Image Segmentation Based on the Integration of Markov Random Fields and Deformable Models
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
MMBIA '01 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA'01)
IEEE Transactions on Image Processing
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
Fast Motion Tracking of Tagged MRI Using Angle-Preserving Meshless Registration
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
Automated tag tracking using Gabor filter bank, robust point matching, and deformable models
FIMH'07 Proceedings of the 4th international conference on Functional imaging and modeling of the heart
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
2D motion analysis of long axis cardiac tagged MRI
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
A new methodology for multiscale myocardial deformation and strain analysis based on tagging MRI
Journal of Biomedical Imaging - Special issue on mathematical methods for images and surfaces
Driving dynamic cardiac model adaptation with MR-tagging displacement information
FIMH'11 Proceedings of the 6th international conference on Functional imaging and modeling of the heart
Cardiac motion estimation using covariant derivatives and helmholtz decomposition
STACOM'11 Proceedings of the Second international conference on Statistical Atlases and Computational Models of the Heart: imaging and modelling challenges
Estimation of in vivo myocardial fibre strain using an architectural atlas of the human heart
FIMH'13 Proceedings of the 7th international conference on Functional Imaging and Modeling of the Heart
| Hi-index | 0.00 |
Magnetic resonance tagging technique measures the deformation of the heart wall by overlying darker tag lines onto the brighter myocardium and tracking their motion during the heart cycle. In this paper, we propose a new spline-based methodology for constructing a dense cardiac displacement map based on the tag tracking result. In this new approach, the deformed tags are tracked using a Gabor filter-based technique and smoothed using implicit splines. Then we measure the displacement in the myocardium of both ventricles using a new spline interpolation model. This model uses rough segmentation results to set up break points along tag tracking spline so that the local myocardium deformation will not be influenced by the tag information in the blood or the deformation in other parts of the myocardium. The displacements in x- and y-directions are calculated separately and are combined later to form the final displacement map. This method accepts either a tag grid or separate horizontal and vertical tag lines as its input by adjusting the offsets of images taken at different breath hold. The method can compute dense displacement maps of the myocardium for time phases during systole and diastole. The approach has been quantatively validated on phantom images and been tested on more than 20 sets of in-vivo heart data.