Advanced MRI Techniques and Applications

This study investigates how echo train length (ETL) affects microvascular specificity in SE-EPI BOLD fMRI, showing increased macrovascular contamination with longer ETL durations.

SACNet corrects susceptibility artifacts in dMRI scans using a registration network with neuroanatomical constraints, showing improved performance across diverse datasets.

The paper uses two non-contrast MRI methods to investigate the glymphatic system's response to sleep and aging in humans.

This study examines how brain glutathione levels change with age and their link to cognitive function in healthy adults, finding age-related declines in specific brain regions and sex differences in GSH dynamics.

This paper develops a data-driven method for analyzing fMRI data across studies, revealing consistent patterns in BOLD time series and demonstrating its generalizability and robustness.

This study validates time-resolved fMRI for detecting sub-second timing differences in neural responses by testing how stimulus duration and intensity affect hemodynamic signals.

This study measures hippocampal perfusion using 7T MRI and finds significant subfield differences, with CA1 having the lowest perfusion, influenced by vascular proximity and cytoarchitecture.

mrQA is an open-source tool that automatically assesses MRI protocol compliance across datasets, revealing widespread non-compliance in neuroimaging studies.

This paper introduces TRIGGER, a 3T MRI technique for high-resolution neural activity recording in awake humans, showing millisecond temporal resolution and hemispheric response timing.

The paper introduces a deep brain imaging dataset from the Bergen Breakfast Scanning Club project, detailing data acquisition and preprocessing protocols for three subjects over one year.

This paper introduces a high-resolution, fast-sampled fMRI technique for whole-brain BOLD signal measurement, demonstrating improved spatial and temporal resolution in human studies.

This paper introduces a new fMRI method called SELINE to improve laminar-specific BOLD signal detection by reducing vein effects and improving spatial resolution.

This study shows diurnal oscillations exist in MRI metrics of healthy adults and bipolar disorder patients, with similar rhythmicity parameters except for greater phase variation in cerebral blood flow in patients.

This paper introduces a dual-projection based ICA denoising method to remove scanner/site effects in multi-site MRI data, showing improved performance over traditional ICA and GLM methods.

The paper develops a method to estimate tissue perfusion using MRI data and a porous media flow model, validated with synthetic data from complex models.

This study examines layer dependence of monocular and binocular responses in human V1 using VASO and BOLD at 7T, finding that VASO better differentiates columnar responses and BOLD signal is confounded by pial veins.

This paper improves 1H-MRS quality in the brainstem periaqueductal grey using spectral registration, showing increased SNR and reduced linewidth and CRLBs.

This paper introduces Deli-CS, a method that accelerates spatio-temporal MRI reconstruction using deep learning-initialized compressed sensing, reducing time and resource usage while maintaining quality.

This paper introduces a domain-agnostic MR reconstruction framework using a randomly weighted neural network that achieves performance comparable to state-of-the-art methods with minimal training data.

This paper introduces QUIQI, a method to restore homoscedasticity in MRI relaxometry data by using weighted least squares, improving statistical analysis robustness.

This paper identifies and addresses quality-related biases in structural MRI analyses of children by improving automated quality control methods.

This study compares fMRI noise correction methods using peripheral physiological signals and data-driven approaches, finding that peripheral-based methods offer more reliable noise reduction, especially in high-noise regions.

This study compares four parametric transit time distributions for DSC-MRI perfusion analysis, finding the gamma distribution to be most stable, fast, and robust to noise.

The paper uses multi-compartment T2 relaxometry to show that parenchymal cerebrospinal fluid fraction increases quadratically with age in brain tissue.

This study compares aMRI and DENSE for brain tissue motion assessment, finding aMRI provides comparable results to DENSE in specific directions despite lower amplification.

This study compares PRESS and sLASER for detecting metabolite-age correlations in brain regions, finding similar results despite technical differences.

This study shows real-time motion feedback reduces head movement during task-based fMRI, with a moderate effect size, but effectiveness varies by participant and task.

The paper examines age-related changes in metabolite T1 relaxation times in brain regions using a cross-sectional dataset and finds significant decreases in white-matter-rich areas with age.

This paper presents an optimized awake mouse fMRI paradigm that reduces stress and motion artifacts, improving functional connectivity detection.

This paper conducts a meta-analysis of 23Na-MRI studies to estimate human brain sodium concentrations by region and method, finding significant variability and providing pooled mean values.