World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
44
Citations
7624
World Ranking
5805
National Ranking
1625

Overview

Tonghe Wang is affiliated with the Memorial Sloan Kettering Cancer Center in the United States. Their research primarily focuses on the field of medicine with a specialized emphasis on radiology, nuclear medicine and imaging, biomedical engineering, radiation, computer vision and pattern recognition, as well as pulmonary and respiratory medicine.

Their work encompasses a range of topics including:

  • Medical Imaging Techniques and Applications
  • Advanced Radiotherapy Techniques
  • 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

Some of their recent publications are:

  • A review on medical imaging synthesis using deep learning and its clinical applications, 2020, Journal of Applied Clinical Medical Physics
  • Deep learning in medical image registration: a review, 2020, Physics in Medicine and Biology
  • A review of deep learning based methods for medical image multi-organ segmentation, 2021, Physica Medica
  • CBCT-based synthetic CT generation using deep-attention cycleGAN for pancreatic adaptive radiotherapy, 2020, Medical Physics
  • 2D medical image synthesis using transformer-based denoising diffusion probabilistic model, 2023, Physics in Medicine and Biology

They have frequently published in venues such as:

  • Medical Physics
  • arXiv (Cornell University)
  • Physics in Medicine and Biology
  • Journal of Applied Clinical Medical Physics
  • Medical Imaging 2020: Physics of Medical Imaging

Frequent collaborators in their academic career include Xiaofeng Yang, Yang Lei, Walter J. Curran, Justin Roper, and Tian Liu. These co-authors have contributed significantly in partnership on multiple research projects.

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

  • Evaluation of a deep learning-based pelvic synthetic CT generation technique for MRI-based prostate proton treatment planning.

    Yingzi Liu;Yang Lei;Yinan Wang;Ghazal Shafai-Erfani

  • 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

  • Machine learning in quantitative PET: A review of attenuation correction and low-count image reconstruction methods.

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

  • Biomechanically constrained non-rigid MR-TRUS prostate registration using deep learning based 3D point cloud matching.

    Yabo Fu;Yang Lei;Tonghe Wang;Pretesh Patel

  • MRI-based attenuation correction for brain PET/MRI based on anatomic signature and machine learning

    Xiaofeng Yang;Tonghe Wang;Yang Lei;Kristin Higgins

  • CT-based multi-organ segmentation using a 3D self-attention U-net network for pancreatic radiotherapy

    Yingzi Liu;Yang Lei;Yabo Fu;Tonghe Wang

  • Multi-Needle Detection in 3D Ultrasound Images Using Unsupervised Order-Graph Regularized Sparse Dictionary Learning

    Yupei Zhang;Xiuxiu He;Zhen Tian;Jiwoong Jason Jeong

  • Label-driven magnetic resonance imaging (MRI)-transrectal ultrasound (TRUS) registration using weakly supervised learning for MRI-guided prostate radiotherapy.

    Qiulan Zeng;Yabo Fu;Zhen Tian;Yang Lei

  • Dose evaluation of MRI-based synthetic CT generated using a machine learning method for prostate cancer radiotherapy.

    Ghazal Shafai-Erfani;Tonghe Wang;Yang Lei;Sibo Tian

  • Head-and-neck organs-at-risk auto-delineation using dual pyramid networks for CBCT-guided adaptive radiotherapy.

    Xianjin Dai;Yang Lei;Tonghe Wang;Anees H Dhabaan

  • Deep learning-based image quality improvement for low-dose computed tomography simulation in radiation therapy.

    Tonghe Wang;Yang Lei;Zhen Tian;Xue Dong

  • Magnetic resonance imaging-based pseudo computed tomography using anatomic signature and joint dictionary learning.

    Yang Lei;Hui-Kuo Shu;Sibo Tian;Jiwoong Jason Jeong

  • Automated prostate segmentation of volumetric CT images using 3D deeply supervised dilated FCN

    Bo Wang;Bo Wang;Yang Lei;Tonghe Wang;Xue Dong

Frequent Co-Authors

Yang Lei
Yang Lei University of Nevada Reno
Walter J. Curran
Walter J. Curran Emory University

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