42 citations · 77 across the 5 of their papers we have counts for
5 papers
Deep Semi-supervised Knowledge Distillation for Overlapping Cervical Cell Instance Segmentation
Yanning Zhou, Hao Chen, Huangjing Lin +1
Deep learning methods show promising results for overlapping cervical cell instance segmentation. However, in order to train a model with good generalization ability, voluminous pi…
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…
Unsupervised Bidirectional Cross-Modality Adaptation via Deeply Synergistic Image and Feature Alignment for Medical Image Segmentation
Cheng Chen, Qi Dou, Hao Chen +2
Unsupervised domain adaptation has increasingly gained interest in medical image computing, aiming to tackle the performance degradation of deep neural networks when being deployed…
CIA-Net: Robust Nuclei Instance Segmentation with Contour-aware Information Aggregation
Yanning Zhou, Omer Fahri Onder, Qi Dou +3
Accurate segmenting nuclei instances is a crucial step in computer-aided image analysis to extract rich features for cellular estimation and following diagnosis as well as treatmen…
Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation
Cheng Chen, Qi Dou, Hao Chen +2
This paper presents a novel unsupervised domain adaptation framework, called Synergistic Image and Feature Adaptation (SIFA), to effectively tackle the problem of domain shift. Dom…