1 citations · 3 across the 14 of their papers we have counts for
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Wireless, Customizable Coaxially-shielded Coils for Magnetic Resonance Imaging
Ke Wu, Xia Zhu, Stephan W. Anderson +1
Anatomy-specific RF receive coil arrays routinely adopted in magnetic resonance imaging (MRI) for signal acquisition, are commonly burdened by their bulky, fixed, and rigid configu…
Wearable Coaxially-shielded Metamaterial for Magnetic Resonance Imaging
Xia Zhu, Ke Wu, Stephan W. Anderson +1
Recent advancements in metamaterials have yielded the possibility of a wireless solution to improve signal-to-noise ratio (SNR) in magnetic resonance imaging (MRI). Unlike traditio…
Computational-design Enabled Wearable and Tunable Metamaterials via Freeform Auxetics for Magnetic Resonance Imaging
Ke Wu, Xia Zhu, Thomas G. Bifano +2
Metamaterials hold significant promise for enhancing the imaging capabilities of MRI machines as an additive technology, due to their unique ability to enhance local magnetic field…
Learning to Reconstruct Accelerated MRI Through K-space Cold Diffusion without Noise
Guoyao Shen, Mengyu Li, Chad W. Farris +2
Deep learning-based MRI reconstruction models have achieved superior performance these days. Most recently, diffusion models have shown remarkable performance in image generation,…
Conformal Metamaterials with Active Tunability and Self-adaptivity for Magnetic Resonance Imaging
Ke Wu, Xia Zhu, Xiaoguang Zhao +2
Ongoing effort has been devoted to applying metamaterials to boost the imaging performance of magnetic resonance imaging owing to their unique capacity for electromagnetic field co…
Regularization by Neural Style Transfer for MRI Field-Transfer Reconstruction with Limited Data
Guoyao Shen, Yancheng Zhu, Mengyu Li +6
Recent advances in MRI reconstruction have demonstrated remarkable success through deep learning-based models. However, most existing methods rely heavily on large-scale, task-spec…
Attention Hybrid Variational Net for Accelerated MRI Reconstruction
Guoyao Shen, Boran Hao, Mengyu Li +4
The application of compressed sensing (CS)-enabled data reconstruction for accelerating magnetic resonance imaging (MRI) remains a challenging problem. This is due to the fact that…
Bayesian Reconstruction of Magnetic Resonance Images using Gaussian Processes
Yihong Xu, Chad W. Farris, Stephan W. Anderson +2
A central goal of modern magnetic resonance imaging (MRI) is to reduce the time required to produce high-quality images. Efforts have included hardware and software innovations suc…