Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Recovery of Soft Tissue Object Deformation from 3D Image Sequences Using Biomechanical Models
IPMI '99 Proceedings of the 16th International Conference on Information Processing in Medical Imaging
Atlas-Based Segmentation and Tracking of 3D Cardiac MR Images Using Non-rigid Registration
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part I
Consistent estimation of cardiac motions by 4D image registration
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Surface alignment of 3d spherical harmonic models: application to cardiac MRI analysis
MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
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This paper presents a nonrigid image registration method for cardiac deformation recovery from 3D MR image sequences. The main contribution of this work is that the method is mathematically guaranteed to generate incompressible deformations. This is a desirable property since the myocardium has been shown to be close to incompressible. The method is based on an incompressible deformable model that can include all four cardiac chambers and has a relatively small number of parameters. The myocardium needs to be segmented in an initial frame after which the method automatically determines the tissue deformation everywhere in the myocardium throughout the cardiac cycle. The method has been tested with four 3D cardiac MR image sequences for the left and right ventricles and it has been evaluated against manual segmentation. The volume agreement between the model and the manual segmentation exceeds 90% and the distance between the model and the manually generated endocardial and epicardial surface is 1.65mm on average.