IEEE Trans Image Process - Atlas generation for subcortical and ventricular structures with its applications in shape analysis.

Tópicos

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Resumo

Atlas-driven morphometric analysis has received great attention for studying anatomical shape variation across clinical populations in neuroimaging research as it provides a local coordinate representation for understanding the family of anatomic observations. We present a procedure for generating atlas of subcortical and ventricular structures, including amygdala, hippocampus, caudate, putamen, globus pallidus, thalamus, and lateral ventricles, using the large deformation diffeomorphic metric atlas generation algorithm. The atlas was built based on manually labeled volumes of 41 subjects randomly selected from the database of Open Access Series of Imaging Studies (OASIS, 10 young adults, 10 middle-age adults, 10 healthy elders, and 11 patients with dementia). We show that the estimated atlas is representative of the population in terms of its metric distance to each individual subject in the population. In the application of detecting shape variations, using the estimated atlas may potentially increase statistical power in identifying group shape difference when comparing with using a single subject atlas. In shape-based classification, the metric distances between subjects and each of within-class estimated atlases construct a shape feature space, which allows for performing a variety of classification algorithms to distinguish anatomies.

Resumo Limpo

atlasdriven morphometr analysi receiv great attent studi anatom shape variat across clinic popul neuroimag research provid local coordin represent understand famili anatom observ present procedur generat atlas subcort ventricular structur includ amygdala hippocampus caudat putamen globus pallidus thalamus later ventricl use larg deform diffeomorph metric atlas generat algorithm atlas built base manual label volum subject random select databas open access seri imag studi oasi young adult middleag adult healthi elder patient dementia show estim atlas repres popul term metric distanc individu subject popul applic detect shape variat use estim atlas may potenti increas statist power identifi group shape differ compar use singl subject atlas shapebas classif metric distanc subject withinclass estim atlas construct shape featur space allow perform varieti classif algorithm distinguish anatomi

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