CASIA OpenIR  > 中国科学院分子影像重点实验室
Automatic Renal Cortex Segmentation Using Implicit Shape Registration and Novel Multiple Surfaces Graph Search (vol 31, pg 1849, 2012)
Li, Xiuli1; Chen, Xinjian2; Yao, Jianhua2; Zhang, Xing1; Yang, Fei1; Tian, Jie1
Source PublicationIEEE TRANSACTIONS ON MEDICAL IMAGING
2012-12-01
Volume31Issue:12Pages:2366-2366
SubtypeCorrection
Abstract 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, and average symmetric rms surface distance. The experimental results showed the feasibility, efficiency, and robustness of the proposed method.
KeywordImplicit Shape Registration Multiple Surfaces Graph Searching Physical Constraints Renal Cortex Segmentation
WOS HeadingsScience & Technology ; Technology ; Life Sciences & Biomedicine
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering ; Imaging Science & Photographic Technology ; Radiology, Nuclear Medicine & Medical Imaging
WOS SubjectComputer Science, Interdisciplinary Applications ; Engineering, Biomedical ; Engineering, Electrical & Electronic ; Imaging Science & Photographic Technology ; Radiology, Nuclear Medicine & Medical Imaging
WOS IDWOS:000313690600017
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/4063
Collection中国科学院分子影像重点实验室
Corresponding AuthorTian, Jie
Affiliation1.Chinese Acad Sci, Intelligent Med Res Ctr, Inst Automat, Beijing 100190, Peoples R China
2.NIH, Radiol & Imaging Sci Dept, Ctr Clin, Bethesda, MD 20814 USA
Recommended Citation
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Li, Xiuli,Chen, Xinjian,Yao, Jianhua,et al. Automatic Renal Cortex Segmentation Using Implicit Shape Registration and Novel Multiple Surfaces Graph Search (vol 31, pg 1849, 2012)[J]. IEEE TRANSACTIONS ON MEDICAL IMAGING,2012,31(12):2366-2366.
APA Li, Xiuli,Chen, Xinjian,Yao, Jianhua,Zhang, Xing,Yang, Fei,&Tian, Jie.(2012).Automatic Renal Cortex Segmentation Using Implicit Shape Registration and Novel Multiple Surfaces Graph Search (vol 31, pg 1849, 2012).IEEE TRANSACTIONS ON MEDICAL IMAGING,31(12),2366-2366.
MLA Li, Xiuli,et al."Automatic Renal Cortex Segmentation Using Implicit Shape Registration and Novel Multiple Surfaces Graph Search (vol 31, pg 1849, 2012)".IEEE TRANSACTIONS ON MEDICAL IMAGING 31.12(2012):2366-2366.
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