An ugly duckling is an obviously different skin lesion from surrounding
...
In this work, we contribute towards the development of video-based epile...
Reconstructing soft tissues from stereo endoscope videos is an essential...
Long-tailed multi-label visual recognition (LTML) task is a highly
chall...
Digital pathology based on whole slide images (WSIs) plays a key role in...
Semi-supervised learning (SSL) has attracted much attention since it red...
Skin lesion recognition using deep learning has made remarkable progress...
Deep neural networks have demonstrated promising performance on image
re...
Content-based medical image retrieval is an important diagnostic tool th...
Usually, lesions are not isolated but are associated with the surroundin...
Three-dimensional (3D) images, such as CT, MRI, and PET, are common in
m...
Recently, a lot of automated white blood cells (WBC) or leukocyte
classi...
The self-attention mechanism, successfully employed with the transformer...
Existing unsupervised domain adaptation methods based on adversarial lea...
Recent years have witnessed a rapid development of automated methods for...
Recent studies have validated the association between cardiovascular dis...
Most of the medical tasks naturally exhibit a long-tailed distribution d...
The key towards learning informative node representations in graphs lies...
We propose a new video camouflaged object detection (VCOD) framework tha...
Semi-supervised segmentation remains challenging in medical imaging sinc...
The annotation of disease severity for medical image datasets often reli...
Convolutional Neural Network models have successfully detected retinal
i...
Medical Visual Question Answering (VQA) is a combination of medical
arti...
In the real world, medical datasets often exhibit a long-tailed data
dis...
The current generation of deep neural networks has achieved close-to-hum...
Dermatologists often diagnose or rule out early melanoma by evaluating t...
In this paper, we proposed a novel mutual consistency network (MC-Net+) ...
Retinal vessel segmentation plays a key role in computer-aided screening...
In medical image segmentation, it is difficult to mark ambiguous areas
a...
In the real world, medical datasets often exhibit a long-tailed data
dis...
Semi-supervised learning has attracted great attention in the field of
m...
Deep neural networks are known to be data-driven and label noise can hav...
Recently, ultra-widefield (UWF) 200-degree fundus imaging by Optos camer...
To reduce the human efforts in neural network design, Neural Architectur...
Existing studies for automated melanoma diagnosis are based on single-ti...
The need for comprehensive and automated screening methods for retinal i...
For decades, advances in retinal imaging technology have enabled effecti...
An integral part of video analysis and surveillance is temporal activity...
Recent works show that Generative Adversarial Networks (GANs) can be
suc...
Lesion detection from computed tomography (CT) scans is challenging comp...
Registration is an important task in automated medical image analysis.
A...
We present a novel learning framework for vehicle recognition from a sin...
We present a novel learning framework for vehicle recognition from a sin...
Endowing continuum robots with compliance while it is interacting with t...
Localization of chest pathologies in chest X-ray images is a challenging...
The widely used ChestX-ray14 dataset addresses an important medical imag...
We present a conceptually new and flexible method for multi-class open s...
Fine-grained classification is a relatively new field that has concentra...
This paper explores a pragmatic approach to multiple object tracking whe...
We present a novel deep convolutional neural network (DCNN) system for
f...