为了在影像学检查中实时交互地提取病灶血管的四维计算机断层扫描(CT)影像,提出了一种思维进化算法(MEA)优化的并行区域生长算法;MEA优化的基于三级线程处理队列的并行区域生长算法能够通过自我进化避免局部最优,提高了收敛速度和血管分割精度,借助可视化工具包(VTK)和计算机图形图像类库,实现交互式心脏CT局部任意血管病灶的提取和四维可视化。结果表明:局部感兴趣血管10个时相的提取时间大大缩短,体绘制速度大幅提升,局部血管提取数据的每秒帧数(FPS)可达到30左右,如果在显示过程中有旋转、缩小、放大等交互操作,会使数据的FPS减至21左右,但仍能满足心血管的实时显示;借助优化算法实现心肌局部血管区域的提取,能辅助医生观察病人心血管疾病的病灶区域,可为诊断心血管疾病提供直观、有效的可视化依据。

To extract four-dimensional computed tomography (CT) images of lesion blood vessels with real-time interaction in imaging examination, we propose a parallel region growing algorithm with optimized mind evolutionary algorithm (MEA). The parallel region growing algorithm with optimized MEA based on the three-level thread processing queue can avoid local optimum through self-evolution, and can improve convergence speed and blood vessel segmentation accuracy. Any part of the interactive cardiac lesion vascular extraction and four-dimensional visualization can be achieved with the aids of the visualization toolkit (VTK) and computer graphics library. The results show that extraction time and volume rendering velocity with ten phases of local blood vessels of interest are significantly improved, and frames per second (FPS) of local blood vessel extraction can reach about 30. If interactive manipulations such as rotation, shrinkage, and enlargement appear in the display process, the FPS will decrease to about 21, but the real-time display of cardiovascular can be obtained successfully. The local cardiovascular regional extraction technique can assist doctors to observe the lesion area of cardiovascular disease, and provide an intuitive and effective visual basis for the diagnosis of cardiovascular disease.