Corey T. McMillan

This paper evaluates automated white matter lesion segmentation methods in Parkinson's disease and healthy controls, finding U-Net-pgs to be the most accurate and reliable approach across multiple metrics and datasets.

This study uses long-read sequencing to analyze haplotypes and CAA interruptions in ATXN2 CAG repeats, finding ethnicity-specific and ALS-specific associations.

The paper examines subcortical and limbic volume associations with cortical thinning and neurodegenerative pathologies in postmortem brain MRI data from multiple disease groups.

The paper develops a segmentation protocol for anterior medial temporal lobe regions and integrates it into an automated approach to improve imaging biomarkers for neurodegenerative diseases.

This study evaluates parameter-efficient fine-tuning methods for vision transformers in neuroimaging, showing they outperform full fine-tuning and training from scratch with fewer parameters.

This study examines laminar neurodegeneration patterns in bvFTD-tau and bvFTD-TDP, finding progressive SMI32-ir loss along a frontal cortical gradient in tau pathology.

This study compares anatomical and diffusion MRI for Parkinson's disease detection using deep convolutional neural networks, finding that dMRI-based models show promise for classification.

The paper compares TDP-43's transcriptional and splicing effects in muscle and neuronal cells, showing tissue-specific roles in disease.

This paper proposes a 3D CNN for classifying Alzheimer's and Parkinson's disease using T1-weighted MRI, achieving higher ROC-AUC than random forest on multiple datasets.

This study identifies JADE1 as a novel genetic factor in tauopathy through genome-wide association and functional validation in human and Drosophila models.

This study uses joint ex vivo MRI and histology to identify distinct iron-rich gliosis patterns in FTLD-Tau and FTLD-TDP, distinguishing them from other neurodegenerative conditions.