World's Best Scientists 2026 revealed!

Overview

Jiliu Zhou is affiliated with Sichuan University in China and has made contributions primarily in the intersection of medicine, computer science, and engineering. Their research has a strong focus on medical imaging techniques and related computational methods.

The main fields of study for Zhou include:

  • Medicine
  • Computer Science
  • Engineering

Within these broader disciplines, Zhou's work is concentrated on specialized subfields such as:

  • Radiology, Nuclear Medicine and Imaging
  • Computer Vision and Pattern Recognition
  • Radiation
  • Biomedical Engineering
  • Media Technology

The topics often addressed in Zhou's publications cover various advanced aspects of medical imaging and image processing, including:

  • Medical Imaging Techniques and Applications
  • Radiomics and Machine Learning in Medical Imaging
  • Advanced Image Processing Techniques
  • Advanced X-ray and CT Imaging
  • Image and Signal Denoising Methods
  • Image Processing Techniques and Applications
  • Generative Adversarial Networks and Image Synthesis

Zhou has contributed to numerous scientific articles, including recent publications such as:

  • Semi-supervised medical image segmentation via a tripled-uncertainty guided mean teacher model with contrastive learning, 2022, Medical Image Analysis
  • Unified medical image segmentation by learning from uncertainty in an end-to-end manner, 2022, Knowledge-Based Systems
  • Adaptive rectification based adversarial network with spectrum constraint for high-quality PET image synthesis, 2021, Medical Image Analysis
  • Semi-supervised medical image segmentation via hard positives oriented contrastive learning, 2023, Pattern Recognition
  • Edge-preserving MRI image synthesis via adversarial network with iterative multi-scale fusion, 2021, Neurocomputing

These publications are featured in frequent venues, reflecting Zhou's active engagement in the scientific community:

  • arXiv (Cornell University)
  • Medical Image Analysis
  • Pattern Recognition
  • 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)
  • Knowledge-Based Systems

Zhou maintains collaborative relationships with several coauthors who frequently appear in their work. Notable collaborators include:

  • Yan Wang
  • Dinggang Shen
  • Yi Zhang
  • Wenjun Xia
  • Luping Zhou

Best Publications

  • Low-Dose CT With a Residual Encoder-Decoder Convolutional Neural Network

    Hu Chen;Yi Zhang;Mannudeep K. Kalra;Feng Lin

  • Low-dose CT via convolutional neural network

    Hu Chen;Yi Zhang;Weihua Zhang;Peixi Liao

  • Fractional Differential Mask: A Fractional Differential-Based Approach for Multiscale Texture Enhancement

    Yi-Fei Pu;Ji-Liu Zhou;Xiao Yuan

  • Low-Dose CT with a Residual Encoder-Decoder Convolutional Neural Network (RED-CNN)

    Hu Chen;Yi Zhang;Mannudeep K. Kalra;Feng Lin

  • LEARN: Learned Experts’ Assessment-Based Reconstruction Network for Sparse-Data CT

    Hu Chen;Yi Zhang;Yunjin Chen;Junfeng Zhang

  • 3D conditional generative adversarial networks for high-quality PET image estimation at low dose

    Yan Wang;Biting Yu;Lei Wang;Chen Zu

  • 3D Auto-Context-Based Locality Adaptive Multi-Modality GANs for PET Synthesis

    Yan Wang;Luping Zhou;Biting Yu;Lei Wang

  • Fractional Extreme Value Adaptive Training Method: Fractional Steepest Descent Approach

    Yi-Fei Pu;Ji-Liu Zhou;Yi Zhang;Ni Zhang

  • Denoising of 3D magnetic resonance images using a residual encoder-decoder Wasserstein generative adversarial network.

    Maosong Ran;Jinrong Hu;Yang Chen;Hu Chen

  • Low-dose CT denoising with convolutional neural network

    Hu Chen;Yi Zhang;Weihua Zhang;Peixi Liao

  • Fractional Hopfield Neural Networks: Fractional Dynamic Associative Recurrent Neural Networks

    Yi-Fei Pu;Zhang Yi;Ji-Liu Zhou

  • Spectral CT Reconstruction With Image Sparsity and Spectral Mean

    Yi Zhang;Yan Xi;Qingsong Yang;Wenxiang Cong

  • Simultaneous denoising and super-resolution of optical coherence tomography images based on generative adversarial network

    Yongqiang Huang;Zexin Lu;Zhimin Shao;Maosong Ran

  • Few-view image reconstruction with fractional-order total variation

    Yi Zhang;Weihua Zhang;Yinjie Lei;Jiliu Zhou

  • A Class of Fractional-Order Variational Image Inpainting Models

    Y. Zhang;Y.-F. Pu;J.-R. Hu;J.-L. Zhou

  • Statistical iterative reconstruction using adaptive fractional order regularization.

    Yi Zhang;Yan Wang;Weihua Zhang;Feng Lin

  • Edge detection of colour image based on quaternion fractional differential

    C.B. Gao;J.L. Zhou;J.R. Hu;F.N. Lang

  • MAGIC: Manifold and Graph Integrative Convolutional Network for Low-Dose CT Reconstruction.

    Wenjun Xia;Zexin Lu;Yongqiang Huang;Zuoqiang Shi

  • Convolutional Sparse Coding for Compressed Sensing CT Reconstruction

    Peng Bao;Huaiqiang Sun;Zhangyang Wang;Yi Zhang

  • Denoising of 3-D Magnetic Resonance Images Using a Residual Encoder-Decoder Wasserstein Generative Adversarial Network

    Maosong Ran;Jinrong Hu;Yang Chen;Hu Chen

Frequent Co-Authors

Ge Wang
Ge Wang Rensselaer Polytechnic Institute
Dinggang Shen
Dinggang Shen ShanghaiTech University
Zhang Yi
Zhang Yi Sichuan University
Feng Lin
Feng Lin Wayne State University
Leyuan Fang
Leyuan Fang Hunan University
Patrick Siarry
Patrick Siarry Paris-Est Créteil University
Hengyong Yu
Hengyong Yu University of Massachusetts Lowell
Yi Zhang
Yi Zhang Nanyang Technological University
Hongnian Yu
Hongnian Yu Edinburgh Napier University
Feng Shi
Feng Shi United Imaging Intelligence (China)

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