Accelerating multi-coil MR image reconstruction using weak supervision

Deep-learning-based MR image reconstruction in settings where large fully sampled dataset collection is infeasible requires methods that effectively use both under-sampled and fully sampled datasets. This paper evaluates a weakly supervised, multi-coil, physics-guided approach to MR image reconstruc...

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Vydané v:	Magma (New York, N.Y.) Ročník 38; číslo 1; s. 37 - 51
Hlavní autori:	Atalık, Arda, Chopra, Sumit, Sodickson, Daniel K.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Cham Springer International Publishing 01.02.2025
Predmet:	Basic Science - Reconstruction algorithms and artificial intelligence Biomedical Engineering and Bioengineering Computer Appl. in Life Sciences Deep Learning Health Informatics Humans Image Processing, Computer-Assisted - methods Imaging Magnetic Resonance Imaging Medicine Medicine & Public Health Radiology Research Article Solid State Physics Supervised Machine Learning Accelerated imaging Weak supervision Transfer learning MR image reconstruction Machine learning Self-supervised learning
ISSN:	1352-8661, 1352-8661
On-line prístup:	Získať plný text
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