Because of its high positioning accuracy, easy identification and high stability, circular markers are widely used in patient positioning in the medical field. However, during radiotherapy, the marker points on the patient's body surface are blocked by the thermoplastic film that fixes the patient, which makes it difficult to extract and locate the center of the marker points. Commonly used circular marker positioning algorithms cannot accurately locate the markers when there are a large number of random deletions. Therefore, a marker center positioning algorithm for this situation is needed. First, the image is converted to the HSV color space to extract the landmark points through threshold processing; then the Canny edge detection algorithm is used to extract the edges of the landmarks under the occlusion; then the Graham scanning method is used to obtain the convex hull points of the edge points. Finally, the improved least squares circle fitting algorithm is used to fit the convex hull points to locate the center of the marker. Verified by experiment, the accuracy of this method for extracting the center of the circular marker is within 0.05 pixel, and the positioning accuracy is much higher than that of the gray-scale centroid method under the same circumstances.
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