An automatic partitioning method of CTA head-neck image
Gong Zhaoxuan, Tan Wenjun, Yang Jinzhu, Jia Xu, Bian Zijian, Zhao Da-zhe · 2014
The segmentation of vessel in CTA is a challenging task mainly due to bone contact from different regions. The proposed method considers a spatial structure features based partition algorithm which can be separated into three sub-volumes. Firstly, a region growing method was brought forward to remove the background interference, and then added up the bone pixel number in the canter region of head image with specific rules to separate from the proximal layer and the middle layer. Finally, the structure feature of bone profile in neck image was used to separate from middle layer and the distal layer. The experiment results illustrate that the proposed method effectively separate the CTA head-neck image into three sub-volumes in terms of real-timeness, effectiveness and robustness.