7 citations · 28 across the 27 of their papers we have counts for
16 papers · 1 filter
Review and Recommendations for using Artificial Intelligence in Intracoronary Optical Coherence Tomography Analysis
Xu Chen, Yuan Huang, Benn Jessney +5
Artificial intelligence (AI) methodologies hold great promise for the rapid and accurate diagnosis of coronary artery disease (CAD) from intravascular optical coherent tomography (…
Learning Task-Specific Sampling Strategy for Sparse-View CT Reconstruction
Liutao Yang, Jiahao Huang, Yingying Fang +4
Sparse-View Computed Tomography (SVCT) offers low-dose and fast imaging but suffers from severe artifacts. Optimizing the sampling strategy is an essential approach to improving th…
Predicting conversion of mild cognitive impairment to Alzheimer's disease
Yiran Wei, Stephen J. Price, Carola-Bibiane Schönlieb +1
Alzheimer's disease (AD) is the most common age-related dementia. Mild cognitive impairment (MCI) is the early stage of cognitive decline before AD. It is crucial to predict the MC…
Focal Attention Networks: optimising attention for biomedical image segmentation
Michael Yeung, Leonardo Rundo, Evis Sala +2
In recent years, there has been increasing interest to incorporate attention into deep learning architectures for biomedical image segmentation. The modular design of attention mec…
Incorporating Boundary Uncertainty into loss functions for biomedical image segmentation
Michael Yeung, Guang Yang, Evis Sala +2
Manual segmentation is used as the gold-standard for evaluating neural networks on automated image segmentation tasks. Due to considerable heterogeneity in shapes, colours and text…
Predicting isocitrate dehydrogenase mutation status in glioma using structural brain networks and graph neural networks
Yiran Wei, Yonghao Li, Xi Chen +3
Glioma is a common malignant brain tumor with distinct survival among patients. The isocitrate dehydrogenase (IDH) gene mutation provides critical diagnostic and prognostic value f…