AIMC Topic: Brain

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Deep-learning-based attenuation correction in dynamic [O]HO studies using PET/MRI in healthy volunteers.

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
Quantitative [O]HO positron emission tomography (PET) is the accepted reference method for regional cerebral blood flow (rCBF) quantification. To perform reliable quantitative [O]HO-PET studies in PET/MRI scanners, MRI-based attenuation-correction (M...

Rapid high-quality PET Patlak parametric image generation based on direct reconstruction and temporal nonlocal neural network.

NeuroImage
Parametric imaging based on dynamic positron emission tomography (PET) has wide applications in neurology. Compared to indirect methods, direct reconstruction methods, which reconstruct parametric images directly from the raw PET data, have superior ...

The divided brain: Functional brain asymmetry underlying self-construal.

NeuroImage
Self-construal (orientations of independence and interdependence) is a fundamental concept that guides human behaviour, and it is linked to a large number of brain regions. However, understanding the connectivity of these regions and the critical pri...

MoDL-QSM: Model-based deep learning for quantitative susceptibility mapping.

NeuroImage
Quantitative susceptibility mapping (QSM) has demonstrated great potential in quantifying tissue susceptibility in various brain diseases. However, the intrinsic ill-posed inverse problem relating the tissue phase to the underlying susceptibility dis...

Delineating between-subject heterogeneity in alpha networks with Spatio-Spectral Eigenmodes.

NeuroImage
Between subject variability in the spatial and spectral structure of oscillatory networks can be highly informative but poses a considerable analytic challenge. Here, we describe a data-driven modal decomposition of a multivariate autoregressive mode...

On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: Chronicles of the MEMENTO challenge.

NeuroImage
Diffusion MRI (dMRI) has become an invaluable tool to assess the microstructural organization of brain tissue. Depending on the specific acquisition settings, the dMRI signal encodes specific properties of the underlying diffusion process. In the las...

Convolutional neural networks for cytoarchitectonic brain mapping at large scale.

NeuroImage
Human brain atlases provide spatial reference systems for data characterizing brain organization at different levels, coming from different brains. Cytoarchitecture is a basic principle of the microstructural organization of the brain, as regional di...

Within node connectivity changes, not simply edge changes, influence graph theory measures in functional connectivity studies of the brain.

NeuroImage
Interest in understanding the organization of the brain has led to the application of graph theory methods across a wide array of functional connectivity studies. The fundamental basis of a graph is the node. Recent work has shown that functional nod...

Machine learning compensates fold-change method and highlights oxidative phosphorylation in the brain transcriptome of Alzheimer's disease.

Scientific reports
Alzheimer's disease (AD) is a neurodegenerative disorder causing 70% of dementia cases. However, the mechanism of disease development is still elusive. Despite the availability of a wide range of biological data, a comprehensive understanding of AD's...