World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
46
Citations
7919
World Ranking
6890
National Ranking
3020

Aaron Carass publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Aaron Carass sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 231 publications — 57th percentile

57% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Aaron Carass D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Aaron Carass sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 46 D-Index — 53rd percentile

53% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Aaron Carass is a researcher affiliated with Johns Hopkins University in the United States. Their work spans across the fields of Medicine and Computer Science, focusing particularly on Radiology, Nuclear Medicine and Imaging, and Computer Vision and Pattern Recognition. Other subfields of study include Biomedical Engineering, Neurology, and Pulmonary and Respiratory Medicine.

The research topics they concentrate on reflect these fields and include Medical Image Segmentation Techniques, Advanced MRI Techniques and Applications, Advanced Neuroimaging Techniques and Applications, Medical Imaging Techniques and Applications, Advanced Image Processing Techniques, Radiomics and Machine Learning in Medical Imaging, as well as Fetal and Pediatric Neurological Disorders.

Aaron Carass has contributed to various publication venues, with a significant number of papers appearing in:

  • arXiv (Cornell University)
  • Lecture notes in computer science
  • Medical Image Analysis
  • NeuroImage
  • Medical Imaging 2022: Image Processing

Among the recent papers authored or co-authored by Aaron Carass are:

  • "Evaluating White Matter Lesion Segmentations with Refined Sørensen-Dice Analysis," published in 2020 in Scientific Reports
  • "Unsupervised MR-to-CT Synthesis Using Structure-Constrained CycleGAN," published in 2020 in IEEE Transactions on Medical Imaging
  • "Structured layer surface segmentation for retina OCT using fully convolutional regression networks," published in 2020 in Medical Image Analysis
  • "Unsupervised MR harmonization by learning disentangled representations using information bottleneck theory," published in 2021 in NeuroImage
  • "Autoencoder based self-supervised test-time adaptation for medical image analysis," published in 2021 in Medical Image Analysis

Their frequent co-authors reflect ongoing collaboration across several research groups and include:

  • Jerry L. Prince
  • Lianrui Zuo
  • Blake E. Dewey
  • Samuel W. Remedios
  • Peter A. Calabresi

Best Publications

  • Longitudinal changes in cortical thickness associated with normal aging.

    Madhav Thambisetty;Jing Wan;Aaron Carass;Yang An

  • Longitudinal multiple sclerosis lesion segmentation: Resource and challenge.

    Aaron Carass;Snehashis Roy;Amod Jog;Jennifer L. Cuzzocreo

  • Retinal layer segmentation of macular OCT images using boundary classification

    Andrew Lang;Aaron Carass;Matthew Hauser;Elias S. Sotirchos

  • Why rankings of biomedical image analysis competitions should be interpreted with care

    Lena Maier-Hein;Matthias Eisenmann;Annika Reinke;Sinan Onogur

  • MRBrainS challenge: online evaluation framework for brain image segmentation in 3T MRI scans

    Adriënne M. Mendrik;Koen L. Vincken;Hugo J. Kuijf;Marcel Breeuwer

  • DeepHarmony: A deep learning approach to contrast harmonization across scanner changes.

    Blake E. Dewey;Blake E. Dewey;Can Zhao;Jacob C. Reinhold;Aaron Carass

  • Random forest regression for magnetic resonance image synthesis.

    Amod Jog;Aaron Carass;Snehashis Roy;Dzung L. Pham

  • Cross-Modality Image Synthesis from Unpaired Data Using CycleGAN

    Yuta Hiasa;Yoshito Otake;Masaki Takao;Takumi Matsuoka

  • Evaluating the Impact of Intensity Normalization on MR Image Synthesis.

    Jacob C. Reinhold;Blake E. Dewey;Blake E. Dewey;Aaron Carass;Jerry L. Prince

  • Evaluating White Matter Lesion Segmentations with Refined Sørensen-Dice Analysis

    Aaron Carass;Snehashis Roy;Adrian Gherman;Jacob C. Reinhold

  • Unpaired Brain MR-to-CT Synthesis Using a Structure-Constrained CycleGAN

    Heran Yang;Heran Yang;Jian Sun;Aaron Carass;Can Zhao

  • Unsupervised MR-to-CT Synthesis Using Structure-Constrained CycleGAN

    Heran Yang;Jian Sun;Aaron Carass;Can Zhao

  • Magnetic Resonance Image Example-Based Contrast Synthesis

    Snehashis Roy;Aaron Carass;Jerry L. Prince

  • The Java Image Science Toolkit (JIST) for Rapid Prototyping and Publishing of Neuroimaging Software

    Blake C. Lucas;Blake C. Lucas;John A. Bogovic;Aaron Carass;Pierre Louis Bazin

  • SIMPLE PARADIGM FOR EXTRA-CEREBRAL TISSUE REMOVAL: ALGORITHM AND ANALYSIS

    Aaron Carass;Jennifer L. Cuzzocreo;M. Bryan Wheeler;Pierre-Louis Bazin

  • Consistent cortical reconstruction and multi-atlas brain segmentation.

    Yuankai Huo;Andrew J. Plassard;Aaron Carass;Susan M. Resnick

  • Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images

    Aaron Carass;Jennifer L. Cuzzocreo;Shuo Han;Carlos R. Hernandez-Castillo

  • Applications of a deep learning method for anti-aliasing and super-resolution in MRI.

    Can Zhao;Muhan Shao;Aaron Carass;Hao Li

  • Structured layer surface segmentation for retina OCT using fully convolutional regression networks.

    Yufan He;Aaron Carass;Yihao Liu;Bruno M. Jedynak

  • Unsupervised MR harmonization by learning disentangled representations using information bottleneck theory.

    Lianrui Zuo;Blake E. Dewey;Yihao Liu;Yufan He

  • A compressed sensing approach for MR tissue contrast synthesis

    Snehashis Roy;Aaron Carass;Jerry Prince

  • Automatic Magnetic Resonance Spinal Cord Segmentation with Topology Constraints for Variable Fields of View

    Min Chen;Aaron Carass;Jiwon Oh;Govind Nair

  • Erratum to: The Java Image Science Toolkit (JIST) for Rapid Prototyping and Publishing of Neuroimaging Software

    Blake C. Lucas;Blake C. Lucas;John A. Bogovic;Aaron Carass;Pierre Louis Bazin

Frequent Co-Authors

Jerry L. Prince
Jerry L. Prince Johns Hopkins University
Peter A. Calabresi
Peter A. Calabresi Johns Hopkins University School of Medicine
Dzung L. Pham
Dzung L. Pham Henry M. Jackson Foundation
Bennett A. Landman
Bennett A. Landman Vanderbilt University
Pierre-Louis Bazin
Pierre-Louis Bazin University of Amsterdam
Susan M. Resnick
Susan M. Resnick National Institutes of Health
Daniel S. Reich
Daniel S. Reich National Institutes of Health
Peter C.M. van Zijl
Peter C.M. van Zijl Kennedy Krieger Institute
Tal Arbel
Tal Arbel McGill University
K.T. Ramesh
K.T. Ramesh Johns Hopkins University

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