output
20192021
most citedDual-Sampling Attention Network for Diagnosis of COVID-19 from Community Acquired Pneumonia

25 citations

6 papers

cs.LG20218 cited

Task-wise Split Gradient Boosting Trees for Multi-center Diabetes Prediction

Mingcheng Chen, Zhenghui Wang, Zhiyun Zhao +14

Diabetes prediction is an important data science application in the social healthcare domain. There exist two main challenges in the diabetes prediction task: data heterogeneity si…

cs.CV2021

Flip Learning: Erase to Segment

Yuhao Huang, Xin Yang, Yuxin Zou +7

Nodule segmentation from breast ultrasound images is challenging yet essential for the diagnosis. Weakly-supervised segmentation (WSS) can help reduce time-consuming and cumbersome…

cs.CV202025 cited

Dual-Sampling Attention Network for Diagnosis of COVID-19 from Community Acquired Pneumonia

Xi Ouyang, Jiayu Huo, Liming Xia +15

The coronavirus disease (COVID-19) is rapidly spreading all over the world, and has infected more than 1,436,000 people in more than 200 countries and territories as of April 9, 20…

eess.IV20194 cited

The Domain Shift Problem of Medical Image Segmentation and Vendor-Adaptation by Unet-GAN

Wenjun Yan, Yuanyuan Wang, Shengjia Gu +4

Convolutional neural network (CNN), in particular the Unet, is a powerful method for medical image segmentation. To date Unet has demonstrated state-of-art performance in many comp…

cs.CV201916 cited

Signet Ring Cell Detection With a Semi-supervised Learning Framework

Jiahui Li, Shuang Yang, Xiaodi Huang +6

Signet ring cell carcinoma is a type of rare adenocarcinoma with poor prognosis. Early detection leads to huge improvement of patients' survival rate. However, pathologists can onl…

eess.IV20197 cited

Learning-based Single-step Quantitative Susceptibility Mapping Reconstruction Without Brain Extraction

Hongjiang Wei, Steven Cao, Yuyao Zhang +4

Quantitative susceptibility mapping (QSM) estimates the underlying tissue magnetic susceptibility from MRI gradient-echo phase signal and typically requires several processing step…