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2025

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606
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Computer Science

D-Index
42
Citations
7073
World Ranking
8423
National Ranking
3606

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  • 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

Tonghe Wang
Tonghe Wang Memorial Sloan Kettering Cancer Center

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