| Popis: |
The detection of the spine is crucial in automating the measurement of the Cobb Angle. While various segmentation models have been employed for vertebrae segmentation in X-ray images, there is a need to enhance segmentation performance. This paper proposes a comprehensive automatic measurement method for the Cobb angle. The RetinaNet model is employed to detect the region of interest corresponding to the spine, while the W-Net model is developed for accurate vertebrae segmentation. To address the issue of adjacent vertebrae adhesion in the segmented image, a post-processing technique is applied. Experimental results demonstrate that the W-Net model achieves superior performance, with a mean Intersection over Union (MIoU) of 0.9073 ± 0.0021, Dice Coefficient of 0.9446 ± 0.0139, and Precision of 0.9390 ± 0.0190. The post-processing step reduces adhesion at one end by approximately 83.4% and adhesion at both ends by approximately 83.6%. The reliability of the proposed method is evaluated through intra-group correlation coefficients (ICC) of 0.902 and 0.915, respectively, between two observers, both exceeding 0.9. The mean absolute deviation (MAD) is 3.08° and 2.91°, respectively. Therefore, the proposed method achieves automatic detection of the Cobb angle without the need for manual cropping or additional human intervention, while maintaining good reliability. |
