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Engineering and Technology
Chile
2026

D-Index & Metrics

Engineering and Technology

D-Index
46
Citations
6172
World Ranking
5300
National Ranking
3

Claudia Prieto 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 Claudia Prieto 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: 244 publications — 63rd percentile

63% of scientists in this discipline score the same or lower.

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

Claudia Prieto 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 Claudia Prieto 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: 46 D-Index — 49th percentile

49% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2026 - Research.com Engineering and Technology in Chile Leader Award
  • 2025 - Research.com Engineering and Technology in Chile Leader Award

Overview

Claudia Prieto is affiliated with the Pontificia Universidad Católica de Chile in Chile. Their research primarily focuses on the field of Medicine, with a substantial number of publications in subfields such as Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine, Biomedical Engineering, Atomic and Molecular Physics, and Optics, as well as Pulmonary and Respiratory Medicine.

Their work covers a variety of specialized topics including:

  • Advanced MRI Techniques and Applications
  • Cardiac Imaging and Diagnostics
  • Medical Imaging Techniques and Applications
  • Advanced X-ray and CT Imaging
  • Atomic and Subatomic Physics Research
  • Cardiovascular Function and Risk Factors
  • Cardiac Valve Diseases and Treatments

Prieto has contributed to several research papers notable for their focus on medical imaging and cardiovascular diagnostics. Key recent publications include:

  • "CINENet: deep learning-based 3D cardiac CINE MRI reconstruction with multi-coil complex-valued 4D spatio-temporal convolutions" (2020), published in Scientific Reports
  • "From Compressed-Sensing to Artificial Intelligence-Based Cardiac MRI Reconstruction" (2020), published in Frontiers in Cardiovascular Medicine
  • "Multi-parametric liver tissue characterization using MR fingerprinting: Simultaneous T1, T2, T2*, and fat fraction mapping" (2020), published in Magnetic Resonance in Medicine
  • "Deep-learning based super-resolution for 3D isotropic coronary MR angiography in less than a minute" (2021), published in Magnetic Resonance in Medicine
  • "A Survey on Deep Learning and Explainability for Automatic Report Generation from Medical Images" (2022), published in ACM Computing Surveys

Their frequent co-authors include René M. Botnar, Karl Kunze, Radhouène Neji, Gastão Cruz, and Anastasia Fotaki. These collaborations suggest a multidisciplinary approach to imaging and cardiovascular research.

Prieto's research is disseminated across a variety of venues, reflecting engagement with both clinical and technical aspects of medical imaging. These publication venues include:

  • Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
  • Journal of Cardiovascular Magnetic Resonance
  • Magnetic Resonance in Medicine
  • arXiv (Cornell University)
  • Frontiers in Cardiovascular Medicine

Best Publications

  • CINENet: deep learning-based 3D cardiac CINE MRI reconstruction with multi-coil complex-valued 4D spatio-temporal convolutions

    Thomas Küstner;Niccolo Fuin;Kerstin Hammernik;Aurelien Bustin

  • Motion corrected compressed sensing for free-breathing dynamic cardiac MRI.

    Muhammad Usman;David Atkinson;Freddy Odille;Christoph Kolbitsch

  • Whole-heart coronary MR angiography with 2D self-navigated image reconstruction.

    Markus Henningsson;Peter Koken;Christian Stehning;Reza Razavi

  • Highly efficient respiratory motion compensated free‐breathing coronary mra using golden‐step Cartesian acquisition

    Claudia Prieto;Claudia Prieto;Mariya Doneva;Muhammad Usman;Markus Henningsson

  • From Compressed-Sensing to Artificial Intelligence-Based Cardiac MRI Reconstruction.

    Aurélien Bustin;Niccolo Fuin;René M. Botnar;René M. Botnar;Claudia Prieto;Claudia Prieto

  • Highly efficient nonrigid motion corrected 3D whole-heart coronary vessel wall imaging

    Gastao Cruz;David Atkinson;Markus Henningsson;René Michael Botnar;René Michael Botnar

  • Characterization of Bordetella pertussis growing as biofilm by chemical analysis and FT-IR spectroscopy

    A. Bosch;D. Serra;C. Prieto;J. Schmitt

  • High-dimensionality undersampled patch-based reconstruction (HD-PROST) for accelerated multi-contrast MRI

    Aurélien Bustin;Gastão Lima da Cruz;Olivier Jaubert;Karina Lopez

  • Five-minute whole-heart coronary MRA with sub-millimeter isotropic resolution, 100% respiratory scan efficiency, and 3D-PROST reconstruction.

    Aurélien Bustin;Giulia Ginami;Gastão Cruz;Teresa Correia

  • k-t Group sparse: a method for accelerating dynamic MRI.

    M. Usman;C. Prieto;T. Schaeffter;P. G. Batchelor

  • Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning.

    Ilkay Öksüz;Bram Ruijsink;Esther Puyol-Antón;James R. Clough

  • Accelerated motion corrected three‐dimensional abdominal MRI using total variation regularized SENSE reconstruction

    Gastao Cruz;David Atkinson;Christian Buerger;Tobias Schaeffter

  • Deep Learning-Based Detection and Correction of Cardiac MR Motion Artefacts During Reconstruction for High-Quality Segmentation

    Ilkay Oksuz;James R. Clough;Bram Ruijsink;Esther Puyol Anton

  • Nonrigid Motion Modeling of the Liver From 3-D Undersampled Self-Gated Golden-Radial Phase Encoded MRI

    C. Buerger;R. E. Clough;A. P. King;T. Schaeffter

  • 3D Undersampled Golden-Radial Phase Encoding for DCE-MRA Using Inherently Regularized Iterative SENSE

    Claudia Prieto;Sergio Uribe;Sergio Uribe;Reza Razavi;David Atkinson

  • Multi-parametric liver tissue characterization using MR fingerprinting: Simultaneous T1 , T2 , T2 *, and fat fraction mapping.

    Olivier Jaubert;Cristobal Arrieta;Gastão Cruz;Aurélien Bustin

  • Deep-learning based super-resolution for 3D isotropic coronary MR angiography in less than a minute.

    Thomas Küstner;Camila Munoz;Alina Psenicny;Aurélien Bustin

  • 3D whole-heart isotropic sub-millimeter resolution coronary magnetic resonance angiography with non-rigid motion-compensated PROST.

    Aurélien Bustin;Imran Rashid;Gastao Cruz;Reza Hajhosseiny;Reza Hajhosseiny

  • Sparsity and locally low rank regularization for MR fingerprinting.

    Gastão Lima da Cruz;Aurélien Bustin;Oliver Jaubert;Torben Schneider

  • Whole-Heart Coronary MRA with 3D Affine Motion Correction Using 3D Image-Based Navigation

    Markus Henningsson;Claudia Prieto;Claudia Prieto;Amedeo Chiribiri;Ghislain Vaillant

  • Free breathing whole-heart 3D CINE MRI with self-gated Cartesian trajectory.

    M. Usman;M. Usman;B. Ruijsink;M.S. Nazir;G. Cruz

  • Model‐based reconstruction for cardiac cine MRI without ECG or breath holding

    Freddy Odille;Sergio Uribe;Philip G. Batchelor;Claudia Prieto

  • PET image reconstruction using multi-parametric anato-functional priors.

    Abolfazl Mehranian;Martin A Belzunce;Flavia Niccolini;Marios Politis

Frequent Co-Authors

René M. Botnar
René M. Botnar Pontificia Universidad Católica de Chile
David Atkinson
David Atkinson University of Liverpool
Andrew P. King
Andrew P. King King's College London
Andrew J. Reader
Andrew J. Reader King's College London
Daniel Rueckert
Daniel Rueckert Technical University of Munich
Julia A. Schnabel
Julia A. Schnabel King's College London
Reza Razavi
Reza Razavi King's College London
Joseph V. Hajnal
Joseph V. Hajnal King's College London
Alexander Hammers
Alexander Hammers King's College London
David J. Young
David J. Young University of New South Wales

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