Automatic Liver Segmentation Based on Shape Constraints and Deformable Graph Cut in CT Images
文献类型：期刊论文
| 作者 | Li, Guodong1 ; Chen, Xinjian2; Shi, Fei2; Zhu, Weifang2; Tian, Jie1; Xiang, Dehui2
|
| 刊名 | IEEE TRANSACTIONS ON IMAGE PROCESSING
 |
| 出版日期 | 2015-12-01 |
| 卷号 | 24期号:12页码:5315-5329 |
| 关键词 | Liver segmentation principal component analysis euclidean distance transformation deformable graph cut |
| 英文摘要 | Liver segmentation is still a challenging task in medical image processing area due to the complexity of the liver's anatomy, low contrast with adjacent organs, and presence of pathologies. This investigation was used to develop and validate an automated method to segment livers in CT images. The proposed framework consists of three steps: 1) preprocessing; 2) initialization; and 3) segmentation. In the first step, a statistical shape model is constructed based on the principal component analysis and the input image is smoothed using curvature anisotropic diffusion filtering. In the second step, the mean shape model is moved using thresholding and Euclidean distance transformation to obtain a coarse position in a test image, and then the initial mesh is locally and iteratively deformed to the coarse boundary, which is constrained to stay close to a subspace of shapes describing the anatomical variability. Finally, in order to accurately detect the liver surface, deformable graph cut was proposed, which effectively integrates the properties and interrelationship of the input images and initialized surface. The proposed method was evaluated on 50 CT scan images, which are publicly available in two databases Sliver07 and 3Dircadb. The experimental results showed that the proposed method was effective and accurate for detection of the liver surface. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
| 研究领域[WOS] | Computer Science ; Engineering |
| 关键词[WOS] | MODEL ; TOMOGRAPHY ; LAPLACIAN |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000362488900016 |
| 公开日期 | 2015-12-24 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/10031]  |
| 专题 | 自动化研究所_中国科学院分子影像重点实验室 |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 2.Soochow Univ, Sch Elect & Informat Engn, Suzhou 215006, Jiangsu, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Guodong,Chen, Xinjian,Shi, Fei,et al. Automatic Liver Segmentation Based on Shape Constraints and Deformable Graph Cut in CT Images[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2015,24(12):5315-5329. |
| APA | Li, Guodong,Chen, Xinjian,Shi, Fei,Zhu, Weifang,Tian, Jie,&Xiang, Dehui.(2015).Automatic Liver Segmentation Based on Shape Constraints and Deformable Graph Cut in CT Images.IEEE TRANSACTIONS ON IMAGE PROCESSING,24(12),5315-5329. |
| MLA | Li, Guodong,et al."Automatic Liver Segmentation Based on Shape Constraints and Deformable Graph Cut in CT Images".IEEE TRANSACTIONS ON IMAGE PROCESSING 24.12(2015):5315-5329. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。