most citedPCA: Semi-supervised Segmentation with Patch Confidence Adversarial Training

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20231 cited

C^2M-DoT: Cross-modal consistent multi-view medical report generation with domain transfer network

Ruizhi Wang, Xiangtao Wang, Jie Zhou +2

In clinical scenarios, multiple medical images with different views are usually generated simultaneously, and these images have high semantic consistency. However, most existing me…

cs.CV2023

MvCo-DoT:Multi-View Contrastive Domain Transfer Network for Medical Report Generation

Ruizhi Wang, Xiangtao Wang, Zhenghua Xu +3

In clinical scenarios, multiple medical images with different views are usually generated at the same time, and they have high semantic consistency. However, the existing medical r…

cs.CV2023

MPS-AMS: Masked Patches Selection and Adaptive Masking Strategy Based Self-Supervised Medical Image Segmentation

Xiangtao Wang, Ruizhi Wang, Biao Tian +5

Existing self-supervised learning methods based on contrastive learning and masked image modeling have demonstrated impressive performances. However, current masked image modeling…

cs.CV2023

Multi-Head Feature Pyramid Networks for Breast Mass Detection

Hexiang Zhang, Zhenghua Xu, Dan Yao +3

Analysis of X-ray images is one of the main tools to diagnose breast cancer. The ability to quickly and accurately detect the location of masses from the huge amount of image data…

eess.IV20222 cited

PCA: Semi-supervised Segmentation with Patch Confidence Adversarial Training

Zihang Xu, Zhenghua Xu, Shuo Zhang +1

Deep learning based semi-supervised learning (SSL) methods have achieved strong performance in medical image segmentation, which can alleviate doctors' expensive annotation by util…