Medical image analysis
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Medical image analysis · Apr 2009
Phase unwrapping of MR images using Phi UN--a fast and robust region growing algorithm.
We present a fully automated phase unwrapping algorithm (Phi UN) which is optimized for high-resolution magnetic resonance imaging data. The algorithm is a region growing method and uses separate quality maps for seed finding and unwrapping which are retrieved from the full complex information of the data. ⋯ Phi UN, however, was significantly faster at low signal to noise ratio (SNR) and data with a more complex phase topography, making it particularly suitable for applications with low SNR and high spatial resolution. Phi UN is freely available to the scientific community.
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Medical image analysis · Apr 2009
A fast, model-independent method for cerebral cortical thickness estimation using MRI.
Several algorithms for measuring the cortical thickness in the human brain from MR image volumes have been described in the literature, the majority of which rely on fitting deformable models to the inner and outer cortical surfaces. However, the constraints applied during the model fitting process in order to enforce spherical topology and to fit the outer cortical surface in narrow sulci, where the cerebrospinal fluid (CSF) channel may be obscured by partial voluming, may introduce bias in some circumstances, and greatly increase the processor time required. In this paper we describe an alternative, voxel based technique that measures the cortical thickness using inversion recovery anatomical MR images. ⋯ The method was applied to 119 normal volunteers, and validated through extensive comparisons with published measurements of both cortical thickness and rate of thickness change with age. We conclude that the proposed technique is generally faster than deformable model-based alternatives, and free from the possibility of model bias, but suffers no reduction in accuracy. In particular, it will be applicable in data sets showing severe cortical atrophy, where thinning of the gyri leads to points of high curvature, and so the fitting of deformable models is problematic.