Titlebook: Biomedical Image Registration; 6th International Wo Sébastien Ourselin,Marc Modat Conference proceedings 2014 Springer International Publis

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Automated Registration of 3D TEE Datasets of the Descending Aorta for Improved Examination and Quanth qualitative and quantitative results demonstrated the potential feasibility and accuracy of the proposed approach. Its clinical applicability could improve the assessment of aortic total plaque burden from 3D TEE images.

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Biomedical Image Registration978-3-319-08554-8Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/188053.jpg

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https://doi.org/10.1057/9780230379862om volumetric T1-weighted MRI images. A fully automatic multi-atlas registration based segmentation approach is used to label novel data. We use a standard affine registration method combined with a small deformation (non-diffeomorphic), non-linear registration method which optimises mutual informat

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Typical Country Patterns and Conclusions,ty pretreatment fan-beam CT (FBCT) images. Assuming the organ segmentations are both available on CBCT and FBCT images, methods have been proposed to use them to help the intensity-driven image registration. Due to the low contrast between soft-tissue structures exhibited in CBCT, the interobserver

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Infection Prevention and Waste Disposalel was initialised by hand-labelling the constituent bones and joints of a single sample. A coarse alignment of the entire model mesh to a sample mesh was followed by consecutive registration of individual bones and their descendants down a hierarchy. Transformation parameters for subsequent bones w

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