Medical Imaging Analysis

GIRNet: Co-Learning Semantic-aware Unsupervised Segmentation for Pathological Image Registration
The registration of pathological images plays an important role in medical applications. Despite its significance, most researchers in …
Liu Yang, Gu Shi
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GIRNet: Co-Learning Semantic-aware Unsupervised Segmentation for Pathological Image Registration
Detecting brain lesions in suspected acute ischemic stroke with CT-based synthetic MRI using generative adversarial networks
$\mathbf{Background}$
Difficulties in detecting brain lesions in acute ischemic stroke (AIS) have convinced researchers to use computed …
Hu Na, Zhang Tianwei, Wu Yifan, Tang Biqiu, Li Minlong, Song Bin, Gong Qiyong, Wu Min, Gu Shi, Lui Su
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Detecting brain lesions in suspected acute ischemic stroke with CT-based synthetic MRI using generative adversarial networks
A unified framework for generalized low-shot medical image segmentation with scarce data
Medical image segmentation has achieved remarkable advancements using deep neural networks (DNNs). However, DNNs often need big amounts …
Cui Hengji, Wei Dong, Ma Kai, Gu Shi, Zheng Yefeng
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A unified framework for generalized low-shot medical image segmentation with scarce data
Robust medical image segmentation from non-expert annotations with tri-network
Deep convolutional neural networks (CNNs) have achieved commendable results on a variety of medical image segmentation tasks. However, …
Zhang Tianwei, Yu Lequan, Hu Na, Lv Su, Gu Shi
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Robust medical image segmentation from non-expert annotations with tri-network