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Wavelet Transform Image Enhancement Algorithm-Based Evaluation of Lung Recruitment Effect and Nursing of Acute Respiratory Distress Syndrome by Ultrasound Image
This study aimed to analyze the application of ultrasound images of lung recruitment (LR) nursing treatment guided by positive-end expiratory pressure (PEEP) in patients with acute respiratory distress syndrome (ARDS). An ultrasound image enhancement algorithm (UIEA) wavelet transform (WT) was const...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8449728/ https://www.ncbi.nlm.nih.gov/pubmed/34545301 http://dx.doi.org/10.1155/2021/8960465 |
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author | Jin, Wangyan Dai, Ling Ge, Liuyan Huang, Xuhua Xu, Guanhua Qu, Chunhong Sun, Jianfei |
author_facet | Jin, Wangyan Dai, Ling Ge, Liuyan Huang, Xuhua Xu, Guanhua Qu, Chunhong Sun, Jianfei |
author_sort | Jin, Wangyan |
collection | PubMed |
description | This study aimed to analyze the application of ultrasound images of lung recruitment (LR) nursing treatment guided by positive-end expiratory pressure (PEEP) in patients with acute respiratory distress syndrome (ARDS). An ultrasound image enhancement algorithm (UIEA) wavelet transform (WT) was constructed, and the soft threshold (ST) and adjacent region average (ARA) were introduced for simulation comparison. In addition, the signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), and running time were undertaken as the evaluation indexes. The WT algorithm was applied to the ultrasound images of 85 ARDS patients before and after PEEP recruitment. The mean artery pressure (MAP), heart rate (HR), and central venous pressure (CVP), peak inspiratory pressure (Ppeak), mean inspiratory pressure (Pmean), dynamic lung compliance (DLC), PCO(2), and PaO(2)/FiO(2) of the patients were recorded before and after the LR. The results showed that the signal-to-noise ratio (SNR) (19.67 ± 3.15 dB) and PSNR (23.08 ± 2.08 dB) of the images enhanced by the WT algorithm were much higher than those of ST (13.88 ± 2.74 dB and 14.62 ± 1.76 dB, respectively) and ARA (14.96 ± 3.06 dB and 15.11 ± 1.94 dB, respectively), while the running time was in adverse (P < 0.05); the HR and CVP of patients after LR nursing treatment were increased greatly, while the MAP was in the opposite case (P < 0.05); after LR nursing treatment, Ppeak, Pmean, DLC, PCO(2), and PaO(2)/FiO(2) of the patient were significantly greater than those before the LR, and the difference was statistically significant (P < 0.05). In short, the WT algorithm not only enhanced the quality of ultrasound images but also shortened the running time and improved the processing efficiency. PEEP LR nursing treatment could effectively improve the vascular patency, cardiac ejection capacity, and DLC in patients with ARDS, thereby increasing the airway pressure and maintaining the unobstructed expiration. |
format | Online Article Text |
id | pubmed-8449728 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-84497282021-09-19 Wavelet Transform Image Enhancement Algorithm-Based Evaluation of Lung Recruitment Effect and Nursing of Acute Respiratory Distress Syndrome by Ultrasound Image Jin, Wangyan Dai, Ling Ge, Liuyan Huang, Xuhua Xu, Guanhua Qu, Chunhong Sun, Jianfei J Healthc Eng Research Article This study aimed to analyze the application of ultrasound images of lung recruitment (LR) nursing treatment guided by positive-end expiratory pressure (PEEP) in patients with acute respiratory distress syndrome (ARDS). An ultrasound image enhancement algorithm (UIEA) wavelet transform (WT) was constructed, and the soft threshold (ST) and adjacent region average (ARA) were introduced for simulation comparison. In addition, the signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), and running time were undertaken as the evaluation indexes. The WT algorithm was applied to the ultrasound images of 85 ARDS patients before and after PEEP recruitment. The mean artery pressure (MAP), heart rate (HR), and central venous pressure (CVP), peak inspiratory pressure (Ppeak), mean inspiratory pressure (Pmean), dynamic lung compliance (DLC), PCO(2), and PaO(2)/FiO(2) of the patients were recorded before and after the LR. The results showed that the signal-to-noise ratio (SNR) (19.67 ± 3.15 dB) and PSNR (23.08 ± 2.08 dB) of the images enhanced by the WT algorithm were much higher than those of ST (13.88 ± 2.74 dB and 14.62 ± 1.76 dB, respectively) and ARA (14.96 ± 3.06 dB and 15.11 ± 1.94 dB, respectively), while the running time was in adverse (P < 0.05); the HR and CVP of patients after LR nursing treatment were increased greatly, while the MAP was in the opposite case (P < 0.05); after LR nursing treatment, Ppeak, Pmean, DLC, PCO(2), and PaO(2)/FiO(2) of the patient were significantly greater than those before the LR, and the difference was statistically significant (P < 0.05). In short, the WT algorithm not only enhanced the quality of ultrasound images but also shortened the running time and improved the processing efficiency. PEEP LR nursing treatment could effectively improve the vascular patency, cardiac ejection capacity, and DLC in patients with ARDS, thereby increasing the airway pressure and maintaining the unobstructed expiration. Hindawi 2021-09-10 /pmc/articles/PMC8449728/ /pubmed/34545301 http://dx.doi.org/10.1155/2021/8960465 Text en Copyright © 2021 Wangyan Jin et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Jin, Wangyan Dai, Ling Ge, Liuyan Huang, Xuhua Xu, Guanhua Qu, Chunhong Sun, Jianfei Wavelet Transform Image Enhancement Algorithm-Based Evaluation of Lung Recruitment Effect and Nursing of Acute Respiratory Distress Syndrome by Ultrasound Image |
title | Wavelet Transform Image Enhancement Algorithm-Based Evaluation of Lung Recruitment Effect and Nursing of Acute Respiratory Distress Syndrome by Ultrasound Image |
title_full | Wavelet Transform Image Enhancement Algorithm-Based Evaluation of Lung Recruitment Effect and Nursing of Acute Respiratory Distress Syndrome by Ultrasound Image |
title_fullStr | Wavelet Transform Image Enhancement Algorithm-Based Evaluation of Lung Recruitment Effect and Nursing of Acute Respiratory Distress Syndrome by Ultrasound Image |
title_full_unstemmed | Wavelet Transform Image Enhancement Algorithm-Based Evaluation of Lung Recruitment Effect and Nursing of Acute Respiratory Distress Syndrome by Ultrasound Image |
title_short | Wavelet Transform Image Enhancement Algorithm-Based Evaluation of Lung Recruitment Effect and Nursing of Acute Respiratory Distress Syndrome by Ultrasound Image |
title_sort | wavelet transform image enhancement algorithm-based evaluation of lung recruitment effect and nursing of acute respiratory distress syndrome by ultrasound image |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8449728/ https://www.ncbi.nlm.nih.gov/pubmed/34545301 http://dx.doi.org/10.1155/2021/8960465 |
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