Huang Tzung-Chi, Cheng Da-Chuan, Schmidt-Trucksäss Arno, Schütz Uwe H
a Department of Biomedical Imaging and Radiological Science , China Medical University , Taichung , Taiwan.
Comput Methods Biomech Biomed Engin. 2013;16(8):873-84. doi: 10.1080/10255842.2011.643468. Epub 2012 Jan 6.
In this paper, an automated method to localise the right superficial femoral artery (SFA) and identify its boundary on magnetic resonance imaging (MRI) sequences without contrast medium injection is proposed. Some anatomical knowledge combined with the mathematical morphology is used to distinguish SFA from other vessels. Afterwards, the directional gradient, continuity and the local contrast are applied as features to identify the artery's boundary using dynamic programming. The accuracy analysis shows that the system has average unsigned errors 3.1 ± 3.1% on five sequences compared to experts' manual tracings.
本文提出了一种在不注射造影剂的情况下,在磁共振成像(MRI)序列上自动定位右侧股浅动脉(SFA)并识别其边界的方法。结合一些解剖学知识和数学形态学来将SFA与其他血管区分开来。之后,将方向梯度、连续性和局部对比度作为特征,使用动态规划来识别动脉边界。准确性分析表明,与专家手动追踪相比,该系统在五个序列上的平均无符号误差为3.1±3.1%。