Bayesian Estimation of Intra-operative Deformation for Image-Guided Surgery Using 3-D Ultrasound
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
Tracking Liver Motion Using 3-D Ultrasound and a Surface-Based Statistical Shape Model
MMBIA '01 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA'01)
IEEE Transactions on Information Technology in Biomedicine
Non-Rigid Ultrasound Image Registration Based on Intensity and Local Phase Information
Journal of Signal Processing Systems
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
Wavelet-based variational deformable registration for ultrasound
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Fast deformable registration of 3d-ultrasound data using a variational approach
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
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3D registration of ultrasound images is an important and fast-growing research area with various medical applications, such as image-guided radiotherapy and surgery. However, this registration process is extremely challenging due to the deformation of soft tissue and the existence of speckles in these images. This paper presents a novel intra-modality elastic registration technique for 3D ultrasound images. It uses the general concept of attribute vectors to find the corresponding voxels in the fixed and moving images. The method does not require any pre-segmentation and does not employ any numerical optimization procedure. Therefore, the computational requirements are very low and it has the potential to be used for real-time applications. The technique is implemented and tested for 3D ultrasound images of liver, captured by a 3D ultrasound transducer. The results show that the method is sufficiently accurate and robust and is not easily trapped with local minima.