Deformable models with sparsity constraints for cardiac motion analysis.
Deformable models integrate bottom-up information derived from image appearance cues and top-down priori knowledge of the shape. They have been widely used with success in medical image analysis. One limitation of traditional deformable models is that the information extracted from the image data may contain gross errors, which adversely affect the deformation accuracy. To alleviate this issue, we introduce a new family of deformable models that are inspired from the compressed sensing, a technique for accurate signal reconstruction by harnessing some sparseness priors. In this paper, we employ sparsity constraints to handle the outliers or gross errors, and integrate them seamlessly with deformable models. The proposed new formulation is applied to the analysis of cardiac motion using tagged magnetic resonance imaging (tMRI), where the automated tagging line tracking results are very noisy due to the poor image quality. Our new deformable models track the heart motion robustly, and the resulting strains are consistent with those calculated from manual labels.
Department of Computer Science, Rutgers University, Piscataway, NJ, USA.
Yang
Y
Yu
Department of Computer Science, University of North Carolina at Charlotte, NC, USA. Electronic address: rutgers.shaoting@gmail.com.
Shaoting
S
Zhang
Department of Industrial and Systems Engineering, Rutgers University, Piscataway, NJ, USA.
Kang
K
Li
Department of Computer Science, Rutgers University, Piscataway, NJ, USA.
Dimitris
D
Metaxas
Radiology Department, New York University, New York, NY, USA.
Leon
L
Axel
D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D007089:Image Enhancement / Q000379:methods; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D051379:Mice; D008955:Models, Cardiovascular; D009038:Motion; D009200:Myocardial Contraction / Q000502:physiology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016277:Ventricular Function, Left / Q000502:physiology*
Cardiac motion analysis; Compressed sensing; Deformable models; Sparse regularization