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7 papers · 1 filter
Polar-Net: A Clinical-Friendly Model for Alzheimer's Disease Detection in OCTA Images
Shouyue Liu, Jinkui Hao, Yanwu Xu +7
Optical Coherence Tomography Angiography (OCTA) is a promising tool for detecting Alzheimer's disease (AD) by imaging the retinal microvasculature. Ophthalmologists commonly use re…
A Generic Fundus Image Enhancement Network Boosted by Frequency Self-supervised Representation Learning
Heng Li, Haofeng Liu, Huazhu Fu +5
Fundus photography is prone to suffer from image quality degradation that impacts clinical examination performed by ophthalmologists or intelligent systems. Though enhancement algo…
Degradation-invariant Enhancement of Fundus Images via Pyramid Constraint Network
Haofeng Liu, Heng Li, Huazhu Fu +4
As an economical and efficient fundus imaging modality, retinal fundus images have been widely adopted in clinical fundus examination. Unfortunately, fundus images often suffer fro…
ADAM Challenge: Detecting Age-related Macular Degeneration from Fundus Images
Huihui Fang, Fei Li, Huazhu Fu +28
Age-related macular degeneration (AMD) is the leading cause of visual impairment among elderly in the world. Early detection of AMD is of great importance, as the vision loss cause…
Boosting RGB-D Saliency Detection by Leveraging Unlabeled RGB Images
Xiaoqiang Wang, Lei Zhu, Siliang Tang +5
Training deep models for RGB-D salient object detection (SOD) often requires a large number of labeled RGB-D images. However, RGB-D data is not easily acquired, which limits the de…
Medical Image Segmentation Using Squeeze-and-Expansion Transformers
Shaohua Li, Xiuchao Sui, Xiangde Luo +3
Medical image segmentation is important for computer-aided diagnosis. Good segmentation demands the model to see the big picture and fine details simultaneously, i.e., to learn ima…