由于血管边界形态复杂,像素级狭窄检测难以有效地反映血管的细节信息。提出了一种基于数字减影血管造影(DSA)的影像血管狭窄的亚像素级自动检测方法,通过亚像素级分析可以更加准确地辨别狭窄位置并得到更加精确的狭窄程度量化结果。基于自适应多尺度滤波及形态学运算得出血管中轴线,利用泽尼克矩的旋转不变性对血管管壁进行亚像素级检测,采用基于动态球的直径测量算法量化直径,实现了基于DSA的影像血管狭窄的亚像素级自动检测。

Owing to the complex morphology of the blood vessel boundary, the stenosis detection with pixel level cannot reflect the details effectively. We propose a sub-pixel automatic detection method of the blood vessel stenosis based on the digital subtraction angiography (DSA), which can identify the location and the degree of the stenosis more accurately and can obtain accurate quantitative results of the stenosis through sub-pixel analysis. Firstly, we extract the central axis of the blood vessel based on the adaptive multi-scale filtering and morphological operations. Secondly, we perform sub-pixel level detection of the blood vessel by the rotation invariance of Zernike moments. Finally, we quantize the diameter using the diameter measurement algorithm based on dynamical ball. Thus, the sub-pixel automatic detection of blood vessel stenosis based on DSA is realized.