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
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
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