Abstract
This study was to analyze the ultrasound imaging characteristics of infectious pneumonia of newborn in different conditions and the differences in neurobehavioral development. An adaptive image denoising (AID) algorithm was constructed based on multiscale wavelet features. It was compared with the transform domain denoising (TDD) algorithm and spatial domain denoising (SDD) algorithm and applied to ultrasound images of newborns with infectious pneumonia. It was found that the peak signal-to-noise ratio (PSNR), structural similarity (SSIM), and feature similarity index (FSIM) of the constructed algorithm were higher than those of the TDD and SDD algorithms ( P < 0.05 ). The ultrasound scores of newborns in noncritical group (group A, 1.54 ± 0.62 scores) were all lower than those of the critical group (group B, 3.96 ± 0.41 scores) and extremely critical group (group C, 4.25 ± 0.35 scores) ( P < 0.05 ). The behavioral ability, passive muscle tension, active muscle tension, and original reflection of the newborns in group A were better than other groups ( P < 0.05 ). It indicated that the constructed algorithm showed better denoising effect on ultrasound images, which could effectively evaluate the severity of newborns’ infectious pneumonia.
Highlights
Infectious pneumonia is a common disease of newborns and the most common form of newborn infections and an important cause of death
45 newborns with jaundice who came to the hospital during the same period were selected and included in the group C. ere were 25 males and 20 females, with the age of 1–30 days. e newborns in experimental group were grouped into a noncritical group, a critical group, and an extremely critical group based on the severity evaluated by lung ultrasound score (LUS). e study had been approved by the medical ethics committee of the hospital, and the newborn family members had learned about the study and signed the informed consent forms
Active muscular tension effective examination method is an urgent problem that needs to be solved in the clinic [16]. erefore, an adaptive image denoising (AID) algorithm was constructed based on multiscale wavelet features and compared with the transform domain denoising (TDD) algorithm and spatial domain denoising (SDD) algorithm in this study
Summary
Infectious pneumonia is a common disease of newborns and the most common form of newborn infections and an important cause of death. Statistics shows that the death rate of newborn from infectious pneumonia during the perinatal period is about 15% [1, 2]. It is mainly induced by different pathogens such as bacteria, viruses, protozoa, and fungi. Erefore, it is urgent to find a diagnostic method with high coincidence rate. If it cannot be detected in time and treated with anti-infective treatment, the sick newborn is very likely to be complicated by persistent pulmonary hypertension, heart enlargement, liver enlargement, and other heart failure manifestations. Children with severe meconium aspiration and acute hypoxia may have central nervous system symptoms such as disturbance of consciousness, increased intracranial pressure, convulsions, increased red blood cell, hypoglycemia, and hypocalcemia [6]
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