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Identifying the coordinates of marked points in digital subtraction angiography (DSA) is one of the key problems in DSA image-guided navigation systems for interventional radiological procedures. DSA images directly affect the precision and speed of navigation. In this work, a novel method for marked point identification was proposed on the basis of the geographical concept of triangle topology to identify the coordinates of the marked points in a DSA image rapidly and accurately. First, a calibration model with special and distributed marked points was designed. The identifiable marked points from the pretreated image were then selected and the image coordinate of the fourth marked point was verified for calibration. Subsequently, the structure of the triangle topology and proportional relation were used to confirm the uniformized coordinates of the four points. These four points were used to calculate the homography from the coordinates of the uniformized coordinate system to the coordinates of the image coordinate system. Finally, the image coordinates of all the marked points were derived through the values of the uniformized coordinates and homography. Results show that through the marked point identification method proposed in this study, the locations of the marked points can be determined accurately and quickly in the image coordinate system and uniformized coordinate system based on the triangle topology structure, which was formed by the identifiable marked points. The image coordinates of all the marked points can be recalculated without identifying the special marked points. The average error in the algorithm is smaller than 1 mm, and the running time is shorter than 1 s. These values satisfy the requirements of actual surgery in terms of the precision and speed. Thus, the proposed method can provide practical reference for future navigation system based on DSA images for interventional operation.

Marked Point Identification for Inter ventional Operation Navigation of D igital Subtraction Angiography Image based on Triangle Topology