title: Nonrigid registration with corresponding points constraint for automatic segmentation of cardiac DSCT images.
abstract: BACKGROUND
  Dual-source computed tomography (DSCT) is a very effective way for diagnosis and treatment of heart disease. The quantitative information of spatiotemporal DSCT images can be important for the evaluation of cardiac function. To avoid the shortcoming of manual delineation, it is imperative to develop an automatic segmentation technique for 4D cardiac images.
  
  
  METHODS
  In this paper, we implement the heart segmentation-propagation framework based on nonrigid registration. The corresponding points of anatomical substructures are extracted by using the extension of n-dimensional scale invariant feature transform method. They are considered as a constraint term of nonrigid registration using the free-form deformation, in order to restrain the large variations and boundary ambiguity between subjects.
  
  
  RESULTS
  We validate our method on 15 patients at ten time phases. Atlases are constructed by the training dataset from ten patients. On the remaining data the median overlap is shown to improve significantly compared to original mutual information, in particular from 0.4703 to 0.5015 ([Formula: see text]) for left ventricle myocardium and from 0.6307 to 0.6519 ([Formula: see text]) for right atrium.
  
  
  CONCLUSIONS
  The proposed method outperforms standard mutual information of intensity only. The segmentation errors had been significantly reduced at the left ventricle myocardium and the right atrium. The mean surface distance of using our framework is around 1.73 mm for the whole heart.
authors.affiliation: College of Biomedical Engineering, South-Central University for Nationalities, Wuhan, 430074, People's Republic of China.
authors.forename: Xuesong
authors.initials: X
authors.lastname: Lu
authors.affiliation: School of Materials Science and Engineering, South China University of Technology, Guangzhou, 510006, People's Republic of China. bmeyrq@gmail.com.
authors.forename: Rongqian
authors.initials: R
authors.lastname: Yang
authors.affiliation: College of Biomedical Engineering, South-Central University for Nationalities, Wuhan, 430074, People's Republic of China.
authors.forename: Qinlan
authors.initials: Q
authors.lastname: Xie
authors.affiliation: Radiology Department, Guangzhou General Hospital of Guangzhou Military Area Command, Guangzhou, 510010, People's Republic of China.
authors.forename: Shanxing
authors.initials: S
authors.lastname: Ou
authors.affiliation: Department of Radiology, Remin Hospital of Wuhan University, Wuhan, 430060, People's Republic of China.
authors.forename: Yunfei
authors.initials: Y
authors.lastname: Zha
authors.affiliation: Research Center for Medical Image Computing, Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China. dfwang@cuhk.edu.hk.|Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China. dfwang@cuhk.edu.hk.
authors.forename: Defeng
authors.initials: D
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D001331:Automation; D056973:Four-Dimensional Computed Tomography; D006321:Heart / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*
keywords: Automatic heart segmentation; Corresponding points; Dual-source computed tomography (DSCT); Mutual information; Nonrigid registration; n-dimensional scale invariant feature transform (n-SIFT)