Cardiac Motion Analysis from Ultrasound Sequences Using Non-rigid Registration
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
A New Extension of Linear Signal Processing for Estimating Local Properties and Detecting Features
Mustererkennung 2000, 22. DAGM-Symposium
Adaptive non-rigid registration of real time 3D ultrasound to cardiovascular MR images
IPMI'07 Proceedings of the 20th international conference on Information processing in medical imaging
Dynamic 3D ultrasound and MR image registration of the beating heart
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Reducing Motion Artifacts in 3-D Breast Ultrasound Using Non-linear Registration
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
The 2D analytic signal on RF and B-mode ultrasound images
IPMI'11 Proceedings of the 22nd international conference on Information processing in medical imaging
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We extend our static multimodal nonrigid registration [1] to a spatio-temporal (2D+T) co-registration of a real-time 3D ultrasound and a cardiovascular MR sequence. The motivation for our research is to assist a clinician to automatically fuse the information from multiple imaging modalities for the early diagnosis and therapy of cardiac disease. The deformation field between both sequences is decoupled into spatial and temporal components. Temporal alignment is firstly performed to re-slice both sequences using a differential registration method. Spatial alignment is then carried out between the frames corresponding to the same temporal position. The spatial deformation is modeled by the polyaffine transformation whose anchor points (or control points) are automatically detected and refined by calculating a local mis-match measure based on phase mutual information. The spatial alignment is built in an adaptive multi-scale framework to maximize the phase-based similarity measure by optimizing the parameters of the polyaffine transformation. Results demonstrate that this novel method can yield an accurate registration to particular cardiac regions.