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Dong Nie

D-Index & Metrics

Computer Science

D-Index
36
Citations
7882
World Ranking
11050
National Ranking
4593

Dong Nie 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 Dong Nie 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: 73 publications — 2nd percentile

2% of scientists in this discipline score the same or lower.

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

Dong Nie 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 Dong Nie 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: 36 D-Index — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Overview

Dong Nie is a researcher affiliated with the University of North Carolina at Chapel Hill in the United States. Their work spans several intersecting fields, including computer science, medicine, and engineering. The primary areas of study focus on computer vision and pattern recognition, radiology, nuclear medicine and imaging, artificial intelligence, biomedical engineering, and neurology.

The research topics covered by Dong Nie include:

  • Radiomics and machine learning in medical imaging
  • Advanced neural network applications
  • Medical image segmentation techniques
  • Medical imaging and analysis
  • Medical imaging techniques and applications
  • AI in cancer detection
  • Brain tumor detection and classification

Dong Nie has published papers in various scientific venues, commonly in journals and conferences related to medical imaging and artificial intelligence. Frequent publication venues include:

  • UNC Libraries
  • arXiv (Cornell University)
  • IEEE Transactions on Medical Imaging
  • Medical Image Analysis
  • Knowledge-Based Systems

Several coauthors have frequently collaborated with Dong Nie, including:

  • Dinggang Shen
  • Qian Wang
  • Jun Lian
  • Zhenyu Tang
  • Xuyun Wen

Examples of recent research papers authored or coauthored by Dong Nie cover topics such as medical image segmentation, crowd counting, and radiotherapy dose prediction. Selected recent publications include:

  • "Unified medical image segmentation by learning from uncertainty in an end-to-end manner" (2022), published in Knowledge-Based Systems
  • "Hybrid Graph Neural Networks for Crowd Counting" (2020), published in Proceedings of the AAAI Conference on Artificial Intelligence
  • "HF-UNet: Learning Hierarchically Inter-Task Relevance in Multi-Task U-Net for Accurate Prostate Segmentation in CT Images" (2021), published in IEEE Transactions on Medical Imaging
  • "Adversarial Confidence Learning for Medical Image Segmentation and Synthesis" (2020), published in International Journal of Computer Vision
  • "Explainable attention guided adversarial deep network for 3D radiotherapy dose distribution prediction" (2022), published in Knowledge-Based Systems

Best Publications

  • Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

    Spyridon Bakas;Mauricio Reyes;Andras Jakab;Stefan Bauer

  • Medical Image Synthesis with Context-Aware Generative Adversarial Networks

    Dong Nie;Roger Trullo;Jun Lian;Caroline Petitjean

  • Medical Image Synthesis with Deep Convolutional Adversarial Networks

    Dong Nie;Roger Trullo;Jun Lian;Li Wang

  • 3D Deep Learning for Multi-modal Imaging-Guided Survival Time Prediction of Brain Tumor Patients.

    Dong Nie;Han Zhang;Ehsan Adeli;Luyan Liu

  • Fully convolutional networks for multi-modality isointense infant brain image segmentation

    Dong Nie;Li Wang;Yaozong Gao;Dinggang Sken

  • Deep auto-context convolutional neural networks for standard-dose PET image estimation from low-dose PET/MRI

    Lei Xiang;Yu Qiao;Dong Nie;Le An

  • Estimating CT Image from MRI Data Using 3D Fully Convolutional Networks.

    Dong Nie;Xiaohuan Cao;Yaozong Gao;Li Wang

  • ASDNet: Attention Based Semi-supervised Deep Networks for Medical Image Segmentation

    Dong Nie;Yaozong Gao;Li Wang;Dinggang Shen

  • Deformable Image Registration based on Similarity-Steered CNN Regression.

    Xiaohuan Cao;Jianhua Yang;Jun Zhang;Dong Nie

  • High-Resolution Encoder–Decoder Networks for Low-Contrast Medical Image Segmentation

    Sihang Zhou;Dong Nie;Ehsan Adeli;Jianping Yin

  • Multi-Channel 3D Deep Feature Learning for Survival Time Prediction of Brain Tumor Patients Using Multi-Modal Neuroimages

    Dong Nie;Junfeng Lu;Han Zhang;Ehsan Adeli

  • Benchmark on Automatic Six-Month-Old Infant Brain Segmentation Algorithms: The iSeg-2017 Challenge

    Li Wang;Dong Nie;Guannan Li;Elodie Puybareau

  • Deep embedding convolutional neural network for synthesizing CT image from T1-Weighted MR image.

    Lei Xiang;Qian Wang;Dong Nie;Lichi Zhang

  • 3-D Fully Convolutional Networks for Multimodal Isointense Infant Brain Image Segmentation

    Dong Nie;Li Wang;Ehsan Adeli;Cuijin Lao

  • Interleaved 3D-CNNs for joint segmentation of small-volume structures in head and neck CT images

    Xuhua Ren;Lei Xiang;Dong Nie;Yeqin Shao

  • Anatomical Landmark Based Deep Feature Representation for MR Images in Brain Disease Diagnosis

    Mingxia Liu;Jun Zhang;Dong Nie;Pew-Thian Yap

  • Pelvic Organ Segmentation Using Distinctive Curve Guided Fully Convolutional Networks

    Kelei He;Xiaohuan Cao;Yinghuan Shi;Dong Nie

  • Segmentation of Organs at Risk in thoracic CT images using a SharpMask architecture and Conditional Random Fields

    R. Trullo;C. Petitjean;S. Ruan;B. Dubray

  • CT male pelvic organ segmentation using fully convolutional networks with boundary sensitive representation.

    Shuai Wang;Kelei He;Dong Nie;Sihang Zhou

  • HF-UNet: Learning Hierarchically Inter-Task Relevance in Multi-Task U-Net for Accurate Prostate Segmentation in CT Images

    Kelei He;Chunfeng Lian;Bing Zhang;Xin Zhang

  • Medical Image Synthesis with Context-Aware Generative Adversarial Networks

    Dong Nie;Roger Trullo;Caroline Petitjean;Su Ruan

Frequent Co-Authors

Dinggang Shen
Dinggang Shen ShanghaiTech University
Qian Wang
Qian Wang Shanghai Jiao Tong University
Yaozong Gao
Yaozong Gao United Imaging Healthcare (China)
Ehsan Adeli
Ehsan Adeli Stanford University
Tingshao Zhu
Tingshao Zhu University of Chinese Academy of Sciences
Su Ruan
Su Ruan University of Rouen
Weili Lin
Weili Lin University of North Carolina at Chapel Hill
Han Zhang
Han Zhang ShanghaiTech University
Gang Li
Gang Li University of North Carolina at Chapel Hill
Feng Shi
Feng Shi United Imaging Intelligence (China)

External Links

Personal website of Dong Nie

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Best Scientists Citing Dong Nie

Dinggang Shen

Dinggang Shen

ShanghaiTech University

Publications: 122

Weili Lin

Weili Lin

University of North Carolina at Chapel Hill

Publications: 36

Gang Li

Gang Li

University of North Carolina at Chapel Hill

Publications: 30

Baiying Lei

Baiying Lei

Shenzhen University

Publications: 27

Sebastien Ourselin

Sebastien Ourselin

King's College London

Publications: 26

Tonghe Wang

Tonghe Wang

Memorial Sloan Kettering Cancer Center

Publications: 25

Mingxia Liu

Mingxia Liu

University of North Carolina at Chapel Hill

Publications: 23

Bjoern H. Menze

Bjoern H. Menze

University of Zurich

Publications: 22

Qian Wang

Qian Wang

Shanghai Jiao Tong University

Publications: 22

Pheng-Ann Heng

Pheng-Ann Heng

Chinese University of Hong Kong

Publications: 21

Walter J. Curran

Walter J. Curran

Emory University

Publications: 21

Yang Lei

Yang Lei

University of Nevada Reno

Publications: 21

Lequan Yu

Lequan Yu

University of Hong Kong

Publications: 20

Pew Thian Yap

Pew Thian Yap

University of North Carolina at Chapel Hill

Publications: 20

Jiliu Zhou

Jiliu Zhou

Sichuan University

Publications: 20

Jose Dolz

Jose Dolz

École de Technologie Supérieure

Publications: 19

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