基于冠脉造影图像血管树分割的血管狭窄自动识别方法

Automated Detection and Quantification of Coronary Artery Stenoses Based on Vessel Tree Segmentation in X-Ray Angiography

针对冠状动脉造影图像中的血管狭窄位置进行自动识别,并且定量评估其狭窄程度,为临床医生提供一种计算机辅助诊断方法,从而提高对冠状动脉狭窄的诊断准确率,同时减轻医生的劳动强度。所提出的基于冠脉造影图像的血管狭窄自动识别方法包括血管树分割以及血管狭窄识别两部分。在血管树分割部分,首先通过基于Frangi Hessian的改进模型进行图像增强,随后利用基于统计学区域融合方法对血管区域进行分割。在血管狭窄识别部分,首先利用水平集算法对分割结果进行细化获得血管骨架,随后提取血管边缘进行血管直径测量,最后采用局部最小点法计算整幅图像血管段狭窄的百分比,对狭窄段进行定位并分级。实验在153例患者的血管造影图像中检测出狭窄共计208段,其中轻度84段,中度42段,重度82段。统计分析结果显示,血管狭窄识别平均准确率为93.59%,敏感性为88.76%,特异性为95.58%,阳性预测值为90.51%,表明该方法能够有效地检测和定量评价动脉血管的狭窄程度,有助于心血管疾病的临床诊断。

Automated identification and quantification of the vascular stenoses in coronary angiographical images are essential in a computer-aided diagnosis system,which can improve the diagnosis accuracy,while reducing the labor intensity of doctors in daily clinical practice.We presented a computerized method for automatic detection and grading of vascular stenoses on X-ray angiography in this work,which included two main parts.In the vessel segmentation part,image enhancement was first performed by an improved Frangi Hessian based method,and then the blood vessel regions were segmented using a statistical region merging approach,which could provide good partition of the vascular tree with a complex structure.In the stenosis assessment part,a vessel skeleton was first obtained from a skeletonization method,then vessel diameters were computed based on the boundary points from the vessel tree segmentation,and finally stenosis degree were calculated using ratio between minimum and maximum of the vessel diameters in the vessel stenosis segment.The method was tested on 153 patient studies,and a total of 208 vessel segments were identified,including 84 mild,42 moderate,and 82 severe stenoses.The method achieved detection accuracy 93.59%,sensitivity 88.76%,specificity 95.58%,and a positive predictive value 90.51%,which suggested the method was able to effectively detect and quantify the artery vessel stenoses,and provided supplement opinion for clinical diagnosis of cardiovascular disease.