Distance regularized two level sets for segmentation of left and right ventricles from cine-MRI

被引:61
作者
Liu, Yu [1 ]
Captur, Gabriella [2 ,3 ]
Moon, James C. [2 ,3 ]
Guo, Shuxu [1 ]
Yang, Xiaoping [4 ]
Zhang, Shaoxiang [5 ]
Li, Chunming [6 ]
机构
[1] Jilin Univ, Coll Elect Sci & Engn, Changchun 130023, Peoples R China
[2] UCL, Inst Cardiovasc Sci, London, England
[3] Barts Hlth NHS Trust, St Bartholomews Hosp, Barts Heart Ctr, London, England
[4] Nanjing Univ Sci & Technol, Sch Sci, Nanjing, Jiangsu, Peoples R China
[5] TMMU, Inst Digital Med, Chongqing, Peoples R China
[6] UESTC, Sch Elect Engn, Chengdu, Peoples R China
关键词
MRI; Segmentation; Two-level-set; Left and right ventricles; CARDIAC MR; LEVEL-SET; AUTOMATIC SEGMENTATION; ACTIVE CONTOURS; MODEL; IMAGES; MYOCARDIUM; ACCURATE; ATLAS;
D O I
10.1016/j.mri.2015.12.027
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
This paper presents a new level set method for segmentation of cardiac left and right ventricles. We extend the edge based distance regularized level set evolution (DRLSE) model in Li et al. (2010) to a two-level-set formulation, with the 0-level set and k-level set representing the endocardium and epicardium, respectively. The extraction of endocardium and epicardium is obtained as a result of the interactive curve evolution of the 0 and k level sets derived from the proposed variational level set formulation. The initialization of the level set function in the proposed two-level-set DRLSE model is generated from roughly located endocardium, which can be performed by applying the original DRLSE model. Experimental results have demonstrated the effectiveness of the proposed two-level-set DRLSE model. (C) 2016 Elsevier Inc. All rights reserved.
引用
收藏
页码:699 / 706
页数:8
相关论文
共 43 条
[1]   A Probabilistic Patch-Based Label Fusion Model for Multi-Atlas Segmentation With Registration Refinement: Application to Cardiac MR Images [J].
Bai, Wenjia ;
Shi, Wenzhe ;
O'Regan, Declan P. ;
Tong, Tong ;
Wang, Haiyan ;
Jamil-Copley, Shahnaz ;
Peters, Nicholas S. ;
Rueckert, Daniel .
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2013, 32 (07) :1302-1315
[2]   Max-flow segmentation of the left ventricle by recovering subject-specific distributions via a bound of the Bhattacharyya measure [J].
Ben Ayed, Ismail ;
Chen, Hua-mei ;
Punithakumar, Kumaradevan ;
Ross, Ian ;
Li, Shuo .
MEDICAL IMAGE ANALYSIS, 2012, 16 (01) :87-100
[3]  
Bruder O., J CARDIOVASC MAGN RE, V18
[4]   Active contours without edges [J].
Chan, TF ;
Vese, LA .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2001, 10 (02) :266-277
[5]   Using prior shapes in geometric active contours in a variational framework [J].
Chen, YM ;
Tagare, HD ;
Thiruvenkadam, S ;
Huang, F ;
Wilson, D ;
Gopinath, KS ;
Briggs, RW ;
Geiser, EA .
INTERNATIONAL JOURNAL OF COMPUTER VISION, 2002, 50 (03) :315-328
[6]  
Constantinides C, 2009, MIDAS J CARDIAC MR L, DOI 10380/3108.
[7]  
Dornheim L, 2005, LECT NOTES COMPUT SC, V3749, P335
[8]   The UK Biobank sample handling and storage protocol for the collection, processing and archiving of human blood and urine [J].
Elliott, Paul ;
Peakman, Tim C. .
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, 2008, 37 (02) :234-244
[9]   Three-dimensional modeling for functional analysis of cardiac images: A review [J].
Frangi, AF ;
Niessen, WJ ;
Viergever, MA .
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2001, 20 (01) :2-25
[10]   Hybrid segmentation of left ventricle in cardiac MRI using gaussian-mixture model and region restricted dynamic programming [J].
Hu, Huaifei ;
Liu, Haihua ;
Gao, Zhiyong ;
Huang, Lu .
MAGNETIC RESONANCE IMAGING, 2013, 31 (04) :575-584