31 citations · 125 across the 24 of their papers we have counts for
8 papers · 1 filter
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…
AMLP: Adjustable Masking Lesion Patches for Self-Supervised Medical Image Segmentation
Xiangtao Wang, Ruizhi Wang, Thomas Lukasiewicz +1
Self-supervised masked image modeling (MIM) methods have shown promising performances on analyzing natural images. However, directly applying such methods to medical image segmenta…
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…
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…
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…
RSG: A Simple but Effective Module for Learning Imbalanced Datasets
Jianfeng Wang, Thomas Lukasiewicz, Xiaolin Hu +2
Imbalanced datasets widely exist in practice and area great challenge for training deep neural models with agood generalization on infrequent classes. In this work, wepropose a new…
w-Net: Dual Supervised Medical Image Segmentation Model with Multi-Dimensional Attention and Cascade Multi-Scale Convolution
Bo Wang, Lei Wang, Junyang Chen +3
Deep learning-based medical image segmentation technology aims at automatic recognizing and annotating objects on the medical image. Non-local attention and feature learning by mul…
Segmentation is All You Need
Zehua Cheng, Yuxiang Wu, Zhenghua Xu +2
Region proposal mechanisms are essential for existing deep learning approaches to object detection in images. Although they can generally achieve a good detection performance under…