Inpainting the metal artifact region in MRI images by using generative adversarial networks with gated convolution-Reference-Cited by-同舟云学术

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Inpainting the metal artifact region in MRI images by using generative adversarial networks with gated convolution

Published:2022-08-31 Issue:10 Volume:49 Page:6424-6438
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Medical Physics

Author:

Xie Kai¹²,Gao Liugang¹²,Lu Zhengda²³,Li Chunying¹²,Xi Qianyi¹²,Zhang Fan¹²,Sun Jiawei¹²,Lin Tao¹²,Sui Jianfeng¹²,Ni Xinye¹²

Affiliation:

1. Radiotherapy Department Second People's Hospital of Changzhou Nanjing Medical University Changzhou China

2. Center for Medical Physics Nanjing Medical University Changzhou China

3. School of Biomedical Engineering and Informatics Nanjing Medical University Nanjing China

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.15931

Reference33 articles.

1. KwonK KimD ParkH.A learning‐based metal artifacts correction method for MRI using dual‐polarity readout gradients and simulated data.International Conference on Medical Image Computing and Computer‐Assisted Intervention.2018:189‐197.

2. ArabiH ZaidiH.Three‐dimensional shape completion using deep convolutional neural networks: application to truncation compensation and metal artifact reduction in PET/MRI attenuation correction.2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC).2019:1‐3.

3. A deep learning approach to generate synthetic CT in low field MR-guided adaptive radiotherapy for abdominal and pelvic cases

4. On the accuracy of bulk synthetic CT for MR-guided online adaptive radiotherapy

5. Metal About the Hip and Artifact Reduction Techniques: From Basic Concepts to Advanced Imaging

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3. GAN‐based metal artifacts region inpainting in brain MRI imaging with reflective registration;Medical Physics;2023-09-04

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