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Automatic anatomical brain MRI segmentation combining label propagation and decision fusion
Regions in three-dimensional magnetic resonance (MR) brain images can be classified using protocols for manually segmenting and labeling structures. For large cohorts, time and expertise requirementsExpand
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Multi-atlas based segmentation of brain images: Atlas selection and its effect on accuracy
Quantitative research in neuroimaging often relies on anatomical segmentation of human brain MR images. Recent multi-atlas based approaches provide highly accurate structural segmentations of theExpand
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A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction
Inspired by recent advances in deep learning, we propose a framework for reconstructing dynamic sequences of 2-D cardiac magnetic resonance (MR) images from undersampled data using a deep cascade ofExpand
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Use of multicoil arrays for separation of signal from multiple slices simultaneously excited.
Increased acquisition efficiency has been achieved by exciting several slices simultaneously. The mixed data were unfolded to produce separate slices using the spatial encoding information inherentExpand
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Abnormal Cortical Development after Premature Birth Shown by Altered Allometric Scaling of Brain Growth
Background We postulated that during ontogenesis cortical surface area and cerebral volume are related by a scaling law whose exponent gives a quantitative measure of cortical development. We usedExpand
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Diffeomorphic Registration Using B-Splines
In this paper we propose a diffeomorphic non-rigid registration algorithm based on free-form deformations (FFDs) which are modelled by B-splines. In contrast to existing non-rigid registrationExpand
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Construction of a consistent high-definition spatio-temporal atlas of the developing brain using adaptive kernel regression
Medical imaging has shown that, during early development, the brain undergoes more changes in size, shape and appearance than at any other time in life. A better understanding of brain developmentExpand
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A Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction
The acquisition of Magnetic Resonance Imaging (MRI) is inherently slow. Inspired by recent advances in deep learning, we propose a framework for reconstructing MR images from undersampled data usingExpand
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A dynamic 4D probabilistic atlas of the developing brain
Probabilistic atlases are widely used in the neuroscience community as a tool for providing a standard space for comparison of subjects and as tissue priors used to enhance the intensity-basedExpand
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Segmentation of MR images via discriminative dictionary learning and sparse coding: Application to hippocampus labeling
We propose a novel method for the automatic segmentation of brain MRI images by using discriminative dictionary learning and sparse coding techniques. In the proposed method, dictionaries andExpand
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