361 citations
- University of California, Los AngelesUS8 papers
- Stanford UniversityUS6 papers
- Icahn School of Medicine at Mount SinaiUS4 papers
- University of California, San FranciscoUS4 papers
- University of EdinburghGB4 papers
- Cedars-Sinai Smidt Heart InstituteUS3 papers
- Child Health and Development InstituteUS3 papers
- Shahid Beheshti University of Medical SciencesIR3 papers
- The Queen's Medical Research InstituteGB3 papers
- University of WashingtonUS3 papers
- Brigham Young UniversityUS2 papers
- Columbia UniversityUS2 papers
6 papers · 1 filter
Disentangle, align and fuse for multimodal and semi-supervised image segmentation
Agisilaos Chartsias, Giorgos Papanastasiou, Chengjia Wang +4
Magnetic resonance (MR) protocols rely on several sequences to assess pathology and organ status properly. Despite advances in image analysis, we tend to treat each sequence, here…
Disentangled Representation Learning in Cardiac Image Analysis
Agisilaos Chartsias, Thomas Joyce, Giorgos Papanastasiou +4
Typically, a medical image offers spatial information on the anatomy (and pathology) modulated by imaging specific characteristics. Many imaging modalities including Magnetic Reson…
Factorised spatial representation learning: application in semi-supervised myocardial segmentation
Agisilaos Chartsias, Thomas Joyce, Giorgos Papanastasiou +5
The success and generalisation of deep learning algorithms heavily depend on learning good feature representations. In medical imaging this entails representing anatomical informat…
Efficient and Accurate MRI Super-Resolution using a Generative Adversarial Network and 3D Multi-Level Densely Connected Network
Yuhua Chen, Feng Shi, Anthony G. Christodoulou +3
High-resolution (HR) magnetic resonance images (MRI) provide detailed anatomical information important for clinical application and quantitative image analysis. However, HR MRI con…
Calcium Removal From Cardiac CT Images Using Deep Convolutional Neural Network
Siming Yan, Feng Shi, Yuhua Chen +5
Coronary calcium causes beam hardening and blooming artifacts on cardiac computed tomography angiography (CTA) images, which lead to overestimation of lumen stenosis and reduction…
Brain MRI Super Resolution Using 3D Deep Densely Connected Neural Networks
Yuhua Chen, Yibin Xie, Zhengwei Zhou +3
Magnetic resonance image (MRI) in high spatial resolution provides detailed anatomical information and is often necessary for accurate quantitative analysis. However, high spatial…