Background and objective: Sharing of medical data is required to enable the cross-agency
flow of healthcare information and construct high-accuracy computer-aided diagnosis systems…

This paper presents a soft-label anonymous gastric X-ray image distillation method based
on a gradient descent approach. The sharing of medical data is demanded to construct high-…

Sharing medical datasets between hospitals is challenging because of the privacy-protection
problem and the massive cost of transmitting and storing many high-resolution medical …

The global outbreak of the Coronavirus 2019 (COVID-19) has overloaded worldwide
healthcare systems. Computer-aided diagnosis for COVID-19 fast detection and patient triage is …

Aims The aim of this study was to determine whether deep convolutional neural network (DCNN)-based
features can represent the difference between cardiac sarcoidosis (CS) and non-…

Purpose Considering several patients screened due to COVID-19 pandemic, computer-aided
detection has strong potential in assisting clinical workflow efficiency and reducing the …

Background Deep learning has become a new trend of image recognition tasks in the field
of medicine. We developed an automated gastritis detection system using double-contrast …

In this paper, we aim to tackle the problem of unsupervised domain adaptation (UDA) of
semantic segmentation and improve the UDA performance with a novel conception of learning …

In this paper, we present a novel defect detection model based on an improved U-Net
architecture. As a semantic segmentation task, the defect detection task has the problems of …

This paper proposes a novel self-supervised learning method for learning better representations
with small batch sizes. Many self-supervised learning methods based on certain forms …