Metal Artifact Reduction for X-Ray Computed Tomography Using U-Net in Image Domain

Metal Artifact Reduction for X-Ray Computed Tomography Using U-Net in Image Domain

Metal artifacts seriously degrade the quality of the CT data and bring great difficulties to subsequent image processing and analysis, which nowadays become a great concern in X-ray CT applications. In this paper, we introduce a U-net-based metal artifact reduction method into CT image domain. The p...

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Bibliographic Details
Main Authors: Linlin Zhu, Yu Han, Lei Li, Xiaoqi Xi, Mingwan Zhu, Bin Yan
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Computed tomography
metal artifact reduction
deep learning
convolutional neural network
U-net
Online Access:https://ieeexplore.ieee.org/document/8768364/

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