A Methodology to Train a Convolutional Neural Network-Based Low-Dose CT Denoiser With an Accurate Image Domain Noise Insertion Technique

A Methodology to Train a Convolutional Neural Network-Based Low-Dose CT Denoiser With an Accurate Image Domain Noise Insertion Technique

To mitigate the public health risks associated with the increasing utilization of computed tomography (CT), it is desirable to implement a low-dose scanning protocol. However, low-dose CT produces poor image quality due to the increased quantum noise, requiring an effective image denoising method fo...

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Bibliographic Details
Main Authors: Byeongjoon Kim, Sarah E. Divel, Norbert J. Pelc, Jongduk Baek
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Computed tomography (CT)
low-dose CT
noise modeling
image denoising
convolutional neural network
Online Access:https://ieeexplore.ieee.org/document/9857880/

Internet

https://ieeexplore.ieee.org/document/9857880/

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