activity
20172022
most citedLearning Hierarchical Attention for Weakly-supervised Chest X-Ray Abnormality Localization and Diagnosis

130 citations · 182 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV2022

Image Synthesis with Disentangled Attributes for Chest X-Ray Nodule Augmentation and Detection

Zhenrong Shen, Xi Ouyang, Bin Xiao +3

Lung nodule detection in chest X-ray (CXR) images is common to early screening of lung cancers. Deep-learning-based Computer-Assisted Diagnosis (CAD) systems can support radiologis…

cs.CV2021★ 130 cited

Learning Hierarchical Attention for Weakly-supervised Chest X-Ray Abnormality Localization and Diagnosis

Xi Ouyang, Srikrishna Karanam, Ziyan Wu +5

We consider the problem of abnormality localization for clinical applications. While deep learning has driven much recent progress in medical imaging, many clinical challenges are…

eess.IV2021

Domain Generalization for Mammography Detection via Multi-style and Multi-view Contrastive Learning

Zheren Li, Zhiming Cui, Sheng Wang +7

Lesion detection is a fundamental problem in the computer-aided diagnosis scheme for mammography. The advance of deep learning techniques have made a remarkable progress for this t…

eess.IV2020★ 1 cited

mr2NST: Multi-Resolution and Multi-Reference Neural Style Transfer for Mammography

Sheng Wang, Jiayu Huo, Xi Ouyang +5

Computer-aided diagnosis with deep learning techniques has been shown to be helpful for the diagnosis of the mammography in many clinical studies. However, the image styles of diff…

cs.CV2017★ 51 cited

Automatic 3D Cardiovascular MR Segmentation with Densely-Connected Volumetric ConvNets

Lequan Yu, Jie-Zhi Cheng, Qi Dou +4

Automatic and accurate whole-heart and great vessel segmentation from 3D cardiac magnetic resonance (MR) images plays an important role in the computer-assisted diagnosis and treat…