Quantitative Susceptibility Mapping through Model-based Deep Image Prior (MoDIP)

Type: Preprint

Publication Date: 2023-01-01

Citations: 1

DOI: https://doi.org/10.48550/arxiv.2308.09467

Locations

  • arXiv (Cornell University) - View - PDF
  • DataCite API - View

Similar Works

Action Title Year Authors
+ Quantitative susceptibility mapping through model-based deep image prior (MoDIP) 2024 Zhuang Xiong
Yang Gao
Yin Liu
Amir Fazlollahi
Peter J. Nestor
Feng Liu
Hongfu Sun
+ Nonlinear Dipole Inversion (NDI) enables Quantitative Susceptibility Mapping (QSM) without parameter tuning. 2019 Daniel Polak
Itthi Chatnuntawech
Jaeyeon Yoon
Siddharth Iyer
Jongho Lee
Peter Bachert
Elfar Adalsteinsson
Kawin Setsompop
Berkin Bilgic̦
+ Nonlinear Dipole Inversion (NDI) enables Quantitative Susceptibility Mapping (QSM) without parameter tuning 2019 Daniel Polak
Itthi Chatnuntawech
Jaeyeon Yoon
Siddharth Iyer
Jongho Lee
Peter Bachert
Elfar Adalsteinsson
Kawin Setsompop
Berkin Bilgic̦
+ MRI Tissue Magnetism Quantification through Total Field Inversion with Deep Neural Networks 2019 Juan Liu
Kevin M. Koch
+ Affine Transformation Edited and Refined Deep Neural Network for Quantitative Susceptibility Mapping 2022 Zhuang Xiong
Yang Gao
Feng Liu
Hongfu Sun
+ Affine transformation edited and refined deep neural network for quantitative susceptibility mapping 2022 Zhuang Xiong
Yang Gao
Feng Liu
Hongfu Sun
+ Non-locally Encoder-Decoder Convolutional Network for Whole Brain QSM Inversion 2019 Juan Liu
Kevin M. Koch
+ Learned Proximal Networks for Quantitative Susceptibility Mapping 2020 Kuo-Wei Lai
Manisha Aggarwal
Peter C.M. van Zijl
Xu Li
Jeremias Sulam
+ NeXtQSM -- A complete deep learning pipeline for data-consistent quantitative susceptibility mapping trained with hybrid data 2021 Francesco Cognolato
Kieran O’Brien
Jin Jin
Simon Robinson
Frederik B. Laun
Markus Barth
Steffen Bollmann
+ Model-based Learning for Quantitative Susceptibility Mapping 2020 Juan Liu
Kevin M. Koch
+ Weakly-supervised Learning for Single-step Quantitative Susceptibility Mapping 2020 Juan Liu
Kevin M. Koch
+ MoDL-QSM: Model-based deep learning for quantitative susceptibility mapping 2021 Ruimin Feng
Jiayi Zhao
He Wang
Baofeng Yang
Jie Feng
Yuting Shi
Ming Zhang
Chunlei Liu
Yuyao Zhang
Jie Zhuang
+ PDF Chat IR2QSM: Quantitative Susceptibility Mapping via Deep Neural Networks with Iterative Reverse Concatenations and Recurrent Modules 2024 Min Li
Chen Chen
Zhuang Xiong
Ying Liu
Pengfei Rong
Shanshan Shan
Feng Liu
Hongfu Sun
Yang Gao
+ PDF Chat QSMDiff: Unsupervised 3D Diffusion Models for Quantitative Susceptibility Mapping 2024 Zhuang Xiong
Wei Jiang
Yang Gao
Feng Liu
Hongfu Sun
+ Overview of quantitative susceptibility mapping using deep learning -- Current status, challenges and opportunities 2019 Woojin Jung
Steffen Bollmann
Jongho Lee
+ Overview of quantitative susceptibility mapping using deep learning -- Current status, challenges and opportunities 2019 Woo-Jin Jung
Steffen Bollmann
Jongho Lee
+ PDF Chat Probabilistic dipole inversion for adaptive quantitative susceptibility mapping 2021 Jinwei Zhang
Hang Zhang
Mert R. Sabuncu
Pascal Spincemaille
Thanh D. Nguyen
Yi Wang
+ PDF Chat Overview of quantitative susceptibility mapping using deep learning: Current status, challenges and opportunities 2020 Woojin Jung
Steffen Bollmann
Jongho Lee
+ PDF Chat xQSM: quantitative susceptibility mapping with octave convolutional and noise‐regularized neural networks 2020 Yang Gao
Xuanyu Zhu
Bradford A. Moffat
Rebecca Glarin
Alan H. Wilman
G. Bruce Pike
‪Stuart Crozier‬
Feng Liu
Hongfu Sun
+ MoDL-QSM: Model-based Deep Learning for Quantitative Susceptibility Mapping 2021 Ruimin Feng
Jiayi Zhao
He Wang
Baofeng Yang
Jie Feng
Yuting Shi
Ming Zhang
Chunlei Liu
Yuyao Zhang
Jie Zhuang

Works Cited by This (0)

Action Title Year Authors