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Film analysis algorithm of isocenter error based on Hough transform for the CyberKnife system / 中华放射肿瘤学杂志
Chinese Journal of Radiation Oncology ; (6): 392-396, 2021.
Article in Chinese | WPRIM | ID: wpr-884576
ABSTRACT

Objective:

A new algorithm based on Hough transform (HT) was proposed to improve the accuracy and stability of the film image analysis of Automatic Quality Assurance (AQA) test, and to explore the influence of the resolution of film image on the test results.

Methods:

Nine pairs of films were obtained for AQA modules in this study. Firstly, the median filter was used to preprocess the grayed-out film image to remove noise interference. Then, a global threshold was utilized to binarize the image. The images were edge-detected and the film edge line was extracted by Hough transform. The film image was transformed to the correct position. Finally, the edge of the field shadow circle and the shadow circle of the tungsten ball were extracted by the edge detection method and Hough transform. The radial error was finally obtained by analyzing the concentricity.

Results:

There was no significant difference in the accuracy between the test results yielded by the HT method and the AQA software ( P>0.05). The difference in the standard deviation of the test results was statistically significant ( P=0.027), indicating that the algorithm increased the stability while ensuring the accuracy of film analysis. Increasing the resolution of film scanning failed to significantly improve the accuracy and stability of film analysis in both two methods.

Conclusions:

The algorithm used in this study can eliminate the human error caused by film scanning placement while ensuring the accuracy of film analysis, providing a more stable way for the AQA test of the CyberKnife system.
Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: Chinese Journal: Chinese Journal of Radiation Oncology Year: 2021 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: Chinese Journal: Chinese Journal of Radiation Oncology Year: 2021 Type: Article