对于颈部淋巴结的超声造影视频病例, 可利用其时间强度曲线提取灌注特征进行病情诊断. 现有的研究方法对感兴趣区域进行像素级的分析可以更准确地描述灌注特征, 然而很少有深入研究灌注流向可视化的方法. 本文利用了像素级的时间强度曲线TIC分析, 采取双重筛选方式对TIC曲线进行筛选, 进而针对TIC曲线提取二维灌注参数对灌注流向进行可视化. 特征提取后生成的流线图像能够一定程度反映血管的分布, 对医生病情诊断有一定的辅助价值, 也可以对微血管重构有一定的启发价值.
As for contrast-enhanced ultrasound video cases involving cervical lymph nodes, perfusion features can be extracted from the time-intensity curve (TIC) to make a diagnosis. The existing research methods that analyze a region of interest at the pixel level are able to describe perfusion features accurately. However, in-depth research on methods of visualizing the perfusion flow direction is limited in number. In this study, pixel-based TIC analysis is performed, and the TIC is screened by double screening. Then, two-dimensional perfusion parameters are extracted from the TIC to visualize the perfusion flow direction. The streamline image generated after feature extraction can reflect the distribution of blood vessels to a certain extent, thereby helping doctors with their diagnoses and providing implications to microvascular reconstruction.