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

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

NeuroImage (NeuroImage), 2023
18 August 2023
Z. Xiong
Yang Gao
Yin Liu
Amir Fazlollahi
P. Nestor
Feng Liu
Hongfu Sun
    MedIm
ArXiv (abs)PDFHTMLGithub

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

4 / 4 papers shown
Self-supervised physics-informed generative networks for phase retrieval from a single X-ray hologram
Self-supervised physics-informed generative networks for phase retrieval from a single X-ray hologramOptics Express (OE), 2025
Xiaogang Yang
Dawit Hailu
V. Kulvait
Thomas Jentschke
Silja Flenner
...
Stuart I. Campbell
Johannes Hagemann
Christian G. Schroer
Tak Ming Wong
Julian Moosmann
193
0
0
21 Aug 2025
Chemical Shift Encoding based Double Bonds Quantification in
  Triglycerides using Deep Image Prior
Chemical Shift Encoding based Double Bonds Quantification in Triglycerides using Deep Image Prior
Chaoxing Huang
Ziqiang Yu
Zijian Gao
Qiuyi Shen
Queenie Chan
V. Wong
Winnie Chiu Wing Chu
Weitian Chen
MedIm
259
0
0
02 Jul 2024
IR2QSM: Quantitative Susceptibility Mapping via Deep Neural Networks
  with Iterative Reverse Concatenations and Recurrent Modules
IR2QSM: Quantitative Susceptibility Mapping via Deep Neural Networks with Iterative Reverse Concatenations and Recurrent Modules
Min Li
Chen Chen
Z. Xiong
Ying Liu
Pengfei Rong
Shanshan Shan
Feng Liu
Hongfu Sun
Yang Gao
156
0
0
18 Jun 2024
A Learnable Prior Improves Inverse Tumor Growth Modeling
A Learnable Prior Improves Inverse Tumor Growth Modeling
Jonas Weidner
Ivan Ezhov
Michal Balcerak
M. Metz
Sergey Litvinov
...
Jana Lipkova
Jonas Latz
Daniel Rueckert
Bjoern Menze
Benedikt Wiestler
MedImAI4CE
249
11
0
07 Mar 2024
1
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