5 papers
GenFAR: A generalized representation of brain structure, derived from 49,246 multi-cohort MRIs via deep learning
Vishnu M. Bashyam, Guray Erus, Junhao Wen +29
Deep learning models for neuroimaging have largely been developed for individual tasks, limiting knowledge transfer across applications. Here we introduce GenFAR, a modular deep le…
Automated Optical Density Normalization for Myelin Quantification: Cross-Modal Validation with 7T Ex Vivo MRI
Zahra Khodakarami, Sheina Emrani, Pulkit Khandelwal +21
White matter hyperintensities (WMH) are bright regions on T2-weighted magnetic resonance imaging (MRI) scans and are associated with cerebrovascular pathology and neurodegeneration…
ICHOR: A Robust Representation Learning Approach for ASL CBF Maps with Self-Supervised Masked Autoencoders
Xavier Beltran-Urbano, Yiran Li, Xinglin Zeng +10
Arterial spin labeling (ASL) perfusion MRI allows direct quantification of regional cerebral blood flow (CBF) without exogenous contrast, enabling noninvasive measurements that can…
Achieving detailed medial temporal lobe segmentation with upsampled isotropic training from implicit neural representation
Yue Li, Pulkit Khandelwal, Rohit Jena +8
Imaging biomarkers in magnetic resonance imaging (MRI) are important tools for diagnosing, tracking and treating Alzheimer's disease (AD). Neurofibrillary tau pathology in AD is cl…
Imaging Biomarkers for Neurodegenerative Diseases from Detailed Segmentation of Medial Temporal Lobe Subregions on in vivo Brain MRI Using Upsampling Strategy Guided by High-resolution ex vivo MRI
Yue Li, Pulkit Khandelwal, Long Xie +21
The medial temporal lobe (MTL) is a region impacted extensively and non-uniformly in early stages of Alzheimer's disease (AD). Regional MTL morphometric measures extracted from mag…