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Diffusion tensor imaging allows to infer brain connectivity from white matter, which can then be investigated aiming at finding possible biomarkers of disease. The usual initial step in graph construction is to identify the nodes in the brain using a predefined atlas. However, atlases are usually not considering the white matter structure. As a result, atlas-based brain parcellation and, hence, brain...
Brain development is a protracted and dynamic process. Many studies have charted the trajectory of white matter development, but here we sought to map these effects in greater detail, based on a large set of fiber tracts automatically extracted from HARDI (high angular resolution diffusion imaging) at 4 tesla. We used autoMATE (automated multi-atlas tract extraction) to extract diffusivity measures...
We present the largest population-based heritability study of the human brain structural connectome, including a pathology-sensitive extension, the disconnectome. The disconnectome maps the effect of white matter lesions throughout the brain. The connectome and disconnectome were generated from diffusion-weighted images of 3255 unrelated subjects from the Rotterdam Study aged between 45 and 99 years...
The evolutionary success of ants and other social insects is considered to be intrinsically linked to division of labor and emergent collective intelligence. The role of the brains of individual ants in generating these processes, however, is poorly understood. One genus of ant of special interest is Pheidole, which includes more than a thousand species, most of which are dimorphic, i.e. their colonies...
In this paper, we propose an end-to-end trainable Convolutional Neural Network (CNN) architecture called the M-net, for segmenting deep (human) brain structures from Magnetic Resonance Images (MRI). A novel scheme is used to learn to combine and represent 3D context information of a given slice in a 2D slice. Consequently, the M-net utilizes only 2D convolution though it operates on 3D data, which...
Autism Spectrum Disorder (ASD) is a complex developmental disorder affecting 1 in 68 children in the United States. While the prevalence may be on the rise, we currently lack a firm understanding of the etiology of the disease, and diagnosis is made purely on behavioral observation and informant report. As one potential method for improving our understanding of ASD, the current study took a network-level...
Resting-state fMRI provides challenging data that needs to be analyzed without knowledge about timing or duration of neuronal events. The “total activation” framework is one recent approach that combines temporal and spatial regularization to deconvolve the fMRI signals; i.e., undo them from the influence of the hemodynamic response. The temporal regularization is using generalized total variation...
Accurate registration plays a critical role in group-wise functional Magnetic Resonance Imaging (fMRI) image analysis, as spatial correspondence among different brain images is a prerequisite for inferring meaningful patterns. However, the problem is challenging and remains open, and more effort should be made to advance the state-of-the-art image registration methods for fMRI images. Inspired by...
In order to improve the preclinical diagnose of Alzheimer's disease (AD), there is a great deal of interest in analyzing the AD related brain structural changes with magnetic resonance image (MRI) analyses. As the major features, variation of the structural connectivity and the cortical surface morphometry provide different views of structural changes to determine whether AD is present on presymptomatic...
Hyperechogenicity of the substantia nigra (SN) in the “butterfly shaped” midbrain is a widely recognized diagnostic marker to differentiate between the early stages of Parkinsons Disease (PD) and other diseases which cause parkinsonian symptoms. While clinical differentiation of these diseases can be difficult, hyperechogenicity of the SN is only common in PD patients. Transcranial B-mode Ultrasound...
White matter segmentation is an essential step to study whole-brain structural connectivity via diffusion MRI white matter tractography. One important goal of segmentation methods is to improve consistency of the white matter segmentations across multiple subjects. In this study, we quantitatively compare two popular white matter segmentation strategies, i.e., a cortical-parcellation-based method...
Segmentation of the developing cortical plate from MRI data of the post-mortem fetal brain is highly challenging due to partial volume effects, low contrast, and heterogeneous maturation caused by ongoing myelination processes. We present a new atlas-free method that segments the inner and outer boundaries of the cortical plate in fetal brains by exploiting diffusion-weighted imaging cues and using...
This paper introduces a comprehensive computer-aided diagnosis (CAD) system for autism diagnosis that integrates anatomical and functional information of the brain using both structural and functional magnetic resonance (MR) brain images. In order to move towards the idea of personalized medicine, analysis of the brain's Brodmann areas (BAs) is conducted to reach a diagnosis decision on the local...
The relation between normal and pathological aging and the cerebrovascular component is still unclear. In this context, the common marmoset, which has the advantage of enabling longitudinal studies over a reasonable timeframe, appears as a good pre-clinical model. However, there is still a lack of quantitative information on the macrovascular structure of the marmoset brain. In this paper, we investigate...
In the field of medical imaging, atlases are generally used for computer-aided anatomical and functional parcellation of a brain, and for distinguishing which tissue is normal and which is pathologic. The purpose of this paper is to create a set of human brain atlas probability maps, which would be publicly available for clinical and research community and could be applied to computer tomography (CT)...
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