This application provides a method for measuring and analyzing the accuracy of a
stereotactic radiotherapy system. The method involves sequentially performing geometric transformations on film images to calibrate the S-L and S-A directions, adaptively correcting positioning errors, purifying the target region through multi-dimensional interference removal, and denoising using normalization and adaptive
weighted median filtering. Then, improved fuzzy C-means clustering with fused dual images is used to segment and output
label images. Gray-level classification is used to extract the
radiation field and
tungsten sphere contours. After morphological optimization, the
centroid position deviation is calculated. The
system accuracy analysis is then completed by combining the S-L and S-A dual film deviations. This application solves the problems of inaccurate contour recognition and large
centroid calculation errors in traditional detection methods, significantly improving the accuracy, stability, and robustness of the detection. The steps are clear, the parameters are quantified, and the method is repeatable, providing efficient and accurate
technical support for AQA detection in radiotherapy systems.