Extended free-form deformation: a sculpturing tool for 3D geometric modeling
SIGGRAPH '90 Proceedings of the 17th annual conference on Computer graphics and interactive techniques
Introductory Techniques for 3-D Computer Vision
Introductory Techniques for 3-D Computer Vision
Motion Analysis of the Right Ventricle From MRI Images
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Reconstruction of detailed left ventricle motion from TMRI using deformable models
FIMH'07 Proceedings of the 4th international conference on Functional imaging and modeling of the heart
FIMH'11 Proceedings of the 6th international conference on Functional imaging and modeling of the heart
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Quantification of left ventricular (LV) deformation from 3D image sequences (4D data) is important for the assessment of myocardial viability, which can have important clinical implications. To date, feature information from either Magnetic Resonance, computed tomographic or echocardiographic image data has been assembled with the help of different interpolative models to estimate LV deformation. These models typically are designed to be computationally efficient (e.g. regularizing strategies using B-splines) or more physically realistic (e.g. finite element approximations to biomechanical models), but rarely incorporate both notions. In this paper, we combine an approach to the extraction and matching of image-derived point features based on local shape properties with a boundary element model. This overall scheme is intended to be both computationally efficient and physically realistic. In order to illustrate this, we compute strains using our method on canine 4D MR image sequences and compare the results to those found from a B-spline-based method (termed extended free-form deformation (EFFD)) and a method based on finite elements (FEM). All results are compared to displacements found using implanted markers, taken to be a gold standard.