基于血管增强滤波的脑部静脉分割新方法

A New Method for Brain Vein Segmenting Based on Vessel Enhancing Filtering

目的将本身灰度不均的静脉从有噪声干扰、结构复杂的脑部磁敏感加权图像中准确地分割出来。方法提出基于血管增强滤波联合动态阈值分割和动态阈值区域生长的血管提取方法。前者分割出部分静脉作为种子点,后者生长至几乎全部静脉。结果在重度噪声和干扰的仿真图像中,可以达到90%以上的正确率;在临床图像中,能准确地提取出了静脉,清晰地显示了静脉的脉络结构。结论上述方法可以准确地实现脑部磁敏感加权图像中的静脉分割,有效地避免误分割,同时具有很好的鲁棒性。

Objective To segment veins from brain susceptibility weighted images with inhomogeneous background and veins, noises and complex structures. Methods Based on vessel enhancing filtering, an adaptive threshold segmenting method and an adaptive threshold region growing method were proposed. The former method was used to exactly segment part of veins from the original images. Taking the veins segmented by the former method as seeds, the later method was used to extract nearly al the veins. Results For simulation data with serious noises and interferences, correct rate above 90% was achieved. And for clinical data, the veins were extracted accurately and the structures of veins were displayed clearly. Conclusions The methods can extract veins from the brain susceptibility weighted images exactly and avoid false segmentation of the other structures effectively. The methods are very robust and stable.