858 citations · 913 across the 16 of their papers we have counts for
6 papers · 1 filter
DOMINO: Domain-aware Model Calibration in Medical Image Segmentation
Skylar E. Stolte, Kyle Volle, Aprinda Indahlastari +5
Model calibration measures the agreement between the predicted probability estimates and the true correctness likelihood. Proper model calibration is vital for high-risk applicatio…
CADA: Multi-scale Collaborative Adversarial Domain Adaptation for Unsupervised Optic Disc and Cup Segmentation
Peng Liu, Charlie T. Tran, Bin Kong +1
The diversity of retinal imaging devices poses a significant challenge: domain shift, which leads to performance degradation when applying the deep learning models trained on one d…
Regression and Learning with Pixel-wise Attention for Retinal Fundus Glaucoma Segmentation and Detection
Peng Liu, Ruogu Fang
Observing retinal fundus images by an ophthalmologist is a major diagnosis approach for glaucoma. However, it is still difficult to distinguish the features of the lesion solely th…
KRNET: Image Denoising with Kernel Regulation Network
Peng Liu, Xiaoxiao Zhou, Junyiyang Li +2
One popular strategy for image denoising is to design a generalized regularization term that is capable of exploring the implicit prior underlying data observation. Convolutional n…
SDCNet: Smoothed Dense-Convolution Network for Restoring Low-Dose Cerebral CT Perfusion
Peng Liu, Ruogu Fang
With substantial public concerns on potential cancer risks and health hazards caused by the accumulated radiation exposure in medical imaging, reducing radiation dose in X-ray base…
CFEA: Collaborative Feature Ensembling Adaptation for Domain Adaptation in Unsupervised Optic Disc and Cup Segmentation
Peng Liu, Bin Kong, Zhongyu Li +2
Recently, deep neural networks have demonstrated comparable and even better performance with board-certified ophthalmologists in well-annotated datasets. However, the diversity of…