A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Model Tags: Direct 3D Tracking of Heart Wall Motion from Tagged Magnetic Resonance Images
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms
International Journal of Computer Vision
Numerical Recipes 3rd Edition: The Art of Scientific Computing
Numerical Recipes 3rd Edition: The Art of Scientific Computing
GPU Accelerated Non-rigid Registration for the Evaluation of Cardiac Function
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
A Nonrigid Image Registration Framework for Identification of Tissue Mechanical Parameters
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
Nonrigid image registration with subdivision lattices: application to cardiac MR image analysis
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
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We develop a real time element-space non-rigid registration technique for cardiac motion tracking, enabling fast and automatic analysis of myocardial strain in tagged magnetic resonance (MR) cines. Non-rigid registration is achieved by minimizing the sum of squared differences for all pixels within a high order finite-element (FE) model customized to the specific geometry of the heart. The objective function and its derivatives are calculated in element space, and converted to image space using the Jacobian of the transformation. This enables an anisotropic distribution of user-defined model parameters, which can be customized to the application, thereby achieving fast estimations which require fewer degrees of freedom for a given level of accuracy than standard isotropic methods. A graphics processing unit (GPU) accelerated Levenberg-Marquardt procedure was implemented in Compute Unified Device Architecture (CUDA) environment to provide a fast, robust optimization procedure. The method was validated in 30 patients with wall motion abnormalities by comparison with ground truth provided by an independent expert observer using a manually-guided analysis procedure. A heart model comprising 32 parameters was capable of processing 36.5 frames per second, with an error in circumferential strain of -1.97 ±1.18%. For comparison, a standard isotropic free-form deformation method requiring 324 parameters had greater error (-3.70±1.15%) and slower frame-rate (4.5 frames/sec). In conclusion, GPU accelerated custom element-space non-rigid image registration enables real time automatic tracking of cardiac motion, and accurate estimation of myocardial strain in tagged MR cines.