Hongwei Li

This study examines how age, hemisphere, and sex affect claustrum volume across the human lifespan using MRI data from 3,474 healthy participants.

WMH-DualTasker is a weakly-supervised deep learning model that segments white matter hyperintensities and predicts visual ratings, outperforming supervised methods on benchmark datasets.

The paper develops a deep learning-based method to segment micro-vessels from CBV MRI images of AD mice, revealing region-specific vascular density changes in degenerated brains.

The paper introduces LOTS-IM, an unsupervised method for detecting white matter hyperintensities and MS lesions in MRI, showing better performance than existing methods.