A Novel Level Set Method for Segmentation of Left and Right Ventricles from Cardiac MR Images

被引:0
|
作者
Liu, Yu [1 ]
Li, Chunming [2 ]
Guo, Shuxu [1 ]
Song, Yihua [3 ]
Zhao, Yue [1 ]
机构
[1] Jilin Univ, Ctr Image Proc & Comp Vis, Changchun 130023, Peoples R China
[2] Univ Penn, Ctr Biomed Image Comp & Analyt, Philadelphia, PA 19104 USA
[3] Northeastern Univ, Minist Educ, Ctr Key Lab Med Image Comp, Shenyang, Peoples R China
关键词
AUTOMATIC SEGMENTATION;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
In this paper, we propose a novel level set method for segmentation of cardiac left and right ventricles based on the distance regularized level set evolution (DRLSE) framework [7] and the distance regularized two-layer level set (DR2LS) model [17]. First, DRLSE is applied to obtain a preliminary segmentation of left and right ventricles, which is then used to initialize the endocardial contour, which is represented by the zero level contour of the level set function in our method. Then, the epicardial contour is represented by a different level contour of the same level set function. These two level sets are optimized by an energy minimization process to best fit the true endocardium and epicardium. In order to ensure smoothly varying distance between the two level contours, we introduce a distance regularization constraint in the energy function. With the region-scalable fitting (RSF) energy [8] as the data term, our method is able to deal with intensity inhomogeneities in the images, which is a main source of difficulty in image segmentation. Our method has been tested on cardiac MR images with promising results.
引用
收藏
页码:4719 / 4722
页数:4
相关论文
共 50 条
  • [21] Segmentation of the liver from abdominal MR images: a level-set approach
    Abdalbari, Anwar
    Huang, Xishi
    Ren, Jing
    MEDICAL IMAGING 2015: IMAGE PROCESSING, 2015, 9413
  • [22] A Fast Convexity Preserving Level Set Method for Segmentation of Cardiac Left Ventricle
    Shi, Xue
    Tang, Lijun
    Yang, Xiaoping
    ShaoxiangZhang
    Li, Chunming
    ISICDM 2018: PROCEEDINGS OF THE 2ND INTERNATIONAL SYMPOSIUM ON IMAGE COMPUTING AND DIGITAL MEDICINE, 2018, : 51 - 54
  • [23] An efficient level set method for simultaneous intensity inhomogeneity correction and segmentation of MR images
    Ivanovska, Tatyana
    Laqua, Rene
    Wang, Lei
    Schenk, Andrea
    Yoon, Jeong Hee
    Hegenscheid, Katrin
    Voelzke, Henry
    Liebscher, Volkmar
    COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, 2016, 48 : 9 - 20
  • [24] Robust boundary detection of left ventricles on ultrasound images using ASM-level set method
    Zhang, Yaonan
    Gao, Yuan
    Li, Hong
    Teng, Yueyang
    Kang, Yan
    BIO-MEDICAL MATERIALS AND ENGINEERING, 2015, 26 : S1291 - S1296
  • [25] A novel level set based shape prior method for liver segmentation from MRI images
    Cheng, Kan
    Gu, Lixu
    Wu, Jianghua
    Li, Wei
    Xu, Jianrong
    MEDICAL IMAGING AND AUGMENTED REALITY, PROCEEDINGS, 2008, 5128 : 150 - 159
  • [26] Multiphase B-spline level set and incremental shape priors with applications to segmentation and tracking of left ventricle in cardiac MR images
    Van-Truong Pham
    Thi-Thao Tran
    Kuo-Kai Shyu
    Lian-Yu Lin
    Yung-Hung Wang
    Men-Tzung Lo
    Machine Vision and Applications, 2014, 25 : 1967 - 1987
  • [27] Multiphase B-spline level set and incremental shape priors with applications to segmentation and tracking of left ventricle in cardiac MR images
    Van-Truong Pham
    Thi-Thao Tran
    Shyu, Kuo-Kai
    Lin, Lian-Yu
    Wang, Yung-Hung
    Lo, Men-Tzung
    MACHINE VISION AND APPLICATIONS, 2014, 25 (08) : 1967 - 1987
  • [28] Automatic Segmentation of the Left Ventricle in Cardiac MR and CT Images
    Marie-Pierre Jolly
    International Journal of Computer Vision, 2006, 70 : 151 - 163
  • [29] A variational approach for the segmentation of the left ventricle in MR cardiac images
    Paragios, N
    IEEE WORKSHOP ON VARIATIONAL AND LEVEL SET METHODS IN COMPUTER VISION, PROCEEDINGS, 2001, : 153 - 160
  • [30] Automatic segmentation of the left ventricle in cardiac MR and CT images
    Jolly, Marie-Pierre
    INTERNATIONAL JOURNAL OF COMPUTER VISION, 2006, 70 (02) : 151 - 163