Image Reconstruction With B₀ Inhomogeneity Using a Deep Unrolled Network on an Open-Bore MRI-Linac.
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IEEE Trans. Instrum. Meas., 2024
Quantitative susceptibility mapping through model-based deep image prior (MoDIP).
NeuroImage, 2024
Plug-and-Play latent feature editing for orientation-adaptive quantitative susceptibility mapping neural networks.
Medical Image Anal., 2024
IR2QSM: Quantitative Susceptibility Mapping via Deep Neural Networks with Iterative Reverse Concatenations and Recurrent Modules.
CoRR, 2024
QSMDiff: Unsupervised 3D Diffusion Models for Quantitative Susceptibility Mapping.
CoRR, 2024
AutoBCS: Block-Based Image Compressive Sensing With Data-Driven Acquisition and Noniterative Reconstruction.
IEEE Trans. Cybern., April, 2023
Affine transformation edited and refined deep neural network for quantitative susceptibility mapping.
NeuroImage, 2023
Deep learning-based quantitative susceptibility mapping: methods development and applications
PhD thesis, 2022
Instant tissue field and magnetic susceptibility mapping from MRI raw phase using Laplacian enhanced deep neural networks.
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NeuroImage, 2022
Non-Cartesian Spiral Binary Sensing Matrices.
Circuits Syst. Signal Process., 2022
BFRnet: A deep learning-based MR background field removal method for QSM of the brain containing significant pathological susceptibility sources.
CoRR, 2022
Design of Submillimeter Magnetic Stimulation Instrumentation and Its Targeted Inhibitory Effect on Rat Model of Epilepsy.
IEEE Trans. Instrum. Meas., 2021
Accelerating quantitative susceptibility and R2* mapping using incoherent undersampling and deep neural network reconstruction.
NeuroImage, 2021
Chaotic Compressive Sampling Matrix: Where Sensing Architecture Meets Sinusoidal Iterator.
Circuits Syst. Signal Process., 2020
Extreme Low Frequency Electromagnetic Field Stimulation Induces Metaplastic-Like Effects on LTP/ LTD.
IEEE Access, 2019