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	Automatic liver segmentation using statistical prior models and free-form deformation
	Xuhui Li; Cheng Huang; Fucang Jia; Zongmin Li; Chihua Fang , and Yingfang Fan
	2014
会议名称	International Workshop on Medical Computer Vision: Algorithms for Big Data was held in conjunction with 17th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI-bigMCV 2014
会议地点	Cambridge, MA, United states
英文摘要	In this paper, an automatic and robust coarse-to-fine liver image segmentation method is proposed. Multiple prior knowledge models are built to implement liver localization and segmentation: voxel-based AdaBoost classifier is trained to localize liver position robustly, shape and appearance models are constructed to fit liver these models to original CT volume. Free-form deformation is incorporated to improve the models’ ability of refining liver boundary. The method was submitted to VISCERAL big data challenge, and had been tested on IBSI 2014 challenge datasets and the result demonstrates that the proposed method is accurate and efficient.
收录类别	EI
语种	英语
内容类型	会议论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/5918]
专题	深圳先进技术研究院_医工所
作者单位	2014
推荐引用方式 GB/T 7714	Xuhui Li,Cheng Huang,Fucang Jia,et al. Automatic liver segmentation using statistical prior models and free-form deformation[C]. 见:International Workshop on Medical Computer Vision: Algorithms for Big Data was held in conjunction with 17th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI-bigMCV 2014. Cambridge, MA, United states.

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