Adaptive-size dictionary learning using information theoretic criteria for image reconstruction from undersampled k-space data in low field magnetic resonance imaging

Adaptive-size dictionary learning using information theoretic criteria for image reconstruction from undersampled k-space data in low field magnetic resonance imaging

Abstract Background Magnetic resonance imaging (MRI) is a safe non-invasive and nonionizing medical imaging modality that is used to visualize the structure of human anatomy. Conventional (high-field) MRI scanners are very expensive to purchase, operate and maintain, which limit their use in many de...

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Bibliographic Details
Main Authors: Emmanuel Ahishakiye, Martin Bastiaan Van Gijzen, Julius Tumwiine, Johnes Obungoloch
Format: Article
Language:English
Published: BMC 2020-06-01
Series:BMC Medical Imaging
Subjects:
Compressed sensing
Dictionary learning
Image reconstruction
Information-theoretic criteria
Low-field MRI
Online Access:http://link.springer.com/article/10.1186/s12880-020-00474-3

Internet

http://link.springer.com/article/10.1186/s12880-020-00474-3

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