10 citations · 22 across the 11 of their papers we have counts for
5 papers · 1 filter
AirMorph: Topology-Preserving Deep Learning for Pulmonary Airway Analysis
Minghui Zhang, Chenyu Li, Fangfang Xie +8
Accurate anatomical labeling and analysis of the pulmonary structure and its surrounding anatomy from thoracic CT is getting increasingly important for understanding the etilogy of…
From Real Artifacts to Virtual Reference: A Robust Framework for Translating Endoscopic Images
Junyang Wu, Fangfang Xie, Jiayuan Sun +2
Domain adaptation, which bridges the distributions across different modalities, plays a crucial role in multimodal medical image analysis. In endoscopic imaging, combining pre-oper…
Multi-site, Multi-domain Airway Tree Modeling (ATM'22): A Public Benchmark for Pulmonary Airway Segmentation
Minghui Zhang, Yangqian Wu, Hanxiao Zhang +33
Open international challenges are becoming the de facto standard for assessing computer vision and image analysis algorithms. In recent years, new methods have extended the reach o…
Re-thinking and Re-labeling LIDC-IDRI for Robust Pulmonary Cancer Prediction
Hanxiao Zhang, Xiao Gu, Minghui Zhang +6
The LIDC-IDRI database is the most popular benchmark for lung cancer prediction. However, with subjective assessment from radiologists, nodules in LIDC may have entirely different…
Faithful learning with sure data for lung nodule diagnosis
Hanxiao Zhang, Liang Chen, Xiao Gu +6
Recent evolution in deep learning has proven its value for CT-based lung nodule classification. Most current techniques are intrinsically black-box systems, suffering from two gene…