The study focused on the intelligent algorithms-based segmentation of computed tomography (CT) images of patients with cardiovascular diseases (CVD) and the realization of visualization algorithms. The first step was to design a method for precise segmentation under the cylinder model based on the coronary body data of the coarse segmentation, and then the principles of different visualization algorithms were discussed. The results showed that the precise segmentation method can effectively eliminate most of the branches and calcified lesions; curved planar reformation (CPR) and straightened CPR can display the entire blood vessel on one image; and spherical CPR can display the complete coronary artery tree on an image, so that a problem with a certain blood vessel can be quickly found. In conclusion, the precise segmentation of CT images of CVD and visualization algorithm based on the cylinder model have clinical significance in the diagnosis of CVD.

中文翻译：

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基于智能算法的心血管疾病患者CT图像分割及可视化算法的实现

该研究侧重于基于智能算法的心血管疾病 (CVD) 患者计算机断层扫描 (CT) 图像分割和可视化算法的实现。第一步是基于粗分割的冠状体数据设计圆柱模型下的精确分割方法，然后讨论了不同可视化算法的原理。结果表明，精确分割方法可以有效消除大部分分支和钙化病灶；曲面重建 (CPR) 和拉直 CPR 可以在一张图像上显示整个血管；球面心肺复苏可以在图像上显示完整的冠状动脉树，从而可以快速发现某条血管的问题。综上所述，