摘要
针对血管树结构的复杂性,提出了基于管状特性和主动轮廓的3维血管的自动提取模型。该模型充分利用管状特性,包括血管的先验灰度分布、多尺度血管矢量场和血管几何曲率特征,把这些信息表示为主动轮廓模型的能量项并最小化,得到包括3个主要速度项的迭代方程:基于区域竞争和先验灰度的主动轮廓、血管矢量场和多曲率策略。基于区域竞争和先验灰度的主动轮廓可以准确健壮地提取大的血管;由Hessian矩阵主元分析得到的血管矢量场,可以驱使主动轮廓演化到细小血管内部;最小主曲率和平均曲率的多曲率策略,可以降噪平滑血管的同时,充分保持血管的几何形状。通过对肝脏、冠状动脉和肺部血管的分割,表明该模型可以自动地对整个血管树进行提取,不需要太多的预处理和后处理,是一种有效的血管自动提取模型。
In this paper, we propose a nevo model for three dimensional vessel extraction. The model makes full use of tubular properties, which includes prior intensity of vessels, second tensor of tubular structures, and geometric curvatures. All this information makes the energy terms of the active contour model and thus leads to three forces of the iterative equation ： the region competition force using prior intensity, the tubular vector field force and the dual curvature force. The first force help extracting big vessels accurately and robustly, the second force makes it possible to extract thin and weak vessels, and the last one is able to remove noise without changing the tubular geometry. As shown in the experiments extracting liver vessels, coronary, and lung vessels, the proposed model is able to extract the whole vessel trees automatically, accurately, and robustly.
出处
《中国图象图形学报》
CSCD
北大核心
2013年第3期290-298,共9页
Journal of Image and Graphics
基金
国家重大科技专项(2011ZX02505-002)
上海市科委项目(10DZ1500600)
