PURPOSE: We focused on deep learning for a reduction of motion artifacts in MRI. It is difficult to collect a large number of images with and without motion artifacts from clinical images. The purpose of this study was to create motion artifact image...
We applied graph theory analysis on resting-state functional magnetic resonance imaging data to evaluate sex differences of brain functional topography in normal controls (NCs), early mild cognitive impairment (eMCI), and AD patients. These metrics w...
BACKGROUND: The need for accurate and timely detection of Intracranial hemorrhage (ICH) is of utmost importance to avoid untoward incidents that may even lead to death. Hence, this presented work leverages the ability of a pretrained deep convolution...
BACKGROUND: Advanced machine learning methods can aid in the identification of dementia risk using neuroimaging-derived features including FDG-PET. However, to enable the translation of these methods and test their usefulness in clinical practice, it...
BACKGROUND: The automatic segmentation of brain tumour from MRI medical images is mainly covered in this review. Recently, state-of-the-art performance is provided by deep learning- based approaches in the field of image classification, segmentation,...
BACKGROUND: Variations of image segmentation techniques, particularly those used for Brain MRI segmentation, vary in complexity from basic standard Fuzzy C-means (FCM) to more complex and enhanced FCM techniques.
BACKGROUND: In recent years, many convolutional neural networks (CNN) have been proposed for the classification of Alzheimer's disease. Due to memory constraints, many of the proposed CNNs work at a 2D slice-level or 3D patch-level.
Cerebral cortex (New York, N.Y. : 1991)
Jan 1, 2021
Accurate and automated reconstruction of the in vivo human cerebral cortical surface from anatomical magnetic resonance (MR) images facilitates the quantitative analysis of cortical structure. Anatomical MR images with sub-millimeter isotropic spatia...
With the increasing size of datasets used in medical imaging research, the need for automated data curation is arising. One important data curation task is the structured organization of a dataset for preserving integrity and ensuring reusability. Th...
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