51 citations · 128 across the 22 of their papers we have counts for
7 papers · 1 filter
GAMMA Challenge:Glaucoma grAding from Multi-Modality imAges
Junde Wu, Huihui Fang, Fei Li +26
Color fundus photography and Optical Coherence Tomography (OCT) are the two most cost-effective tools for glaucoma screening. Both two modalities of images have prominent biomarker…
LDDMM-Face: Large Deformation Diffeomorphic Metric Learning for Flexible and Consistent Face Alignment
Huilin Yang, Junyan Lyu, Pujin Cheng +1
We innovatively propose a flexible and consistent face alignment framework, LDDMM-Face, the key contribution of which is a deformation layer that naturally embeds facial geometry i…
Lesion-based Contrastive Learning for Diabetic Retinopathy Grading from Fundus Images
Yijin Huang, Li Lin, Pujin Cheng +2
Manually annotating medical images is extremely expensive, especially for large-scale datasets. Self-supervised contrastive learning has been explored to learn feature representati…
A Survey on Deep Learning of Small Sample in Biomedical Image Analysis
Pengyi Zhang, Yunxin Zhong, Yulin Deng +2
The success of deep learning has been witnessed as a promising technique for computer-aided biomedical image analysis, due to end-to-end learning framework and availability of larg…
Brain segmentation based on multi-atlas guided 3D fully convolutional network ensembles
Jiong Wu, Xiaoying Tang
In this study, we proposed and validated a multi-atlas guided 3D fully convolutional network (FCN) ensemble model (M-FCN) for segmenting brain regions of interest (ROIs) from struc…
A post-processing method to improve the white matter hyperintensity segmentation accuracy for randomly-initialized U-net
Yue Zhang, Wanli Chen, Yifan Chen +1
White matter hyperintensity (WMH) is commonly found in elder individuals and appears to be associated with brain diseases. U-net is a convolutional network that has been widely use…
Prostate Segmentation using 2D Bridged U-net
Wanli Chen, Yue Zhang, Junjun He +4
In this paper, we focus on three problems in deep learning based medical image segmentation. Firstly, U-net, as a popular model for medical image segmentation, is difficult to trai…