Spinet-QSM: model-based deep learning with schatten p-norm regularization for improved quantitative susceptibility mapping-Reference-Cited by-同舟云学术

Spinet-QSM: model-based deep learning with schatten p-norm regularization for improved quantitative susceptibility mapping

Published:2024-04-10 Issue:3 Volume:37 Page:411-427
ISSN:1352-8661
Container-title:Magnetic Resonance Materials in Physics, Biology and Medicine
language:en
Short-container-title:Magn Reson Mater Phy

Author:

Venkatesh Vaddadi,Mathew Raji Susan,Yalavarthy Phaneendra K.^ORCID

Funder

Department of Biotechnology, Ministry of Science and Technology, India

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10334-024-01158-7.pdf

Reference33 articles.

1. Deistung A, Schweser F, Reichenbach JR (2017) Overview of quantitative susceptibility mapping. NMR Biomed 30(4):e3569

2. Schweser F, Deistung A, Reichenbach JR (2016) Foundations of MRI phase imaging and processing for Quantitative Susceptibility Mapping (QSM). Z Med Phys 26(1):6–34

3. Liu C, Wei H, Gong NJ, Cronin M, Dibb R, Decker K (2015) Quantitative susceptibility mapping: contrast mechanisms and clinical applications. Tomography. 1(1):3–17

4. Reichenbach J, Schweser F, Serres B, Deistung A (2015) Quantitative susceptibility mapping: concepts and applications. Clin Neuroradiol 25(2):225–230

5. Schweser F, Lehr BW, Andreas D, Rainer RJ (2010) Sophisticated harmonic artifact reduction for phase data (SHARP). Proceeding Proc GC Intl Soc Mag Reson Med

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