Alyssa H. Zhu

This study uses quantitative susceptibility mapping to analyze choroid plexus calcifications in UK Biobank participants, finding age-related increases and associations with various health conditions.

FastEBM improves disease progression modeling by using a diffusion-based Markov framework, achieving better accuracy and speed than existing methods in both synthetic and real-world data.

This paper develops a lifespan normative model of brain white matter microstructure using diffusion MRI data from 54,583 individuals, enabling detection of microstructural deviations in diseases like Alzheimer's and 22q11.2 deletion syndrome.

The paper uses GWAS to identify genetic variants associated with corpus callosum morphometry and links them to cortical structure and neuropsychiatric disorders.

The paper creates lifespan reference curves for white matter microstructure using diffusion MRI data from multiple datasets and validates them with ApoE4 risk factor analysis.

This paper applies a spherical harmonics-based deep learning model to MRI-derived brain shape metrics to predict age, sex, and Alzheimer's disease diagnosis, showing strong performance in classification and regression tasks.

NeuroDISK automates continuous updates of neuroimaging genetic analyses using new data, replicating and refining previous findings from the ENIGMA consortium.

The paper evaluates test-retest reliability of brain imaging metrics across multiple sites and scanners, finding significant differences in reliability between scanner types.

This paper uses a GAN-based style transfer approach to harmonize multi-site MRI images without site labels, effectively removing cross-site variation while preserving clinical patterns.

This paper evaluates the reliability and compatibility of brain metrics from different FreeSurfer versions using test-retest data and finds low compatibility between newer and older versions for specific regions.

This study identifies 388 genetic associations with regional brain sulcal morphology using UK Biobank data, highlighting gene expression and eQTL patterns and providing a 3D visualization resource.

This study examines age and sex effects on white matter microstructure in 15,628 older adults using dMRI models, finding that advanced models like TDF and NODDI detect these effects most sensitively.

This paper uses a GAN-based style transfer approach to harmonize multi-site MRI images without requiring site labels or traveling subjects.

This paper introduces a 2D slice-based recurrent neural network for brain age prediction, achieving comparable or better performance than existing methods with fewer parameters and faster training.

This study examines how exogenous sex hormones affect white matter aging in postmenopausal women using diffusion MRI data from the UK Biobank, finding steeper aging trajectories in hormone therapy users.

The paper creates normative percentile charts for subcortical brain volumes across adulthood and examines age-by-sex interactions and associations with APOE genotype in a large UK Biobank sample.

This study compares a new convolutional neural network-based hippocampal segmentation method (Hippodeep) with existing methods on stroke MRIs, finding Hippodeep more accurate in quality control and spatial accuracy.

This study identifies white matter microstructural differences across epilepsy syndromes using diffusion MRI data from a large multicenter cohort.

This study identifies genetic variants linked to longitudinal brain structure changes across the lifespan using MRI data from 15,640 individuals.

The paper identifies genetic loci associated with human cortical structure and finds genetic correlations with neuropsychiatric disorders.

This study finds that perinatal exposure to maternal smoking is associated with reduced cortical surface area in specific brain regions and increased disease risk in middle-aged and older adults.