26 citations · 56 across the 6 of their papers we have counts for
6 papers
Revisiting Medical Image Retrieval via Knowledge Consolidation
Yang Nan, Huichi Zhou, Xiaodan Xing +5
As artificial intelligence and digital medicine increasingly permeate healthcare systems, robust governance frameworks are essential to ensure ethical, secure, and effective implem…
Towards Modality- and Sampling-Universal Learning Strategies for Accelerating Cardiovascular Imaging: Summary of the CMRxRecon2024 Challenge
Fanwen Wang, Zi Wang, Yan Li +60
Cardiovascular health is vital to human well-being, and cardiac magnetic resonance (CMR) imaging is considered the {clinical reference standard} for diagnosing cardiovascular disea…
Can Generative AI Replace Immunofluorescent Staining Processes? A Comparison Study of Synthetically Generated CellPainting Images from Brightfield
Xiaodan Xing, Siofra Murdoch, Chunling Tang +7
Cell imaging assays utilizing fluorescence stains are essential for observing sub-cellular organelles and their responses to perturbations. Immunofluorescent staining process is ro…
Enhancing Global Sensitivity and Uncertainty Quantification in Medical Image Reconstruction with Monte Carlo Arbitrary-Masked Mamba
Jiahao Huang, Liutao Yang, Fanwen Wang +8
Deep learning has been extensively applied in medical image reconstruction, where Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs) represent the predominant para…
Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge
Yang Nan, Xiaodan Xing, Shiyi Wang +38
Airway-related quantitative imaging biomarkers are crucial for examination, diagnosis, and prognosis in pulmonary diseases. However, the manual delineation of airway trees remains…
Real-Time Edge Intelligence in the Making: A Collaborative Learning Framework via Federated Meta-Learning
Sen Lin, Guang Yang, Junshan Zhang
Many IoT applications at the network edge demand intelligent decisions in a real-time manner. The edge device alone, however, often cannot achieve real-time edge intelligence due t…