93 citations · 117 across the 9 of their papers we have counts for
4 papers · 1 filter
Identifying the key components in ResNet-50 for diabetic retinopathy grading from fundus images: a systematic investigation
Yijin Huang, Li Lin, Pujin Cheng +3
Although deep learning based diabetic retinopathy (DR) classification methods typically benefit from well-designed architectures of convolutional neural networks, the training sett…
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…
BSDA-Net: A Boundary Shape and Distance Aware Joint Learning Framework for Segmenting and Classifying OCTA Images
Li Lin, Zhonghua Wang, Jiewei Wu +5
Optical coherence tomography angiography (OCTA) is a novel non-invasive imaging technique that allows visualizations of vasculature and foveal avascular zone (FAZ) across retinal l…