Xiangrui Zeng

This paper introduces VesSynth, a vessel segmentation framework trained on synthetic data that achieves state-of-the-art accuracy across multiple imaging modalities and spatial resolutions.

This paper presents high-resolution diffusion MRI data from macaque and human brains, enabling detailed mapping of axonal architecture and microstructure.

DUAL improves cryo-electron tomography by simultaneously denoising and simulating data without labeled training data, enhancing structural detection and annotation.

This paper introduces a semi-supervised segmentation model for identifying supragranular and infragranular layers in human cerebral cortex MRI scans with high precision.

CAMO evaluates omics congruence between model organisms and humans by analyzing differential analysis, concordance, pathway investigations, and subnetwork detection.

DISCA uses deep learning to automatically cluster cryo-ET data into homogeneous structural subsets without templates or labels.

The paper introduces CPI, a tool for integrating multiple transcriptomic studies to identify consensual and differential pathway enrichment patterns, and applies it to psychiatric disorder data.

This study models ZIKV transmission through sexual contact networks with double asymmetric percolation, revealing a quadruple epidemic transition.