A Surface-Volume Matching Process Using a Markov Random Field Model for Cardiac Motion Extraction in MSCT Imaging

Multislice Computed Tomography (MSCT) scanners offers new perspectives for cardiac kinetics evaluation with 3D time image sequences of high contrast and spatio-temporal resolutions. A new method is proposed for cardiac motion extraction in Multislice CT. Based on a 3D surface-volume matching process, it provides the detection of the heart left cavities along the acquired sequence and the estimation of their 3D surface velocity fields. A 3D segmentation step and surface reconstruction process are first applied on only one image of the sequence to obtain a 3D mesh representation for one t time. A Markov Random Field model is defined to find best correspondences between 3D mesh nodes at t time and voxels in the next volume at t + 1 time. A simulated annealing is used to perform a global optimization of the correspondences. First results obtained on simulated and real data show the good behaviour of this method.

[1]  R. Leahy,et al.  Computation of 3-D velocity fields from 3-D cine CT images of a human heart. , 1991, IEEE transactions on medical imaging.

[2]  James S. Duncan,et al.  Estimation of 3D left ventricular deformation from echocardiography , 2001, Medical Image Anal..

[3]  Dmitry B. Goldgof,et al.  3D nonrigid motion analysis under small deformations , 1995, Image Vis. Comput..

[4]  Nicholas Ayache,et al.  Dense Non-Rigid Motion Estimation in Sequences of Medical Images Using Differential Constraints , 1995, CAIP.

[5]  Denis Friboulet,et al.  Estimation of three-dimensional cardiac velocity fields: assessment of a differential method and application to three-dimensional CT data , 1997, Medical Image Anal..

[6]  Christine Toumoulin,et al.  Evaluation of a 3D Segmentation Software for the Coronary Characterization in Multi-slice Computed Tomography , 2003, FIMH.

[7]  Patrick Clarysse,et al.  Exploratory analysis of the spatio-temporal deformation of the myocardium during systole from tagged MRI , 2002, IEEE Transactions on Biomedical Engineering.

[8]  Patrick Bouthemy,et al.  Multimodal Estimation of Discontinuous Optical Flow using Markov Random Fields , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Thomas S. Huang,et al.  Modeling, Analysis, and Visualization of Left Ventricle Shape and Motion by Hierarchical Decomposition , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Soo-Mi Choi,et al.  Motion visualization of human left ventricle with a time-varying deformable model for cardiac diagnosis , 2001, Comput. Animat. Virtual Worlds.

[11]  Alejandro F. Frangi,et al.  Three-dimensional modeling for functional analysis of cardiac images, a review , 2001, IEEE Transactions on Medical Imaging.

[12]  C D Claussen,et al.  Accuracy and reliability of quantitative measurements in coronary arteries by multi-slice computed tomography: experimental and initial clinical results. , 2001, Clinical radiology.

[13]  James S. Duncan,et al.  Point-tracked quantitative analysis of left ventricular surface motion from 3-D image sequences , 2000, IEEE Transactions on Medical Imaging.

[14]  J. Duncan,et al.  Point – Tracked Quantitative Analysis of Left Ventricular Motion from 3 D Image Sequences , 2000 .

[15]  J. Alison Noble,et al.  2D+T acoustic boundary detection in echocardiography , 2000, Medical Image Anal..

[16]  Laurent D. Cohen,et al.  Tracking and motion analysis of the left ventricle with deformable superquadrics , 1996, Medical Image Anal..

[17]  J. Besag.  Spatial Interaction and the Statistical Analysis of Lattice Systems , 1974 .

[18]  Amitabha Das,et al.  Estimation of Occlusion and Dense Motion Fields in a Bidirectional Bayesian Framework , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  M. Garreau,et al.  Cardiac motion extraction in multislice computed tomography by using a 3D hierarchical surface matching process , 2004, Computers in Cardiology, 2004.

[20]  Jerry L. Prince,et al.  Motion estimation from tagged MR image sequences , 1992, IEEE Trans. Medical Imaging.

[21]  James S. Duncan,et al.  Bending and stretching models for LV wall motion analysis from curves and surfaces , 1992, Image Vis. Comput..

[22]  Richard A Robb,et al.  Parametric visualization methods for the quantitative assessment of myocardial motion. , 2003, Academic radiology.