A densely connected LDCT image denoising network based on dual-edge extraction and multi-scale attention under compound loss.

Journal: Journal of X-ray science and technology
Published Date: Jan 1, 2023

Abstract

BACKGROUND: Low dose computed tomography (LDCT) uses lower radiation dose, but the reconstructed images contain higher noise that can have negative impact in disease diagnosis. Although deep learning with the edge extraction operators reserves edge information well, only applying the edge extraction operators to input LDCT images does not yield overall satisfactory results.

Authors

  • Jia Lina
    School of Physics and Electronic Engineering, Shanxi University, Taiyuan, China.
  • He Xu
    School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
  • Huang Aimin
    School of Physics and Electronic Engineering, Shanxi University, Taiyuan, China.
  • Jia Beibei
    School of Physics and Electronic Engineering, Shanxi University, Taiyuan, China.
  • Gui Zhiguo
    State Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan, China.

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