Automatic Renal Cortex Segmentation Using Implicit Shape Registration and Novel Multiple Surfaces Graph Search

	Automatic Renal Cortex Segmentation Using Implicit Shape Registration and Novel Multiple Surfaces Graph Search
	Li, Xiuli 1; Chen, Xinjian 2; Yao, Jianhua 2; Zhang, Xing 1; Yang, Fei 1; Tian, Jian 1
发表期刊	IEEE TRANSACTIONS ON MEDICAL IMAGING
	2012-10-01
卷号	31 期号:10 页码:1849-1860
文章类型	Article
摘要	In this paper, we present an automatic renal cortex segmentation approach using the implicit shape registration and novel multiple surfaces graph search. The proposed approach is based on a hierarchy system. First, the whole kidney is roughly initialized using an implicit shape registration method, with the shapes embedded in the space of Euclidean distance functions. Second, the outer and inner surfaces of renal cortex are extracted utilizing multiple surfaces graph searching, which is extended to allow for varying sampling distances and physical constraints to better separate the renal cortex and renal column. Third, a renal cortex refining procedure is applied to detect and reduce incorrect segmentation pixels around the renal pelvis, further improving the segmentation accuracy. The method was evaluated on 17 clinical computed tomography scans using the leave-one-out strategy with five metrics: Dice similarity coefficient (DSC), volumetric overlap error (OE), signed relative volume difference (SVD), average symmetric surface distance (D-avg), and average symmetric rms surface distance (D-rms). The experimental results of DSC, OE, SVD, D-avg, and D-rms were 90.50% +/- 1.19% 4.38% +/- 3.93%, 2.37% +/- 1.72%, 0.14 mm +/- 0.09 mm, and 0.80 mm +/- 0.64 mm, respectively. The results showed the feasibility, efficiency, and robustness of the proposed method.
关键词	Implicit Shape Registration Multiple Surfaces Graph Searching Physical Constraints Renal Cortex Segmentation
WOS标题词	Science & Technology ; Technology ; Life Sciences & Biomedicine
关键词[WOS]	KIDNEY SEGMENTATION ; CT IMAGES ; MODEL ; INFORMATION ; ALGORITHMS ; VOLUMETRY ; SOFTWARE ; MRI
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Engineering ; Imaging Science & Photographic Technology ; Radiology, Nuclear Medicine & Medical Imaging
WOS类目	Computer Science, Interdisciplinary Applications ; Engineering, Biomedical ; Engineering, Electrical & Electronic ; Imaging Science & Photographic Technology ; Radiology, Nuclear Medicine & Medical Imaging
WOS记录号	WOS:000310149700002
引用统计	被引频次：17[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/4064
专题	中国科学院分子影像重点实验室
作者单位	1.Chinese Acad Sci, Intelligent Med Res Ctr, Inst Automat, Beijing 100190, Peoples R China 2.NIH, Ctr Clin, Radiol & Imaging Sci Dept, Bethesda, MD 20814 USA
推荐引用方式 GB/T 7714	Li, Xiuli,Chen, Xinjian,Yao, Jianhua,et al. Automatic Renal Cortex Segmentation Using Implicit Shape Registration and Novel Multiple Surfaces Graph Search[J]. IEEE TRANSACTIONS ON MEDICAL IMAGING,2012,31(10):1849-1860.
APA	Li, Xiuli,Chen, Xinjian,Yao, Jianhua,Zhang, Xing,Yang, Fei,&Tian, Jian.(2012).Automatic Renal Cortex Segmentation Using Implicit Shape Registration and Novel Multiple Surfaces Graph Search.IEEE TRANSACTIONS ON MEDICAL IMAGING,31(10),1849-1860.
MLA	Li, Xiuli,et al."Automatic Renal Cortex Segmentation Using Implicit Shape Registration and Novel Multiple Surfaces Graph Search".IEEE TRANSACTIONS ON MEDICAL IMAGING 31.10(2012):1849-1860.