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Computer Science

D-Index
33
Citations
4318
World Ranking
12736
National Ranking
1570

Overview

Yaoqin Xie is affiliated with the Chinese Academy of Sciences in China. Their research spans multiple fields particularly focused on Medicine, Computer Science, and Engineering, with a significant concentration in subfields such as Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, Computer Vision and Pattern Recognition, Radiation, and Artificial Intelligence.

The scientist's work predominantly covers topics related to Radiomics and Machine Learning in Medical Imaging, Medical Imaging Techniques and Applications, Advanced Radiotherapy Techniques, AI in cancer detection, Medical Imaging and Analysis, Advanced X-ray and CT Imaging, and Medical Image Segmentation Techniques.

Yaoqin Xie has a record of publications in various journals and conference venues, including:

  • arXiv (Cornell University)
  • Bioengineering
  • Computers in Biology and Medicine
  • Medical Image Analysis
  • IEEE Journal of Biomedical and Health Informatics

The following recent papers illustrate the scope of their research:

  • Magnetic resonance image (MRI) synthesis from brain computed tomography (CT) images based on deep learning methods for magnetic resonance (MR)-guided radiotherapy, 2020, Quantitative Imaging in Medicine and Surgery
  • Noninvasive Prediction of Occult Peritoneal Metastasis in Gastric Cancer Using Deep Learning, 2021, JAMA Network Open
  • Incorporating the hybrid deformable model for improving the performance of abdominal CT segmentation via multi-scale feature fusion network, 2021, Medical Image Analysis
  • Radiographical assessment of tumour stroma and treatment outcomes using deep learning: a retrospective, multicohort study, 2021, The Lancet Digital Health
  • Comparison of Supervised and Unsupervised Deep Learning Methods for Medical Image Synthesis between Computed Tomography and Magnetic Resonance Images, 2020, BioMed Research International

Coauthorship patterns highlight frequent collaboration with researchers such as Xiaokun Liang, Wenjian Qin, Chulong Zhang, Jingjing Dai, and Wenfeng He, with the highest number of joint publications with Xiaokun Liang.

Best Publications

  • A Sparse-View CT Reconstruction Method Based on Combination of DenseNet and Deconvolution

    Zhicheng Zhang;Xiaokun Liang;Xu Dong;Yaoqin Xie

  • Scatter correction for cone-beam CT in radiation therapy.

    Lei Zhu;Yaoqin Xie;Jing Wang;Lei Xing

  • Intrafractional motion of the prostate during hypofractionated radiotherapy.

    Yaoqin Xie;David Djajaputra;Christopher R. King;Sabbir Hossain

  • Objective assessment of deformable image registration in radiotherapy: A multi-institution study

    Rojano Kashani;Martina Hub;James M. Balter;Marc L. Kessler

  • A Technical Review of Convolutional Neural Network-Based Mammographic Breast Cancer Diagnosis.

    Lian Zou;Shaode Yu;Shaode Yu;Tiebao Meng;Zhicheng Zhang

  • Magnetic resonance image (MRI) synthesis from brain computed tomography (CT) images based on deep learning methods for magnetic resonance (MR)-guided Radiotherapy

    Wen Li;Yafen Li;Wenjian Qin;Xiaokun Liang

  • Breast mass lesion classification in mammograms by transfer learning

    Fan Jiang;Hui Liu;Shaode Yu;Yaoqin Xie

  • A Feasibility of Respiration Prediction Based on Deep Bi-LSTM for Real-Time Tumor Tracking

    Ran Wang;Xiaokun Liang;Xuanyu Zhu;Yaoqin Xie

  • Auto-propagation of contours for adaptive prostate radiation therapy.

    Ming Chao;Yaoqin Xie;Lei Xing

  • Evaluation of various speckle reduction filters on medical ultrasound images

    Shibin Wu;Qingsong Zhu;Yaoqin Xie

  • Robust Segmentation of Intima–Media Borders With Different Morphologies and Dynamics During the Cardiac Cycle

    Shen Zhao;Zhifan Gao;Heye Zhang;Yaoqin Xie

  • Feature‐based rectal contour propagation from planning CT to cone beam CT

    Yaoqin Xie;Ming Chao;Percy Lee;Lei Xing

  • A Novel Wearable Electrocardiogram Classification System Using Convolutional Neural Networks and Active Learning

    Yufa Xia;Yaoqin Xie

  • Iterative image-domain ring artifact removal in cone-beam CT

    Xiaokun Liang;Zhicheng Zhang;Tianye Niu;Shaode Yu

  • Learning based alpha matting using support vector regression

    Zhanpeng Zhang;Qingsong Zhu;Yaoqin Xie

  • A shallow convolutional neural network for blind image sharpness assessment.

    Shaode Yu;Shibin Wu;Lei Wang;Fan Jiang

  • Transferring deep neural networks for the differentiation of mammographic breast lesions

    ShaoDe Yu;LingLing Liu;ZhaoYang Wang;GuangZhe Dai

  • Incorporating the hybrid deformable model for improving the performance of abdominal CT segmentation via multi-scale feature fusion network.

    Xiaokun Liang;Na Li;Zhicheng Zhang;Jing Xiong

  • Cone Beam X-ray Luminescence Computed Tomography Based on Bayesian Method

    Guanglei Zhang;Fei Liu;Jie Liu;Jianwen Luo

  • A Novel Recursive Bayesian Learning-Based Method for the Efficient and Accurate Segmentation of Video With Dynamic Background

    Qingsong Zhu;Zhan Song;Yaoqin Xie;Lei Wang

  • Using Edge-Preserving Algorithm with Non-local Mean for Significantly Improved Image-Domain Material Decomposition in Dual Energy CT

    Wei Zhao;Tianye Niu;Lei Xing;Yaoqin Xie

  • TU‐C‐M100J‐03: Objective Assessment of Deformable Image Registration in Radiotherapy — a Multi‐Institution Study

    R Kashani;J Balter;M Kessler;M Hub

Frequent Co-Authors

Lei Xing
Lei Xing Stanford University
Xizhang Wang
Xizhang Wang Nanjing University
Tianmiao Wang
Tianmiao Wang Beihang University
Lei Wang
Lei Wang University of California, San Francisco
Ling Shao
Ling Shao Terminus International
Song Gao
Song Gao University of Wisconsin–Madison
Shu-Hong Yu
Shu-Hong Yu University of Science and Technology of China
Yong Yang
Yong Yang Chinese Academy of Sciences
Sarang Joshi
Sarang Joshi University of Utah
Julia A. Schnabel
Julia A. Schnabel King's College London

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