Detecting breast lesion in videos is crucial for computer-aided diagnosi...
Fundus photography is prone to suffer from image quality degradation tha...
In the medical field, federated learning commonly deals with highly
imba...
Limited labeled data makes it hard to train models from scratch in medic...
The annotation scarcity of medical image segmentation poses challenges i...
Frontotemporal Dementia (FTD) diagnosis has been successfully progress u...
Recently, Segmenting Anything has taken an important step towards genera...
The inherent challenge of multimodal fusion is to precisely capture the
...
Cutting out an object and estimating its opacity mask, known as image
ma...
Multimodal machine learning has achieved remarkable progress in a wide r...
Robust and accurate segmentation for elongated physiological structures ...
Pathologic myopia (PM) is a common blinding retinal degeneration suffere...
Federated Magnetic Resonance Imaging (MRI) reconstruction enables multip...
Large language models have demonstrated surprising ability to perform
in...
Deep learning models have shown promising performance in the field of
di...
As scientific and technological advancements result from human intellect...
Diffusion Probabilistic Models have recently shown remarkable performanc...
In recent years, Denoising Diffusion Models have demonstrated remarkable...
Classification and segmentation are crucial in medical image analysis as...
The collection of medical image datasets is a demanding and laborious pr...
Multimodality eye disease screening is crucial in ophthalmology as it
in...
Shadow removal in a single image has received increasing attention in re...
Medical phrase grounding (MPG) aims to locate the most relevant region i...
Deep learning based image enhancement models have largely improved the
r...
The use of AI systems in healthcare for the early screening of diseases ...
Federated learning (FL), as an effective decentralized distributed learn...
Medical image segmentation (MIS) is essential for supporting disease
dia...
Focusing on the complicated pathological features, such as blurred
bound...
Different from the general visual classification, some classification ta...
Automated detecting lung infections from computed tomography (CT) data p...
As an economical and efficient fundus imaging modality, retinal fundus i...
GAMMA Challenge is organized to encourage the AI models to screen the
gl...
Unsupervised domain adaptation (UDA) has attracted considerable attentio...
Glaucoma causes irreversible vision loss due to damage to the optic nerv...
Breast lesion detection in ultrasound is critical for breast cancer
diag...
Despite recent improvements in the accuracy of brain tumor segmentation,...
Fundus photography is a routine examination in clinics to diagnose and
m...
Effectively integrating multi-scale information is of considerable
signi...
In this paper, we present a novel end-to-end group collaborative learnin...
Generative models have been widely proposed in image recognition to gene...
Existing multi-view classification algorithms focus on promoting accurac...
The goal of co-salient object detection (CoSOD) is to discover salient
o...
In the deep learning era, we present the first comprehensive video polyp...
Federated semi-supervised learning (FSSL) aims to derive a global model ...
Federated learning (FL) allows multiple clients to collectively train a
...
Cataracts are the leading cause of vision loss worldwide. Restoration
al...
Glaucoma is the second leading cause of blindness and is the leading cau...
Age-related macular degeneration (AMD) is the leading cause of visual
im...
Color fundus photography and Optical Coherence Tomography (OCT) are the ...
Subspace clustering is a classical technique that has been widely used f...