50 citations · 91 across the 10 of their papers we have counts for
10 papers
Plug-and-Play Latent Feature Editing for Orientation-Adaptive Quantitative Susceptibility Mapping Neural Networks
Yang Gao, Zhuang Xiong, Shanshan Shan +7
Quantitative susceptibility mapping (QSM) is a post-processing technique for deriving tissue magnetic susceptibility distribution from MRI phase measurements. Deep learning (DL) al…
Quantitative Susceptibility Mapping through Model-based Deep Image Prior (MoDIP)
Zhuang Xiong, Yang Gao, Yin Liu +4
The data-driven approach of supervised learning methods has limited applicability in solving dipole inversion in Quantitative Susceptibility Mapping (QSM) with varying scan paramet…
MM-SFENet: Multi-scale Multi-task Localization and Classification of Bladder Cancer in MRI with Spatial Feature Encoder Network
Yu Ren, Guoli Wang, Pingping Wang +5
Background and Objective: Bladder cancer is a common malignant urinary carcinoma, with muscle-invasive and non-muscle-invasive as its two major subtypes. This paper aims to achieve…
Affine Transformation Edited and Refined Deep Neural Network for Quantitative Susceptibility Mapping
Zhuang Xiong, Yang Gao, Feng Liu +1
Deep neural networks have demonstrated great potential in solving dipole inversion for Quantitative Susceptibility Mapping (QSM). However, the performances of most existing deep le…
Distortion-Corrected Image Reconstruction with Deep Learning on an MRI-Linac
Shanshan Shan, Yang Gao, Paul Z. Y. Liu +5
Magnetic resonance imaging (MRI) is increasingly utilized for image-guided radiotherapy due to its outstanding soft-tissue contrast and lack of ionizing radiation. However, geometr…
BFRnet: A deep learning-based MR background field removal method for QSM of the brain containing significant pathological susceptibility sources
Xuanyu Zhu, Yang Gao, Feng Liu +2
Introduction: Background field removal (BFR) is a critical step required for successful quantitative susceptibility mapping (QSM). However, eliminating the background field in brai…
Instant tissue field and magnetic susceptibility mapping from MR raw phase using Laplacian enabled deep neural networks
Yang Gao, Zhuang Xiong, Amir Fazlollahi +8
Quantitative susceptibility mapping (QSM) is a valuable MRI post-processing technique that quantifies the magnetic susceptibility of body tissue from phase data. However, the tradi…
Deep grey matter quantitative susceptibility mapping from small spatial coverages using deep learning
Xuanyu Zhu, Yang Gao, Feng Liu +2
Introduction: Quantitative Susceptibility Mapping (QSM) is generally acquired with full brain coverage, even though many QSM brain-iron studies focus on the deep grey matter (DGM)…
Accelerating Quantitative Susceptibility Mapping using Compressed Sensing and Deep Neural Network
Yang Gao, Martijn Cloos, Feng Liu +3
Quantitative susceptibility mapping (QSM) is an MRI phase-based post-processing method that quantifies tissue magnetic susceptibility distributions. However, QSM acquisitions are r…
xQSM: Quantitative Susceptibility Mapping with Octave Convolutional and Noise Regularized Neural Networks
Yang Gao, Xuanyu Zhu, Bradford A. Moffat +6
Quantitative susceptibility mapping (QSM) is a valuable magnetic resonance imaging (MRI) contrast mechanism that has demonstrated broad clinical applications. However, the image re…