Coupled B-snake grids and constrained thin-plate splines for analysis of 2-D tissue deformations from tagged MRI

Magnetic resonance imaging (MRI) is unique in its ability to noninvasively and selectively alter tissue magnetization and create tagged patterns within a deforming body such as the heart muscle. The resulting patterns define a time-varying curvilinear coordinate system on the tissue, which the authors track with coupled B-snake grids. B-spline bases provide local control of shape, compact representation, and parametric continuity. Efficient spline warps are proposed which warp an area in the plane such that two embedded snake grids obtained from two tagged frames are brought into registration, interpolating a dense displacement vector field. The reconstructed vector field adheres to the known displacement information at the intersections, forces corresponding snakes to be warped into one another, and for all other points in the plane, where no information is available, a C/sup 1/ continuous vector field is interpolated. The implementation proposed in this paper improves on the authors' previous variational-based implementation and generalizes warp methods to include biologically relevant contiguous open curves, in addition to standard landmark points. The methods are validated with a cardiac motion simulator, in addition to in-vivo tagging data sets.

[1]  Frank E. Rademakers,et al.  Dissociation Between Left Ventricular Untwisting and Filling: Accentuation by Catecholamines , 1992, Circulation.

[2]  Jerry L. Prince,et al.  Reconstruction of 3-D left ventricular motion from planar tagged cardiac MR images: an estimation theoretic approach , 1995, IEEE Trans. Medical Imaging.

[3]  A. Gueziec,et al.  Surface representation with deformable splines: using decoupled variables , 1995 .

[4]  I D Wilkinson,et al.  Measurement of regional left ventricular function using labelled magnetic resonance imaging. , 1991, The British journal of radiology.

[5]  W. O'Dell,et al.  Three-dimensional myocardial deformations: calculation with displacement field fitting to tagged MR images. , 1995, Radiology.

[6]  W. Eric L. Grimson,et al.  An implementation of a computational theory of visual surface interpolation , 1983, Comput. Vis. Graph. Image Process..

[7]  A. Douglas,et al.  Description of the deformation of the left ventricle by a kinematic model. , 1992, Journal of biomechanics.

[8]  Yongmin Kim,et al.  A methodology for evaluation of boundary detection algorithms on medical images , 1997, IEEE Transactions on Medical Imaging.

[9]  R Beyar,et al.  Noninvasive quantification of left ventricular rotational deformation in normal humans using magnetic resonance imaging myocardial tagging. , 1990, Circulation.

[10]  Jerry L Prince,et al.  Cardiac motion simulator for tagged MRI , 1996, Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis.

[11]  L Axel,et al.  Circumferential Myocardial Shortening in the Normal Human Left Ventricle: Assessment by Magnetic Resonance Imaging Using Spatial Modulation of Magnetization , 1991, Circulation.

[12]  J. Gore,et al.  MR Physics-Based Snake Tracking and Dense Deformations from Tagged Cardiac Images , 1994 .

[13]  Demetri Terzopoulos,et al.  Multiresolution computation of visible-surface representations , 1984 .

[14]  Alistair A. Young,et al.  Tracking and finite element analysis of stripe deformation in magnetic resonance tagging , 1995, IEEE Trans. Medical Imaging.

[15]  E. McVeigh,et al.  Cardiac Tagging with Breath‐Hold Cine MRI , 1992, Magnetic resonance in medicine.

[16]  Amir A. Amini,et al.  Snakes and Splines for Tracking Non-Rigid Heart Motion , 1996, ECCV.

[17]  Amir A. Amini,et al.  Quantitative coronary angiography with deformable spline models , 1997, IEEE Transactions on Medical Imaging.

[18]  N Reichek,et al.  Magnetic resonance imaging for assessment of myocardial function. , 1991, Magnetic resonance quarterly.

[19]  Jerry L. Prince,et al.  Tag and contour detection in tagged MR images of the left ventricle , 1994, IEEE Trans. Medical Imaging.

[20]  Pengcheng Shi,et al.  Energy-minimizing deformable grids for tracking tagged MR cardiac images , 1992, Proceedings Computers in Cardiology.

[21]  L. Axel,et al.  MR imaging of motion with spatial modulation of magnetization. , 1989, Radiology.

[22]  Fred L. Bookstein,et al.  Principal Warps: Thin-Plate Splines and the Decomposition of Deformations , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  Jinah Park,et al.  Volumetric deformable models with parameter functions: A new approach to the 3D motion analysis of the LV from MRI-SPAMM , 1995, Proceedings of IEEE International Conference on Computer Vision.

[24]  E. Zerhouni,et al.  Human heart: tagging with MR imaging--a method for noninvasive assessment of myocardial motion. , 1988, Radiology.

[25]  Petia Radeva,et al.  Deformable B-Solids and Implicit Snakes for 3D Localization and Tracking of SPAMM MRI Data , 1997, Comput. Vis. Image Underst..

[26]  W. Grossman Assessment of regional myocardial function. , 1986, Journal of the American College of Cardiology.