Contrastive learning based vision-language joint pre-training has emerge...
The prediction of mild cognitive impairment (MCI) conversion to Alzheime...
Deep learning-based image segmentation and detection models have largely...
Recent applications of deep convolutional neural networks in medical ima...
Federated learning (FL) enables multiple sites to collaboratively train
...
The quality of a fundus image can be compromised by numerous factors, ma...
Federated Learning (FL) is a machine learning paradigm that protects pri...
Medical image quality assessment (MIQA) is a vital prerequisite in vario...
Weakly-supervised learning (WSL) has been proposed to alleviate the conf...
Self-supervised learning (SSL) has been widely applied to learn image
re...
Machine learning algorithms minimizing the average training loss usually...
Convolutional neural networks have been widely applied to medical image
...
Federated learning (FL) is a distributed machine learning paradigm that
...
Federated Learning (FL) is a machine learning paradigm that learns from ...
Contrast-enhanced T1 (T1ce) is one of the most essential magnetic resona...
Due to the high cost of manually annotating medical images, especially f...
A large-scale labeled dataset is a key factor for the success of supervi...
Multi-modal magnetic resonance (MR) imaging provides great potential for...
Unsupervised domain adaptation has been proposed recently to tackle the
...
Fundus photography has been routinely used to document the presence and
...
Color fundus photography and Optical Coherence Tomography (OCT) are the ...
Various deep learning models have been developed to segment anatomical
s...
Glaucoma is one of the ophthalmic diseases that may cause blindness, for...
Federated Learning (FL) is an emerging learning paradigm that preserves
...
Although deep learning based diabetic retinopathy (DR) classification me...
In this paper, we proposed and validated a fully automatic pipeline for
...
We innovatively propose a flexible and consistent face alignment framewo...
Manually annotating medical images is extremely expensive, especially fo...
Optical coherence tomography angiography (OCTA) is a novel non-invasive
...
Automated infection measurement and COVID-19 diagnosis based on Chest X-...
The success of deep learning has been witnessed as a promising technique...
In this study, we proposed and validated a multi-atlas guided 3D fully
c...
White matter hyperintensity (WMH) is commonly found in elder individuals...
In this paper, we focus on three problems in deep learning based medical...