52 citations · 103 across the 5 of their papers we have counts for
5 papers
Graph Convolutional Networks for Multi-modality Medical Imaging: Methods, Architectures, and Clinical Applications
Kexin Ding, Mu Zhou, Zichen Wang +4
Image-based characterization and disease understanding involve integrative analysis of morphological, spatial, and topological information across biological scales. The development…
UTNet: A Hybrid Transformer Architecture for Medical Image Segmentation
Yunhe Gao, Mu Zhou, Dimitris Metaxas
Transformer architecture has emerged to be successful in a number of natural language processing tasks. However, its applications to medical vision remain largely unexplored. In th…
Low-Dose CT Denoising Using a Structure-Preserving Kernel Prediction Network
Lu Xu, Yuwei Zhang, Ying Liu +5
Low-dose CT has been a key diagnostic imaging modality to reduce the potential risk of radiation overdose to patient health. Despite recent advances, CNN-based approaches typically…
Enabling Data Diversity: Efficient Automatic Augmentation via Regularized Adversarial Training
Yunhe Gao, Zhiqiang Tang, Mu Zhou +1
Data augmentation has proved extremely useful by increasing training data variance to alleviate overfitting and improve deep neural networks' generalization performance. In medical…
3-D Convolutional Neural Networks for Glioblastoma Segmentation
Darvin Yi, Mu Zhou, Zhao Chen +1
Convolutional Neural Networks (CNN) have emerged as powerful tools for learning discriminative image features. In this paper, we propose a framework of 3-D fully CNN models for Gli…