World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
48
Citations
9479
World Ranking
4542
National Ranking
1302

Shigao Chen publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Shigao Chen sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 286 publications — 73rd percentile

73% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Shigao Chen D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Shigao Chen sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 48 D-Index — 55th percentile

55% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Shigao Chen is affiliated with the Mayo Clinic in the United States. Their research spans the intersection of medicine and engineering, with a significant focus on biomedical engineering and imaging technologies.

Their main fields of study include:

  • Medicine
  • Engineering

In terms of subfields, their work primarily covers:

  • Biomedical Engineering
  • Radiology, Nuclear Medicine and Imaging
  • Materials Chemistry
  • Epidemiology
  • Electrical and Electronic Engineering

The primary topics of their research are:

  • Ultrasound Imaging and Elastography
  • Photoacoustic and Ultrasonic Imaging
  • Ultrasound and Hyperthermia Applications
  • Liver Disease Diagnosis and Treatment
  • Luminescence Properties of Advanced Materials
  • Perovskite Materials and Applications
  • Liver Disease and Transplantation

Frequent co-authors collaborating with Shigao Chen include:

  • Chengwu Huang
  • U-Wai Lok
  • Pengfei Song
  • Shanshan Tang
  • Ping Gong

Shigao Chen has published extensively in several scientific venues, particularly:

  • IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control
  • Ultrasound in Medicine & Biology
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Journal of Ultrasound in Medicine
  • Ceramics International

Some of the recent notable papers include:

  • "Short Acquisition Time Super-Resolution Ultrasound Microvessel Imaging via Microbubble Separation" (2020) published in Scientific Reports
  • "Utilisation of artificial intelligence for the development of an EUS-convolutional neural network model trained to enhance the diagnosis of autoimmune pancreatitis" (2020) published in Gut
  • "Kalman Filter-Based Microbubble Tracking for Robust Super-Resolution Ultrasound Microvessel Imaging" (2020) published in IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control
  • "Ultrasound localization microscopy of renal tumor xenografts in chicken embryo is correlated to hypoxia" (2020) published in Scientific Reports
  • "Real time SVD-based clutter filtering using randomized singular value decomposition and spatial downsampling for micro-vessel imaging on a Verasonics ultrasound system" (2020) published in Ultrasonics

Best Publications

  • Shearwave dispersion ultrasound vibrometry (SDUV) for measuring tissue elasticity and viscosity

    Shigao Chen;M. Urban;C. Pislaru;R. Kinnick

  • Validation of shear wave elastography in skeletal muscle.

    Sarah F. Eby;Pengfei Song;Shigao Chen;Qingshan Chen

  • Quantifying elasticity and viscosity from measurement of shear wave speed dispersion

    Shigao Chen;Mostafa Fatemi;James F. Greenleaf

  • Ultrasound elastography: the new frontier in direct measurement of muscle stiffness.

    Joline E. Brandenburg;Sarah F. Eby;Pengfei Song;Heng Zhao

  • Shear wave elastography of passive skeletal muscle stiffness: Influences of sex and age throughout adulthood

    Sarah F. Eby;Beth A. Cloud;Joline E. Brandenburg;Hugo Giambini

  • Improved Super-Resolution Ultrasound Microvessel Imaging With Spatiotemporal Nonlocal Means Filtering and Bipartite Graph-Based Microbubble Tracking

    Pengfei Song;Joshua D. Trzasko;Armando Manduca;Runqing Huang

  • Assessment of Liver Viscoelasticity by Using Shear Waves Induced by Ultrasound Radiation Force

    Shigao Chen;William Sanchez;Matthew R. Callstrom;Brian Gorman

  • Ultrasound Small Vessel Imaging With Block-Wise Adaptive Local Clutter Filtering

    Pengfei Song;Armando Manduca;Joshua D. Trzasko;Shigao Chen

  • Comb-Push Ultrasound Shear Elastography (CUSE): A Novel Method for Two-Dimensional Shear Elasticity Imaging of Soft Tissues

    Pengfei Song;Heng Zhao;A. Manduca;M. W. Urban

  • Short Acquisition Time Super-Resolution Ultrasound Microvessel Imaging via Microbubble Separation

    Chengwu Huang;Matthew R Lowerison;Matthew R Lowerison;Joshua D Trzasko;Armando Manduca

  • RSNA/QIBA: Shear wave speed as a biomarker for liver fibrosis staging

    Timothy J. Hall;Andy Milkowski;Brian Garra;Paul Carson

  • Fast shear compounding using robust 2-D shear wave speed calculation and multi-directional filtering.

    Pengfei Song;Armando Manduca;Heng Zhao;Matthew W. Urban

  • Utilisation of artificial intelligence for the development of an EUS-convolutional neural network model trained to enhance the diagnosis of autoimmune pancreatitis.

    Neil B Marya;Patrick D Powers;Suresh T Chari;Ferga C Gleeson

  • Detection of tissue harmonic motion induced by ultrasonic radiation force using pulse-echo ultrasound and kalman filter

    Yi Zheng;Shigao Chen;Wei Tan;R. Kinnick

  • Bias observed in time-of-flight shear wave speed measurements using radiation force of a focused ultrasound beam.

    Heng Zhao;Pengfei Song;Matthew W. Urban;Randall R. Kinnick

  • A Review of Shearwave Dispersion Ultrasound Vibrometry (SDUV) and its Applications.

    Matthew W. Urban;Shigao Chen;Mostafa Fatemi

  • Kalman Filter-Based Microbubble Tracking for Robust Super-Resolution Ultrasound Microvessel Imaging

    Shanshan Tang;Pengfei Song;Joshua D. Trzasko;Matthew Lowerison

  • Remote measurement of material properties from radiation force induced vibration of an embedded sphere

    Shigao Chen;Mostafa Fatemi;James F. Greenleaf

  • Quantitative assessment of rotator cuff muscle elasticity: Reliability and feasibility of shear wave elastography

    Taku Hatta;Hugo Giambini;Kosuke Uehara;Seiji Okamoto

  • Comb-Push Ultrasound Shear Elastography (CUSE) With Various Ultrasound Push Beams

    Pengfei Song;Matthew W. Urban;Armando Manduca;Heng Zhao

  • Two-dimensional shear-wave elastography on conventional ultrasound scanners with time-aligned sequential tracking (TAST) and comb-push ultrasound shear elastography (CUSE)

    Pengfei Song;Michael C. Macdonald;Russell H. Behler;Justin D. Lanning

  • Improved Shear Wave Motion Detection Using Pulse-Inversion Harmonic Imaging With a Phased Array Transducer

    Pengfei Song;Heng Zhao;Matthew W. Urban;Armando Manduca

  • Super-resolution ultrasound localization microscopy based on a high frame-rate clinical ultrasound scanner: an in-human feasibility study.

    Chengwu Huang;Wei Zhang;Ping Gong;U-Wai Lok

  • Error in estimates of tissue material properties from shear wave dispersion ultrasound vibrometry

    M.W. Urban;Shigao Chen;J.F. Greenleaf

Frequent Co-Authors

Matthew W. Urban
Matthew W. Urban Mayo Clinic
Armando Manduca
Armando Manduca Mayo Clinic
Mostafa Fatemi
Mostafa Fatemi Mayo Clinic
Kai Nan An
Kai Nan An Mayo Clinic
Mark L. Palmeri
Mark L. Palmeri Duke University
David F. Kallmes
David F. Kallmes Mayo Clinic
Paul L. Carson
Paul L. Carson University of Michigan–Ann Arbor
Timothy J. Hall
Timothy J. Hall University of Wisconsin–Madison
Richard L. Ehman
Richard L. Ehman Mayo Clinic

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