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	Automatic liver segmentation from CT images using adaptive fast marching method
	Song, Xiao ; Cheng, Ming ; Wang, Boliang ; Huang, Shaohui ; Huang, Xiaoyang ; Wang BL(王博亮) ; Huang XY(黄晓阳)
	2013
关键词	Computer aided diagnosis Image segmentation Noise abatement
英文摘要	Conference Name:2013 7th International Conference on Image and Graphics, ICIG 2013. Conference Address: Qingdao, Shandong, China. Time:July 26, 2013 - July 28, 2013.; Liver segmentation is the fundamental step in computer-aided liver disease diagnosis and surgery planning. In this study, we developed a fully automatic liver extraction scheme based on an adaptive fast marching method (FMM). Firstly, a thresholding operation was applied to remove the ribs, spines and kidneys. Followed by a smooth filter for noise reduction. Secondly, a nonlinear gray scale converter was used to enhance the contrast of the liver parenchyma. The enhanced image is then eroded with 3-voxel radius so that small regions are deleted. The seed points located in the liver were selected automatically. Finally, using the processed image as a speed function, FMM was employed to generate the liver contour. Clinical validation has performed on 30 abdominal computed tomography (CT) datasets. The proposed algorithm achieved an overall true positive rate (TPR) of 0.98. It takes about 0.30 s for a 512×512-pixel slice. The method has been applied successfully for fast and accurate liver segmentation. ? 2013 IEEE.
语种	英语
出处	http://dx.doi.org/10.1109/ICIG.2013.181
出版者	IEEE Computer Society
内容类型	其他
源URL	[http://dspace.xmu.edu.cn/handle/2288/86689]
专题	信息技术－会议论文
推荐引用方式 GB/T 7714	Song, Xiao,Cheng, Ming,Wang, Boliang,et al. Automatic liver segmentation from CT images using adaptive fast marching method. 2013-01-01.

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