학술논문

肥胖病人進行胸部床邊攝影時利用影像處理軟體提升影像對比度之應用 / The Application of Using Image Processing Software to Improve Image Contrast in Obese Patients Take Chest Bedside Radiography
Document Type
Article
Source
中華放射線技術學雜誌 / Chinese Journal Of Radiologic Technology. Vol. 47 Issue 2, p88-93. 6 p.
Subject
肥胖病人
影像處理軟體
浸潤
散射光子
Obese Patient
Imaging Processing Software
Infiltration
Scatter Radiation
Language
繁體中文
英文
ISSN
1684-9418
Abstract
In clinic situation, we consider that the patient's dose and safety. Radiogrpher will be not using anti-scatter grid, when take chest portable X-ray. But the scatter radiation will bulr the image, when radiographer take exam without anti-scatter grid. When the obese patient do this examination, it will be worse. In this study, we discuss that use the imaging processing software to inprove the image quality. The case of this study were collected from 2020/5/1 to 2021/3/31. A total of 60 obese patients over the age of 20 with a BMI > 27(male:30 female:30). The images of each patient can be divided into a control group (not processed by IG) and an experimental group (processed by IG). Invite radiologists with 10 years of experience in reading images compare the number of retake due to poor contrast. Then compare the image quality of the trachea, hilum, mediastinum, left lower lung lobe, right lower lung lobe, ribs, thoracic spine, and overall images in the two groups to score. Using the likert scale for scoring, very dissatisfied: 1 point, dissatisfied: 2 points, fair: 3 points, satisfied: 4 points, very satisfied: 5 points. In this study, SPSS (Statistical Package for the Social Sciences) version 25 statistical software was used to perform statistics in a Wilcoxon signed-rank test method. The average number of trachea experimental group and control group was 4.40/3.66、hilum 4.18/3.95、mediastinal cavity 4.03/3.40、left lower lobe 4.28/3.86、right lower lobe 4.45/3.93、ribs 4.11/3.40、thoracic spine 4.46/3.51、whole image 4.33/ 3.50. It can be seen that its significance p <0.01, which means that there is a significant difference.

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