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D-Index
41
Citations
6770
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606
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89

Computer Science

D-Index
42
Citations
7073
World Ranking
8422
National Ranking
3606

Yang Lei 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 Yang Lei 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: 242 publications — 60th percentile

60% of scientists in this discipline score the same or lower.

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

Yang Lei 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 Yang Lei 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: 42 D-Index — 43rd percentile

43% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Yang Lei is a researcher affiliated with the University of Nevada Reno in the United States. Their work spans primarily across the fields of Medicine and Computer Science, with significant contributions to Radiology, Nuclear Medicine and Imaging, and Computer Vision and Pattern Recognition. The research also addresses specialized areas such as Pulmonary and Respiratory Medicine, Radiation, and Biomedical Engineering.

The scientist's research topics cover a range of advanced medical technologies and methods, including:

  • Advanced Radiotherapy Techniques
  • Medical Imaging Techniques and Applications
  • Radiomics and Machine Learning in Medical Imaging
  • Advanced X-ray and CT Imaging
  • Advanced Neural Network Applications
  • Medical Imaging and Analysis
  • Radiation Therapy and Dosimetry

Yang Lei's recent published papers include:

  • Deep learning in medical image registration: a review, 2020, Physics in Medicine and Biology
  • A review on medical imaging synthesis using deep learning and its clinical applications, 2020, Journal of Applied Clinical Medical Physics
  • A review of deep learning based methods for medical image multi-organ segmentation, 2021, Physica Medica
  • Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography, 2020, Cell
  • CBCT-based synthetic CT generation using deep-attention cycleGAN for pancreatic adaptive radiotherapy, 2020, Medical Physics

The venues where Yang Lei frequently publishes reflect an emphasis on interdisciplinary and highly specialized domains. These venues include:

  • arXiv (Cornell University)
  • Medical Physics
  • Physics in Medicine and Biology
  • International Journal of Radiation Oncology*Biology*Physics
  • SSRN Electronic Journal

Collaboration plays a notable role in their research, with frequent co-authors comprising Xiaofeng Yang, Tonghe Wang, Walter J. Curran, Tian Liu, and Justin Roper. These partnerships indicate an extensive network within the medical imaging and radiotherapy community.

Best Publications

  • Deep learning in medical image registration: a review.

    Yabo Fu;Yang Lei;Tonghe Wang;Walter J Curran

  • MRI-only based synthetic CT generation using dense cycle consistent generative adversarial networks.

    Yang Lei;Joseph Harms;Tonghe Wang;Yingzi Liu

  • Automatic multiorgan segmentation in thorax CT images using U-net-GAN.

    Xue Dong;Yang Lei;Tonghe Wang;Matthew Thomas

  • Paired cycle-GAN-based image correction for quantitative cone-beam computed tomography

    Joseph Harms;Yang Lei;Tonghe Wang;Rongxiao Zhang

  • A review on medical imaging synthesis using deep learning and its clinical applications.

    Tonghe Wang;Yang Lei;Yabo Fu;Jacob F. Wynne

  • A review of deep learning based methods for medical image multi-organ segmentation.

    Yabo Fu;Yang Lei;Tonghe Wang;Walter J. Curran

  • Deeply supervised 3D fully convolutional networks with group dilated convolution for automatic MRI prostate segmentation

    Bo Wang;Bo Wang;Yang Lei;Sibo Tian;Tonghe Wang

  • Synthetic MRI-aided multi-organ segmentation on male pelvic CT using cycle consistent deep attention network.

    Xue Dong;Yang Lei;Sibo Tian;Tonghe Wang

  • Ultrasound prostate segmentation based on multidirectional deeply supervised V-Net

    Yang Lei;Sibo Tian;Xiuxiu He;Tonghe Wang

  • Synthetic CT generation from non-attenuation corrected PET images for whole-body PET imaging.

    Xue Dong;Tonghe Wang;Yang Lei;Kristin Higgins

  • Deep learning-based attenuation correction in the absence of structural information for whole-body positron emission tomography imaging.

    Xue Dong;Yang Lei;Tonghe Wang;Kristin Higgins

  • Male Pelvic Multi-Organ Segmentation Aided by CBCT-based Synthetic MRI

    Yang Lei;Tonghe Wang;Sibo Tian;Xue Dong

  • A learning-based automatic segmentation and quantification method on left ventricle in gated myocardial perfusion SPECT imaging: A feasibility study

    Tonghe Wang;Yang Lei;Haipeng Tang;Zhuo He

  • CT prostate segmentation based on synthetic MRI-aided deep attention fully convolution network.

    Yang Lei;Xue Dong;Zhen Tian;Yingzi Liu

  • Whole-body PET estimation from low count statistics using cycle-consistent generative adversarial networks

    Yang Lei;Xue Dong;Tonghe Wang;Kristin Higgins

  • MRI-based treatment planning for proton radiotherapy: dosimetric validation of a deep learning-based liver synthetic CT generation method.

    Yingzi Liu;Yang Lei;Yinan Wang;Tonghe Wang

  • LungRegNet: An unsupervised deformable image registration method for 4D-CT lung.

    Yabo Fu;Yang Lei;Tonghe Wang;Kristin Higgins

  • Breast tumor segmentation in 3D automatic breast ultrasound using Mask scoring R-CNN.

    Yang Lei;Xiuxiu He;Jincao Yao;Tonghe Wang

  • MRI-based treatment planning for liver stereotactic body radiotherapy: validation of a deep learning-based synthetic CT generation method

    Yingzi Liu;Yang Lei;Tonghe Wang;Oluwatosin Kayode

  • 4D-CT deformable image registration using multiscale unsupervised deep learning.

    Yang Lei;Yabo Fu;Tonghe Wang;Yingzi Liu

  • Automatic multi-organ segmentation in thorax CT images using U-Net-GAN

    Yang Lei;Yingzi Liu;Xue Dong;Sibo Tian

Frequent Co-Authors

Walter J. Curran
Walter J. Curran Emory University
Tonghe Wang
Tonghe Wang Memorial Sloan Kettering Cancer Center

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