World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
7965
World Ranking
10554
National Ranking
4424

Elizabeth Bullitt 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 Elizabeth Bullitt 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: 88 publications — 5th percentile

5% of scientists in this discipline score the same or lower.

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

Elizabeth Bullitt 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 Elizabeth Bullitt 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: 37 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Overview

Elizabeth Bullitt is affiliated with the University of North Carolina at Chapel Hill in the United States. Their research primarily falls within the field of Medicine, with a strong focus on Radiology, Nuclear Medicine and Imaging. Additional subfields of study include Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine, Neurology, and Genetics.

The scientist's work encompasses a variety of topics, notably:

  • Radiomics and Machine Learning in Medical Imaging
  • Brain Tumor Detection and Classification
  • Medical Image Segmentation Techniques
  • MRI in Cancer Diagnosis
  • Advanced MRI Techniques and Applications
  • Medical Imaging and Analysis
  • Connective Tissue Disorders Research

Elizabeth Bullitt has contributed to several publications hosted in the UNC Libraries, a frequent venue for their work. Notable recent papers include:

  • "Vessel tortuosity and brain tumor malignancy: A blinded study" (2020, UNC Libraries)
  • "Registration and Analysis of Vascular Images" (2021, UNC Libraries)
  • "The effects of healthy aging on intracerebral blood vessels visualized by magnetic resonance angiography" (2020, UNC Libraries)
  • "Malignancy-Associated Vessel Tortuosity: A Computer-Assisted, MRA Study of Choroid Plexus Carcinoma in Genetically Engineered Mice" (2020, UNC Libraries)
  • "A principal component analysis for trees" (2021, UNC Libraries)

Collaborations form an integral part of their research, with frequent co-authorship alongside:

  • Stephen Aylward
  • Matthew G. Ewend
  • Donglin Zeng
  • Guido Gerig
  • J. Keith Smith

The collaborative network and venue consistency suggest ongoing engagement with institutions and scholars focused on medical imaging and computational analysis in healthcare.

Best Publications

  • A brain tumor segmentation framework based on outlier detection.

    Marcel Prastawa;Elizabeth Bullitt;Sean Ho;Guido Gerig

  • Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction

    S.R. Aylward;E. Bullitt

  • Measuring tortuosity of the intracerebral vasculature from MRA images

    E. Bullitt;G. Gerig;S.M. Pizer;Weili Lin

  • Level-set evolution with region competition: automatic 3-D segmentation of brain tumors

    S. Ho;E. Bullitt;G. Gerig

  • Population Shape Regression from Random Design Data

    Brad C. Davis;P. Thomas Fletcher;Elizabeth Bullitt;Sarang Joshi

  • Vessel tortuosity and brain tumor malignancy: a blinded study.

    Elizabeth Bullitt;Donglin Zeng;Guido Gerig;Stephen Aylward

  • Automatic brain tumor segmentation by subject specific modification of atlas priors.

    Marcel Prastawa;Elizabeth Bullitt;Nathan Moon;Koen Van Leemput

  • Systems and methods for tubular object processing

    Stephen R. Aylward;Elizabeth Bullitt;Stephen M. Pizer;Daniel Fritsch

  • Population Shape Regression From Random Design Data

    B.C. Davis;P.T. Fletcher;E. Bullitt;S. Joshi

  • Intensity ridge and widths for tubular object segmentation and description

    S. Aylward;E. Bullitt;S. Pizer;D. Eberly

  • Methods, systems, and computer program products for hierarchical registration between a blood vessel and tissue surface model for a subject and a blood vessel and tissue surface image for the subject

    Stephen Aylward;Elizabeth Bullitt;Julien Jomier

  • Simulation of brain tumors in MR images for evaluation of segmentation efficacy.

    Marcel Prastawa;Elizabeth Bullitt;Guido Gerig

  • The Effect of Exercise on the Cerebral Vasculature of Healthy Aged Subjects as Visualized by MR Angiography

    Elizabeth Bullitt;F. N. Rahman;J. K. Smith;E. Kim

  • Systems, methods, and computer program products for analysis of vessel attributes for diagnosis, disease staging, and surgical planning

    Elizabeth Bullitt;Stephen Aylward

  • Automatic brain and tumor segmentation

    Nathan Moon;Elizabeth Bullitt;Koen Van Leemput;Guido Gerig

  • Registration and Analysis of Vascular Images

    Stephen R. Aylward;Julien Jomier;Sue Weeks;Elizabeth Bullitt

  • White matter abnormalities revealed by diffusion tensor imaging in non-demented and demented HIV+ patients

    Yasheng Chen;Hongyu An;Hongtu Zhu;Taylor Stone

  • Multi-modal image set registration and atlas formation

    Peter Lorenzen;Marcel Prastawa;Brad Davis;Guido Gerig

  • Model-based brain and tumor segmentation

    N. Moon;E. Bullitt;K. van Leemput;G. Gerig

  • The effects of healthy aging on intracerebral blood vessels visualized by magnetic resonance angiography.

    Elizabeth Bullitt;Donglin Zeng;Benedicte Mortamet;Arpita Ghosh

Frequent Co-Authors

Guido Gerig
Guido Gerig New York University
Stephen M. Pizer
Stephen M. Pizer University of North Carolina at Chapel Hill
Weili Lin
Weili Lin University of North Carolina at Chapel Hill
Sarang Joshi
Sarang Joshi University of Utah
James Stephen Marron
James Stephen Marron University of North Carolina at Chapel Hill
Eric P. Winer
Eric P. Winer Yale University
Lisa A. Carey
Lisa A. Carey University of North Carolina at Chapel Hill
Rebecca Gelman
Rebecca Gelman Harvard University
Koen Van Leemput
Koen Van Leemput Harvard University
Alan R. Light
Alan R. Light University of Utah

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Best Scientists Citing Elizabeth Bullitt