryan Clifford, Wei‐Ching Lo, et al.. (2024). Clinical Evaluation of a 2-Minute Ultrafast Brain MR Protocol for Evaluation of Acute Pathology in the Emergency and Inpatient Settings. American Journal of Neuroradiology. 45(4). 379–385. 6 indexed citations
4.
Clifford, Bryan, Wei‐Ching Lo, Daniel Polak, et al.. (2024). Motion Estimation and Retrospective Correction in 2D Cartesian Turbo Spin Echo Spine Scans. Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition.
5.
Cho, Jaejin, Borjan Gagoski, Tae Hyung Kim, et al.. (2023). Time‐efficient, high‐resolution3Twhole‐brain relaxometry using3D‐QALASwithwave‐CAIPIreadouts. Magnetic Resonance in Medicine. 91(2). 630–639. 10 indexed citations
6.
Feiweier, Thorsten, John Conklin, Stephan Kannengießer, et al.. (2023). A data-driven method for automatic regularization selection in a hybrid DL-SENSE reconstruction. Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition. 1 indexed citations
7.
Lang, Min, Azadeh Tabari, Daniel Polak, et al.. (2023). Clinical Evaluation of Scout Accelerated Motion Estimation and Reduction Technique for 3D MR Imaging in the Inpatient and Emergency Department Settings. American Journal of Neuroradiology. 44(2). 125–133. 2 indexed citations
8.
Conklin, John, Azadeh Tabari, Maria Gabriela Figueiró Longo, et al.. (2022). Evaluation of highly accelerated wave controlled aliasing in parallel imaging (Wave-CAIPI) susceptibility-weighted imaging in the non-sedated pediatric setting: a pilot study. Pediatric Radiology. 52(6). 1115–1124. 4 indexed citations
9.
Conklin, John, Maria Gabriela Figueiró Longo, Azadeh Tabari, et al.. (2022). Clinical validation of Wave-CAIPI susceptibility-weighted imaging for routine brain MRI at 1.5 T. European Radiology. 32(10). 7128–7135. 2 indexed citations
10.
Cauley, Stephen, Jason Stockmann, Charlotte R. Sappo, et al.. (2021). External Dynamic InTerference Estimation and Removal (EDITER) for low field MRI. Magnetic Resonance in Medicine. 87(2). 614–628. 37 indexed citations
11.
Ngamsombat, Chanon, Maria Gabriela Figueiró Longo, Stephen Cauley, et al.. (2021). Evaluation of Ultrafast Wave–Controlled Aliasing in Parallel Imaging 3D-FLAIR in the Visualization and Volumetric Estimation of Cerebral White Matter Lesions. American Journal of Neuroradiology. 42(9). 1584–1590. 14 indexed citations
12.
Clifford, Bryan, John Conklin, Susie Y. Huang, et al.. (2021). An artificial intelligence‐accelerated 2‐minute multi‐shot echo planar imaging protocol for comprehensive high‐quality clinical brain imaging. Magnetic Resonance in Medicine. 87(5). 2453–2463. 16 indexed citations
13.
14.
Cooley, Clarissa, Patrick C. McDaniel, Jason Stockmann, et al.. (2020). A portable scanner for magnetic resonance imaging of the brain. Nature Biomedical Engineering. 5(3). 229–239. 149 indexed citations
15.
Bilgic̦, Berkin, Itthi Chatnuntawech, Mary Kate Manhard, et al.. (2019). Highly accelerated multishot echo planar imaging through synergistic machine learning and joint reconstruction. Magnetic Resonance in Medicine. 82(4). 1343–1358. 43 indexed citations
16.
Conklin, John, Maria Gabriela Figueiró Longo, Stephen Cauley, et al.. (2019). Validation of Highly Accelerated Wave–CAIPI SWI Compared with Conventional SWI and T2*-Weighted Gradient Recalled-Echo for Routine Clinical Brain MRI at 3T. American Journal of Neuroradiology. 40(12). 2073–2080. 36 indexed citations
17.
Zhu, Bo, Jeremiah Zhe Liu, Stephen Cauley, Bruce R. Rosen, & Matthew S. Rosen. (2018). Image reconstruction by domain-transform manifold learning. Nature. 555(7697). 487–492. 1085 indexed citations breakdown →
18.
Jiang, Yun, Dan Ma, Himanshu Bhat, et al.. (2016). Use of pattern recognition for unaliasing simultaneously acquired slices in simultaneous multislice MR fingerprinting. Magnetic Resonance in Medicine. 78(5). 1870–1876. 24 indexed citations
19.
Cauley, Stephen, Yuanzhe Xi, Berkin Bilgic̦, et al.. (2015). Fast reconstruction for multichannel compressed sensing using a hierarchically semiseparable solver. DSpace@MIT (Massachusetts Institute of Technology). 4 indexed citations
20.
Fan, Qiuyun, Aapo Nummenmaa, Thomas Witzel, et al.. (2014). Investigating the Capability to Resolve Complex White Matter Structures with High b -Value Diffusion Magnetic Resonance Imaging on the MGH-USC Connectom Scanner. Brain Connectivity. 4(9). 718–726. 41 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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