Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (11A): 620-624.doi: 10.11896/jsjkx.201200252

• Interdiscipline & Application • Previous Articles     Next Articles

Image Quality Assessment for Low-dose-CT Images of COVID-19 Based on DenseNet and Mixed Domain Attention

SUN Rong-rong1, SHAN Fei2, YE Wen2   

  1. 1 Shanghai Institute of Measurement and Testing Technology,Shanghai 201203,China
    2 Shanghai Public Health Clinical Center,Shanghai 201508,China
  • Online:2021-11-10 Published:2021-11-12
  • About author:SUN Rong-rong,born in 1981,Ph.D,senior engineer.Her main research interests include medical metrology,biomedical engineering,medical images with artificial intelligence and so on.
  • Supported by:
    Natural Science Foundation Project of “Science and Technology Innovation Action Plan” of Shanghai in 2021 (21ZR1479700) and Key Discipline Construction Project of the Three Year Action Plan for the Construction of Shanghai Public Health System (2020－2022) Nuclear Medicine and Radiological Hygiene (GWV-10.1-XK10).

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Abstract: It is important to study the image quality assessment algorithm of low-dose-CT images for COVID-19.However,with the increase of the number of network layers,the gradient will disappear for the method based on deep learning.To solve this problem,this paper proposes DenseNet algorithm based on mixed domain attention.DenseNet solves the problem of gradient vanishing while reducing parameters through feature reuse and tight connection of network.Based on the attention mechanism of human vision,it adopts the combination of bottom-up and top-down structure to realize spatial attention.Based on the multi-channel characteristics of human vision,this paper ignores the information in the channel domain for spatial attention,studies and introduces the mixed domain attention to DenseNet.Spearman rank order correlation coefficient and Pearson linear correlation coefficient are used to measure the consistency between objective assessment method and subjective assessment method.The experimental results show that this method can simulate the human visual characteristics better,and evaluate the quality of low-dose-CT more accurately.The evaluation results are in good agreement with the subjective feelings of human vision.

Key words: COVID-19, CT images, DenseNet, Low-dose, Mixed domain attention

CLC Number: 

  • TP391
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