Dunja Simičić

The paper estimates age-related changes in metabolite relaxation times in pediatric thalamus using MRS and provides linear equations for age-specific correction.

This paper introduces an AI-integrated MRI pulse sequence that detects and adapts to out-of-voxel artifacts in real-time, improving data quality through gradient adjustments.

The paper introduces a method to identify out-of-voxel signals in MRS by analyzing phase cycles, leading to improved suppression of artifacts through optimized gradients.

This paper optimizes a gradient scheme for PRESS-localized edited MRS to suppress out-of-voxel artifacts using a volume-based likelihood model and genetic algorithm.

This paper introduces a data-driven algorithm using AIC to determine the optimal basis set composition for 1H-MRS, showing improved accuracy in identifying metabolites.

The paper measures metabolite T1 relaxation times in healthy adults across age groups and finds age-related decreases in several metabolites in specific brain regions.

The paper investigates age-related changes in metabolite T2 relaxation times across the adult lifespan in a multi-site cohort, finding significant declines in several metabolites with aging.

This paper develops a water relaxation atlas to correct metabolite concentrations in MRS by integrating age and region-specific relaxation values into the analysis workflow.

This study compares the test-retest reproducibility of DESPOT and QALAS for T1 and T2 mapping in healthy volunteers, finding QALAS provides better reproducibility and reduced acquisition time.

This study compares 1D and 2D linear-combination modeling of MRS data, finding similar accuracy and uncertainty estimation between the two approaches, with 2D showing stability under correlated noise.

This paper introduces a model-based frequency-and-phase correction method for 1H MRS data using 2D linear-combination modeling, showing improved performance over traditional approaches at low SNR.