224 citations · 331 across the 9 of their papers we have counts for
9 papers
AutoIQ: An Ensemble Framework for Automatic Assessment of Geometric Distortion in Prostate Diffusion-Weighted Imaging
Haoran Sun, Lixia Wang, Yin-Chen Hsu +13
Geometric distortion in prostate diffusion-weighted imaging (DWI) can impair lesion localization and reduce the reliability of MRI-based clinical assessment. We propose AutoIQ, an…
Let Distortion Guide Restoration (DGR): A physics-informed learning framework for Prostate Diffusion MRI
Ziyang Long, Binesh Nader, Lixia Wang +9
We present Distortion-Guided Restoration (DGR), a physics-informed hybrid CNN-diffusion framework for acquisition-free correction of severe susceptibility-induced distortions in pr…
Data-Consistent Non-Cartesian Deep Subspace Learning for Efficient Dynamic MR Image Reconstruction
Zihao Chen, Yuhua Chen, Yibin Xie +2
Non-Cartesian sampling with subspace-constrained image reconstruction is a popular approach to dynamic MRI, but slow iterative reconstruction limits its clinical application. Data-…
Cine Cardiac MRI Motion Artifact Reduction Using a Recurrent Neural Network
Qing Lyu, Hongming Shan, Yibin Xie +2
Cine cardiac magnetic resonance imaging (MRI) is widely used for diagnosis of cardiac diseases thanks to its ability to present cardiovascular features in excellent contrast. As co…
MRI Super-Resolution with GAN and 3D Multi-Level DenseNet: Smaller, Faster, and Better
Yuhua Chen, Anthony G. Christodoulou, Zhengwei Zhou +3
High-resolution (HR) magnetic resonance imaging (MRI) provides detailed anatomical information that is critical for diagnosis in the clinical application. However, HR MRI typically…
Deep learning within a priori temporal feature spaces for large-scale dynamic MR image reconstruction: Application to 5-D cardiac MR Multitasking
Yuhua Chen, Jaime L. Shaw, Yibin Xie +2
High spatiotemporal resolution dynamic magnetic resonance imaging (MRI) is a powerful clinical tool for imaging moving structures as well as to reveal and quantify other physical a…
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…