التفاصيل البيبلوغرافية
| العنوان: |
Image segmentation based on active contour in chest X-ray image. |
| المؤلفون: |
Oktamuliani, Sri, Saijo, Yoshifumi |
| المصدر: |
AIP Conference Proceedings; 2024, Vol. 3074 Issue 1, p1-7, 7p |
| مصطلحات موضوعية: |
COMPUTER vision, IMAGE analysis, MEDICAL research, LUNGS, UNIVERSITY hospitals |
| مستخلص: |
Chest X-ray (CXR) imaging is often used to diagnose pneumonia caused by COVID-19. The advantage of CXR is that it is cheap, fast, widespread, and uses less radiation. Studies of distinguishing object regions from one to another or image segmentation have been used in the medical field for further image analysis. This paper has proposed a method for segmenting lungregions using region-based active contour to measure the area segmented in CXR images. Active contour segmentation was performed using a computer vision image segmented in MATLAB. We assessed the CXR image in Andalas University Hospital and composed the data consisting of lung opacity (pneumonia) and regular. The result shows that, in both the left and right of the chest, the area in the pixel of the lung affected by COVID-19 is smaller than in the normal lung. In conclusion, this technique will benefit biomedical research investigating the regional lung. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
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