Deep learning initialized compressed sensing (Deli-CS) in volumetric spatio-temporal subspace reconstruction

Object Spatio-temporal MRI methods offer rapid whole-brain multi-parametric mapping, yet they are often hindered by prolonged reconstruction times or prohibitively burdensome hardware requirements. The aim of this project is to reduce reconstruction time using deep learning. Materials and methods Th...

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Veröffentlicht in:	Magma (New York, N.Y.) Jg. 38; H. 2; S. 221 - 237
Hauptverfasser:	Schauman, S. Sophie, Iyer, Siddharth S., Sandino, Christopher M., Yurt, Mahmut, Cao, Xiaozhi, Liao, Congyu, Ruengchaijatuporn, Natthanan, Chatnuntawech, Itthi, Tong, Elizabeth, Setsompop, Kawin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Cham Springer International Publishing 01.04.2025
Schlagworte:	Algorithms Basic Science - Reconstruction algorithms and artificial intelligence Biomedical Engineering and Bioengineering Brain - diagnostic imaging Brain Mapping - methods Computer Appl. in Life Sciences Data Compression - methods Deep Learning Health Informatics Humans Image Processing, Computer-Assisted - methods Imaging Imaging, Three-Dimensional Magnetic Resonance Imaging - methods Medicine Medicine & Public Health Phantoms, Imaging Radiology Research Article Solid State Physics Spatio-Temporal Analysis Deep learning Brain Algorithms Magnetic resonance imaging Image processing (computer-assisted)
ISSN:	1352-8661, 0968-5243, 1352-8661
Online-Zugang:	Volltext
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