Comput Math Methods Med - Parametric mapping of brain tissues from diffusion kurtosis tensor.

Tópicos

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Resumo

Diffusion kurtosis imaging (DKI) is a new diffusion magnetic resonance imaging (MRI) technique to go beyond the shortages of conventional diffusion tensor imaging (DTI) from the assumption that water diffuse in biological tissue is Gaussian. Kurtosis is used to measure the deviation of water diffusion from Gaussian model, which is called non-Gaussian, in DKI. However, the high-order kurtosis tensor in the model brings great difficulties in feature extraction. In this study, parameters like fractional anisotropy of kurtosis eigenvalues (FAek) and mean values of kurtosis eigenvalues (Mek) were proposed, and regional analysis was performed for 4 different tissues: corpus callosum, crossing fibers, thalamus, and cerebral cortex, compared with other parameters. Scatterplot analysis and Gaussian mixture decomposition of different parametric maps are used for tissues identification. Diffusion kurtosis information extracted from kurtosis tensor presented a more detailed classification of tissues actually as well as clinical significance, and the FAek of D-eigenvalues showed good sensitivity of tissues complexity which is important for further study of DKI.

Resumo Limpo

diffus kurtosi imag dki new diffus magnet reson imag mri techniqu go beyond shortag convent diffus tensor imag dti assumpt water diffus biolog tissu gaussian kurtosi use measur deviat water diffus gaussian model call nongaussian dki howev highord kurtosi tensor model bring great difficulti featur extract studi paramet like fraction anisotropi kurtosi eigenvalu faek mean valu kurtosi eigenvalu mek propos region analysi perform differ tissu corpus callosum cross fiber thalamus cerebr cortex compar paramet scatterplot analysi gaussian mixtur decomposit differ parametr map use tissu identif diffus kurtosi inform extract kurtosi tensor present detail classif tissu actual well clinic signific faek deigenvalu show good sensit tissu complex import studi dki

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