52 citations · 103 across the 5 of their papers we have counts for
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cs.CV2021★ 52 cited
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…
cs.CV2021★ 1 cited
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…
cs.CV2016★ 34 cited
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…