Multi-atlas segmentation using clustering, local non-linear manifold embeddings and target-specific templatesTools Arthofer, Christoph (2018) Multi-atlas segmentation using clustering, local non-linear manifold embeddings and target-specific templates. PhD thesis, University of Nottingham.
AbstractMulti-atlas segmentation (MAS) has become an established technique for the automated delineation of anatomical structures. The often manually annotated labels from each of multiple pre-segmented images (atlases) are typically transferred to a target through the spatial mapping of corresponding structures of interest. The mapping can be estimated by pairwise registration between each atlas and the target or by creating an intermediate population template for spatial normalisation of atlases and targets. The former is done at runtime which is computationally expensive but provides high accuracy. In the latter approach the template can be constructed from the atlases offline requiring only one registration to the target at runtime. Although this is computationally more efficient, the composition of deformation fields can lead to decreased accuracy.
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