Advanced Technologies in Healthcare by Shuli Guo & Lina Han & Yanan Guo

Author:Shuli Guo & Lina Han & Yanan Guo
Language: eng
Format: epub
ISBN: 9789819995851
Publisher: Springer Nature Singapore

Wang et al. [5] proposed a denoising method based on wavelet transform combined with improved particle swam optimization (PSO) to solve the problem that asymptomatic COVID-19 CT image often have small flake ground-glass shadow in the early lesions, and the density is low, which is easily confused with noise. Figure 3.12 shows the flow chart of wavelet transform combined with improved PSO. Aiming at the problems of low contrast and fuzzy boundary in the traditional wavelet transform, the threshold function based on the optimization of parameters combined with the improved PSO is proposed, so that the parameters of wavelet threshold function can change adaptively according to the lung lobe and ground-glass lesions with fewer iterations. The simulation results show that the paper method is significantly better than other algorithms in peak signal-to-noise ratio (PSNR), signal-to-noise ratio (SNR) and mean absolute error (MSE).

Fig. 3.12Flow chart of wavelet transform combined with improved PSO [5]

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