Guide-wire Detecting Using a Modified Cascade Classifier in Interventional Radiology
Wang, Li; Xie, Xiao-Liang; Gao, Zhan-Jie; Bian, Gui-Bin; Hou, Zeng-Guang
2016
会议名称IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)
会议日期AUG 16-20, 2016
会议地点Orlando, FL
摘要Endovascular surgery is becoming a widespread
procedure to treat cardiovascular diseases (CVDs) such as
abdominal aortic aneurysm and peripheral artery disease. The
guide-wire is a crucial surgical instrument inserted into vessels
to offer guidance to physicians during the surgery. There are
some approaches for tracking the guide-wire, most algorithms
consist of two phases, namely, the initialization phase and the
tracking phase. In the initialization phase, most algorithms use
B-splines for modeling the guide-wire which requires manually
annotated data. In the tracking phase, the guide-wire motion
is non-linearity because it is deforming and changing its shape
and size as a result of patients’ respiration, some algorithms
decompose the non-linearity motion into rigid motion and
non-rigid motion, while the computational complexity is high
especially for the non-rigid motion. This paper mainly presents
an approach to detect the guide-wire. The algorithm has
two main advantages. First, without modeling the guide-wire,
this approach uses a cascade classifier which can detect the
guide-wire under arbitrary motion automatically. Second, by
taking the guide-wire motion direction into consideration, the
detection accuracy improves significantly. The presented work
has been validated on a test set of 349 frames, and the mean
tracking accuracy achieves more than 95% which proves the
effectiveness of the proposed method
 .
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/20001
专题复杂系统管理与控制国家重点实验室_先进机器人
通讯作者Xie, Xiao-Liang
作者单位State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing.
推荐引用方式
GB/T 7714
Wang, Li,Xie, Xiao-Liang,Gao, Zhan-Jie,et al. Guide-wire Detecting Using a Modified Cascade Classifier in Interventional Radiology[C],2016.
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