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Sparse coding for improved signal-to-noise ratio in MRI

Razzaq,FA, Mohamed,S, Bhatti,A and Nahavandi,S 2014, Sparse coding for improved signal-to-noise ratio in MRI. In Loo,CK, Yap,KS, Wong,KW, Teoh,A and Huang,K (ed), Neural information processing : 21st International Conference ICONIP 2014 Kuching, Malaysia, November 3-6, 2014 Proceedings, Part III, Springer Verlag, Germany, pp.258-265.

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Title Sparse coding for improved signal-to-noise ratio in MRI
Author(s) Razzaq,FA
Mohamed,SORCID iD for Mohamed,S orcid.org/0000-0002-8851-1635
Bhatti,AORCID iD for Bhatti,A orcid.org/0000-0001-6876-1437
Nahavandi,S
Title of book Neural information processing : 21st International Conference ICONIP 2014 Kuching, Malaysia, November 3-6, 2014 Proceedings, Part III
Editor(s) Loo,CK
Yap,KS
Wong,KW
Teoh,A
Huang,K
Publication date 2014
Series Lecture Notes in Computer Science; v.8836
Chapter number 32
Total chapters 83
Start page 258
End page 265
Total pages 8
Publisher Springer Verlag
Place of Publication Germany
Keyword(s) Additive White Gaussian Noise (AWGN)
Magnetic Resonance imaging(MRI)
Signalto Noise Ratio (SNR)
Sparse Coding
Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science, Information Systems
Computer Science, Theory & Methods
Computer Science
Signal-to Noise Ratio (SNR)
IMAGES
CONTRAST
Summary Magnetic Resonance images (MRI) do not only exhibit sparsity but their sparsity take a certain predictable shape which is common for all kinds of images. That region based localised sparsity can be used to de-noise MR images from random thermal noise. This paper present a simple framework to exploit sparsity of MR images for image de-noising. As, noise in MR images tends to change its shape based on contrast level and signal itself, the proposed method is independent of noise shape and type and it can be used in combination with other methods.
Notes 21st International Conference, ICONIP 2014, Kuching, Malaysia, November 3-6, 2014. Proceedings
ISBN 9783319126425
ISSN 0302-9743
1611-3349
Language eng
Field of Research 080106 Image Processing
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category B1 Book chapter
ERA Research output type B Book chapter
Copyright notice ©2014, Springer Verlag
Persistent URL http://hdl.handle.net/10536/DRO/DU:30071099

Document type: Book Chapter
Collection: Centre for Intelligent Systems Research
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