302 citations · 898 across the 13 of their papers we have counts for
6 papers · 1 filter
Contrastive Cross-site Learning with Redesigned Net for COVID-19 CT Classification
Zhao Wang, Quande Liu, Qi Dou
The pandemic of coronavirus disease 2019 (COVID-19) has lead to a global public health crisis spreading hundreds of countries. With the continuous growth of new infections, develop…
Shape-aware Meta-learning for Generalizing Prostate MRI Segmentation to Unseen Domains
Quande Liu, Qi Dou, Pheng-Ann Heng
Model generalization capacity at domain shift (e.g., various imaging protocols and scanners) is crucial for deep learning methods in real-world clinical deployment. This paper tack…
Deep Mining External Imperfect Data for Chest X-ray Disease Screening
Luyang Luo, Lequan Yu, Hao Chen +4
Deep learning approaches have demonstrated remarkable progress in automatic Chest X-ray analysis. The data-driven feature of deep models requires training data to cover a large dis…
Semi-supervised Medical Image Classification with Relation-driven Self-ensembling Model
Quande Liu, Lequan Yu, Luyang Luo +2
Training deep neural networks usually requires a large amount of labeled data to obtain good performance. However, in medical image analysis, obtaining high-quality labels for the…
MS-Net: Multi-Site Network for Improving Prostate Segmentation with Heterogeneous MRI Data
Quande Liu, Qi Dou, Lequan Yu +1
Automated prostate segmentation in MRI is highly demanded for computer-assisted diagnosis. Recently, a variety of deep learning methods have achieved remarkable progress in this ta…
Unpaired Multi-modal Segmentation via Knowledge Distillation
Qi Dou, Quande Liu, Pheng Ann Heng +1
Multi-modal learning is typically performed with network architectures containing modality-specific layers and shared layers, utilizing co-registered images of different modalities…