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基于特征提取算法的计算机断层扫描图像纹理在特定护理干预对儿童肺炎支原体疗效诊断中的应用。

Computed Tomography Image Texture under Feature Extraction Algorithm in the Diagnosis of Effect of Specific Nursing Intervention on Mycoplasma Pneumonia in Children.

机构信息

Department of Pediatric Ward, Jinan City People's Hospital, Jinan 271199, Shandong Province, China.

Department of Pediatric Surgery, Jinan City People's Hospital, Jinan 271199, Shandong Province, China.

出版信息

J Healthc Eng. 2021 Oct 16;2021:6059060. doi: 10.1155/2021/6059060. eCollection 2021.

DOI:10.1155/2021/6059060
PMID:34697567
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8541873/
Abstract

To evaluate the effect of specific nursing intervention in children with mycoplasma pneumonia (MP), a feature extraction algorithm based on gray level co-occurrence matrix (GLCM) was proposed and combined with computed tomography (CT) image texture features. Then, 98 children with MP were rolled into the observation group with 49 cases (specific nursing) and the control group with 49 cases (routine nursing). CT images based on feature extraction algorithm of optimized GLCM were used to examine the children before and after nursing intervention, and the recovery of the two groups of children was discussed. The results showed that the proportion of lung texture increase, rope shadow, ground glass shadow, atelectasis, and pleural effusion in the observation group (24.11%, 3.86%, 8.53%, 15.03%, and 3.74%) was significantly lower than that in the control group (28.53%, 10.23%, 13.34%, 21.15%, and 8.13%) after nursing ( < 0.05). There were no significant differences in the proportion of small patchy shadows, large patchy consolidation shadows, and bronchiectasis between the observation group and the control group ( > 0.05). In the course of nursing intervention, in the observation group, the disappearance time of cough, normal temperature, disappearance time of lung rales, and absorption time of lung shadow (2.15 ± 0.86 days, 4.81 ± 1.14 days, 3.64 ± 0.55 days, and 5.96 ± 0.62 days) were significantly shorter than those in the control group (2.87 ± 0.95 days, 3.95 ± 1.06 days, 4.51 ± 1.02 days, and 8.14 ± 1.35 days) ( < 0.05). After nursing intervention, the proportion of satisfaction and total satisfaction in the experimental group (67.08% and 28.66%) was significantly higher than that in the control group (40.21% and 47.39%), while the proportion of dissatisfaction (4.26%) was significantly lower than that in the control group (12.4%) ( < 0.05). To sum up, specific nursing intervention was more beneficial to improve the progress of characterization recovery and the overall recovery effect of children with MP relative to conventional nursing. CT image based on feature extraction algorithm of optimized GLCM was of good adoption value in the diagnosis and treatment of MP in children.

摘要

为了评估特定护理干预对肺炎支原体(MP)患儿的效果,提出了一种基于灰度共生矩阵(GLCM)的特征提取算法,并结合 CT 图像纹理特征。然后,将 98 例 MP 患儿纳入观察组(49 例,特定护理)和对照组(49 例,常规护理)。对护理干预前后的患儿进行基于优化 GLCM 特征提取算法的 CT 图像检查,并对两组患儿的恢复情况进行探讨。结果显示,观察组(24.11%、3.86%、8.53%、15.03%、3.74%)的肺纹理增加、索条影、磨玻璃影、肺不张、胸腔积液比例明显低于对照组(28.53%、10.23%、13.34%、21.15%、8.13%),差异具有统计学意义(<0.05)。观察组与对照组的小斑片状影、大斑片状实变影、支气管扩张比例差异无统计学意义(>0.05)。在护理干预过程中,观察组咳嗽消失时间、体温正常时间、肺部啰音消失时间、肺部阴影吸收时间(2.15±0.86d、4.81±1.14d、3.64±0.55d、5.96±0.62d)明显短于对照组(2.87±0.95d、3.95±1.06d、4.51±1.02d、8.14±1.35d),差异具有统计学意义(<0.05)。护理干预后,观察组的满意度和总满意度(67.08%、28.66%)明显高于对照组(40.21%、47.39%),而观察组的不满意率(4.26%)明显低于对照组(12.4%),差异具有统计学意义(<0.05)。综上所述,与常规护理相比,特定护理干预更有利于改善 MP 患儿的特征恢复进度和整体恢复效果。基于优化 GLCM 特征提取算法的 CT 图像在儿童 MP 的诊断和治疗中具有良好的采用价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9458/8541873/450ea6cba84d/JHE2021-6059060.010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9458/8541873/65eb661bed91/JHE2021-6059060.001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9458/8541873/b26b10f4422c/JHE2021-6059060.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9458/8541873/450ea6cba84d/JHE2021-6059060.010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9458/8541873/65eb661bed91/JHE2021-6059060.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9458/8541873/f441e8e666da/JHE2021-6059060.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9458/8541873/185fa36abd4a/JHE2021-6059060.003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9458/8541873/b0d8f74e50a4/JHE2021-6059060.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9458/8541873/f63e02dfe0d5/JHE2021-6059060.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9458/8541873/596c003af90c/JHE2021-6059060.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9458/8541873/03b6b58f9f93/JHE2021-6059060.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9458/8541873/b26b10f4422c/JHE2021-6059060.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9458/8541873/450ea6cba84d/JHE2021-6059060.010.jpg

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