World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
30
Citations
3790
World Ranking
14102
National Ranking
5587

Tina Kapur 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 Tina Kapur 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.

Tina Kapur 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 Tina Kapur 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: 30 D-Index — 3rd percentile

3% of scientists in this discipline score the same or lower.

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

Overview

Tina Kapur is a researcher affiliated with Brigham and Women's Hospital in the United States. Their work primarily falls within the broad field of Medicine, with a focus on several specialized subfields including Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Computer Vision and Pattern Recognition, Biomedical Engineering, and Critical Care and Intensive Care Medicine.

Their research topics cover a range of subjects, prominently featuring Ultrasound in Clinical Applications, Radiomics and Machine Learning in Medical Imaging, Schizophrenia research and treatment, Medical Image Segmentation Techniques, Medical Imaging Techniques and Applications, Lung Cancer Diagnosis and Treatment, and Medical Imaging and Analysis.

Tina Kapur has contributed to multiple publication venues, frequently publishing in arXiv (Cornell University), UNC Libraries, International Journal of Computer Assisted Radiology and Surgery, bioRxiv (Cold Spring Harbor Laboratory), and Lecture Notes in Computer Science.

Frequent collaborators include Alexandra J. Golby, Sarah Frisken, William M. Wells, Daniel H. Mathalon, and Nazim Haouchine, indicating interdisciplinary cooperation in their research projects.

Selected recent papers authored by or associated with Tina Kapur include:

  • Peak learning of mass spectrometry imaging data using artificial neural networks, 2021, Nature Communications
  • SlicerDMRI: Diffusion MRI and Tractography Research Software for Brain Cancer Surgery Planning and Visualization, 2020, JCO Clinical Cancer Informatics
  • Challenges and Opportunities of Intraoperative 3D Ultrasound With Neuronavigation in Relation to Intraoperative MRI, 2021, Frontiers in Oncology
  • Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ): Rationale and Study Design of the Largest Global Prospective Cohort Study of Clinical High Risk for Psychosis, 2024, Schizophrenia Bulletin
  • Improving detection of prostate cancer foci via information fusion of MRI and temporal enhanced ultrasound, 2020, International Journal of Computer Assisted Radiology and Surgery

Best Publications

  • Fluoroscopic tracking and visualization system

    Teresa Seeley;Faith Lin;Tina Kapur;Gene Gregerson

  • Segmentation of Brain Tissue from Magnetic Resonance Images

    Tina Kapur

  • OpenIGTLink: an open network protocol for image-guided therapy environment

    Junichi Tokuda;Gregory S. Fischer;Xenophon Papademetris;Ziv Yaniv

  • Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation

    Mohsen Ghafoorian;Mohsen Ghafoorian;Alireza Mehrtash;Alireza Mehrtash;Tina Kapur;Nico Karssemeijer

  • Confidence Calibration and Predictive Uncertainty Estimation for Deep Medical Image Segmentation

    Alireza Mehrtash;William M. Wells;Clare M. Tempany;Purang Abolmaesumi

  • GBM Volumetry using the 3D Slicer Medical Image Computing Platform

    Jan Egger;Tina Kapur;Andriy Fedorov;Steve Pieper

  • A variational framework for joint segmentation and registration

    A. Yezzi;L. Zollei;T. Kapur

  • A variational framework for integrating segmentation and registration through active contours.

    Anthony J. Yezzi;Lilla Zöllei;Tina Kapur

  • Applications of Ultrasound in the Resection of Brain Tumors

    Rahul Sastry;Wenya Linda Bi;Steve Pieper;Sarah Frisken

  • Utilizing Segmented MRI Data in Image-Guided Surgery

    W. E. L. Grimson;G. J. Ettinger;T. Kapur;M. E. Leventon

  • Fiber Tractography Based on Diffusion Tensor Imaging Compared With High-Angular-Resolution Diffusion Imaging With Compressed Sensing: Initial Experience

    Daniela Kuhnt;Miriam H A Bauer;Jan Egger;Mirco Richter

  • Enhanced Spatial Priors for Segmentation of Magnetic Resonance Imagery

    Tina Kapur;W. Eric L. Grimson;Ron Kikinis;William M. Wells

  • Classification of Clinical Significance of MRI Prostate Findings Using 3D Convolutional Neural Networks.

    Alireza Mehrtash;Alireza Sedghi;Mohsen Ghafoorian;Mehdi Taghipour

  • Pituitary Adenoma Volumetry with 3D Slicer

    Jan Egger;Jan Egger;Tina Kapur;Christopher Nimsky;Ron Kikinis

  • Whole brain white matter connectivity analysis using machine learning: An application to autism.

    Fan Zhang;Peter Savadjiev;Weidong Cai;Yang Song

  • Model-based three-dimensional medical image segmentation

    Tina Kapur;W. Eric Grimson;William M. Wells

  • Peak learning of mass spectrometry imaging data using artificial neural networks

    Walid M. Abdelmoula;Begona Gimenez Cassina Lopez;Elizabeth C. Randall;Tina Kapur

  • 3-T MR-guided brachytherapy for gynecologic malignancies.

    Tina Kapur;Jan Egger;Antonio Damato;Ehud J. Schmidt

  • Increasing the impact of medical image computing using community-based open-access hackathons: The NA-MIC and 3D Slicer experience.

    Tina Kapur;Steve Pieper;Andriy Fedorov;J. C. Fillion-Robin

  • SlicerDMRI: Diffusion MRI and Tractography Research Software for Brain Cancer Surgery Planning and Visualization

    Fan Zhang;Thomas Noh;Parikshit Juvekar;Sarah F. Frisken

  • Square-Cut: A Segmentation Algorithm on the Basis of a Rectangle Shape

    Jan Egger;Jan Egger;Tina Kapur;Thomas Dukatz;Malgorzata Kolodziej

  • Challenges in Image-Guided Therapy System Design

    Simon Dimaio;Tina Kapur;Kevin Cleary;Stephen Aylward

  • Automatic Needle Segmentation and Localization in MRI With 3-D Convolutional Neural Networks: Application to MRI-Targeted Prostate Biopsy

    Alireza Mehrtash;Mohsen Ghafoorian;Guillaume Pernelle;Alireza Ziaei

  • Fully automatic catheter segmentation in MRI with 3D convolutional neural networks: application to MRI-guided gynecologic brachytherapy.

    Paolo Zaffino;Guillaume Pernelle;Andre Mastmeyer;Alireza Mehrtash

Frequent Co-Authors

Clare M. Tempany
Clare M. Tempany Brigham and Women's Hospital
Ron Kikinis
Ron Kikinis Brigham and Women's Hospital
Jan Egger
Jan Egger University of Graz
Steve Pieper
Steve Pieper Brigham and Women's Hospital
Purang Abolmaesumi
Purang Abolmaesumi University of British Columbia
Alexandra J. Golby
Alexandra J. Golby Brigham and Women's Hospital
Christopher Nimsky
Christopher Nimsky Philipp University of Marburg
Bernd Freisleben
Bernd Freisleben Philipp University of Marburg
Paul L. Nguyen
Paul L. Nguyen Harvard Medical School

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

As computer science continues to evolve, related disciplines offer unique online study options and diverse career prospects. Many students considering technology fields also explore degrees in engineering and the sciences, which are now widely available online.

For those seeking a fast track into tech careers, a 2-year computer science degree online provides flexibility and a quicker route to job opportunities in programming, software development, and IT support.

Other technical pathways include engineering and applied sciences. For example, an environmental engineer degree online prepares graduates for sustainability and green technology roles, while an online degree in mechanical engineering is ideal for those interested in product design and advanced manufacturing.

Students interested in the fundamentals of science can pursue an online theoretical physics degree, opening the door to research, data analysis, and technology innovation roles. These related online degrees allow for flexible, affordable learning while expanding your career pathways in STEM fields.

Best Scientists Citing Tina Kapur

Trending Scientists

Recently Published Articles