Scaling Theorems for Zero Crossings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Free-form deformation of solid geometric models
SIGGRAPH '86 Proceedings of the 13th annual conference on Computer graphics and interactive techniques
Inferring Surface Trace and Differential Structure from 3-D Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Framework for Automatic Landmark Identification Using a New Method of Nonrigid Correspondence
IEEE Transactions on Pattern Analysis and Machine Intelligence
On Critical Point Detection of Digital Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence
A New Kinetic Modeling Scheme for the Human Left Ventricle Wall Motion with MR-Tagging Imaging
Proceedings of the First International Workshop on Functional Imaging and Modeling of the Heart
FIMH'05 Proceedings of the Third international conference on Functional Imaging and Modeling of the Heart
Inferring the left ventricle dynamical behavior using a free-form deformations model
Mathematics and Computers in Simulation
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This paper describes a method for estimating the deformation field of the Left Ventricle (LV) walls from a 4–D Multi Slice Computerized Tomography (MSCT) database. The approach is composed of two stages: in the first, a 2–D non–rigid correspondence algorithm matches a set of contours on the LV at consecutive time instants. In the second, a 3–D curvature–based correspondence algorithm is used to optimize the initial approximate correspondence. The dense displacement field is obtained based on the optimized correspondence. Parameters like LV volume, radial contraction and torsion are estimated. The algorithm is validated on synthetic objects and tested using a 4–D MSCT database. Results are promising as the error of the displacement vectors is 2.69 ± 1.38 mm using synthetic objects and, when tested in real data, local parameters extracted agree with values obtained using tagged magnetic resonance imaging.