111 citations · 210 across the 22 of their papers we have counts for
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Two-stage Cytopathological Image Synthesis for Augmenting Cervical Abnormality Screening
Zhenrong Shen, Manman Fei, Xin Wang +4
Automatic thin-prep cytologic test (TCT) screening can assist pathologists in finding cervical abnormality towards accurate and efficient cervical cancer diagnosis. Current automat…
CellGAN: Conditional Cervical Cell Synthesis for Augmenting Cytopathological Image Classification
Zhenrong Shen, Maosong Cao, Sheng Wang +2
Automatic examination of thin-prep cytologic test (TCT) slides can assist pathologists in finding cervical abnormality for accurate and efficient cancer screening. Current solution…
Learning Better Contrastive View from Radiologist's Gaze
Sheng Wang, Zixu Zhuang, Xi Ouyang +6
Recent self-supervised contrastive learning methods greatly benefit from the Siamese structure that aims to minimizing distances between positive pairs. These methods usually apply…
Domain Generalization for Mammographic Image Analysis with Contrastive Learning
Zheren Li, Zhiming Cui, Lichi Zhang +10
The deep learning technique has been shown to be effectively addressed several image analysis tasks in the computer-aided diagnosis scheme for mammography. The training of an effic…
PA-GM: Position-Aware Learning of Embedding Networks for Deep Graph Matching
Dongdong Chen, Yuxing Dai, Lichi Zhang +1
Graph matching can be formalized as a combinatorial optimization problem, where there are corresponding relationships between pairs of nodes that can be represented as edges. This…
RCPS: Rectified Contrastive Pseudo Supervision for Semi-Supervised Medical Image Segmentation
Xiangyu Zhao, Zengxin Qi, Sheng Wang +4
Medical image segmentation methods are generally designed as fully-supervised to guarantee model performance, which require a significant amount of expert annotated samples that ar…
Task Decomposition and Synchronization for Semantic Biomedical Image Segmentation
Xuhua Ren, Lichi Zhang, Sahar Ahmad +5
Semantic segmentation is essentially important to biomedical image analysis. Many recent works mainly focus on integrating the Fully Convolutional Network (FCN) architecture with s…