AI Medical Compendium Journal:
NeuroImage

Showing 21 to 30 of 380 articles

High resolution multi-delay arterial spin labeling with self-supervised deep learning denoising for pediatric choroid plexus perfusion MRI.

NeuroImage
Choroid plexus (CP) is an important brain structure that produces cerebrospinal fluid (CSF). CP perfusion has been studied using multi-delay arterial spin labeling (MD-ASL) in adults but not in pediatric populations due to the challenge of small CP s...

Beyond averaging: A transformer approach to decoding event related brain potentials.

NeuroImage
The objective of this study is to assess the potential of a transformer-based deep learning approach applied to event-related brain potentials (ERPs) derived from electroencephalographic (EEG) data. Traditional methods involve averaging the EEG signa...

Decoding cortical folding patterns in marmosets using machine learning and large language model.

NeuroImage
Macroscale neuroimaging results have revealed significant differences in the structural and functional connectivity patterns of gyri and sulci in the primate cerebral cortex. Despite these findings, understanding these differences at the molecular le...

A joint three-plane physics-constrained deep learning based polynomial fitting approach for MR electrical properties tomography.

NeuroImage
Magnetic resonance electrical properties tomography can extract the electrical properties of in-vivo tissue. To estimate tissue electrical properties, various reconstruction algorithms have been proposed. However, physics-based reconstructions are pr...

Adapting to evolving MRI data: A transfer learning approach for Alzheimer's disease prediction.

NeuroImage
Integrating 3D magnetic resonance imaging (MRI) with machine learning has shown promising results in healthcare, especially in detecting Alzheimer's Disease (AD). However, changes in MRI technologies and acquisition protocols often yield limited data...

Development and routine implementation of deep learning algorithm for automatic brain metastases segmentation on MRI for RANO-BM criteria follow-up.

NeuroImage
RATIONALE AND OBJECTIVES: The RANO-BM criteria, which employ a one-dimensional measurement of the largest diameter, are imperfect due to the fact that the lesion volume is neither isotropic nor homogeneous. Furthermore, this approach is inherently ti...

A novel way to use cross-validation to measure connectivity by machine learning allows epilepsy surgery outcome prediction.

NeuroImage
The rate of success of epilepsy surgery, ensuring seizure-freedom, is limited by the lack of epileptogenicity biomarkers. Previous evidence supports the critical role of functional connectivity during seizure generation to characterize the epileptoge...

Deep learning applied to the segmentation of rodent brain MRI data outperforms noisy ground truth on full-fledged brain atlases.

NeuroImage
Translational magnetic resonance imaging of the rodent brain provides invaluable information for preclinical drug development. However, the automated segmentation of such images for quantitative analyses is limited compared to human brain imaging mai...

Differentiating atypical parkinsonian syndromes with hyperbolic few-shot contrastive learning.

NeuroImage
Differences in iron accumulation patterns have been observed in susceptibility-weighted images across different classes of atypical parkinsonian syndromes (APS). Deep learning methods have shown great potential in automatically detecting these differ...

Generative modeling of the Circle of Willis using 3D-StyleGAN.

NeuroImage
The circle of Willis (CoW) is a network of cerebral arteries with significant inter-individual anatomical variations. Deep learning has been used to characterize and quantify the status of the CoW in various applications for the diagnosis and treatme...