Reducing the effects of noise in MRI reconstruction

Rick Archibald; Anne Gelb

doi:10.1109/ISBI.2002.1029303

Reducing the effects of noise in MRI reconstruction

Rick Archibald, Anne Gelb

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Fourier methods are a natural choice for reconstructing magnetic resonance images (MRI). Unfortunately, however, due to the many different tissues normally present in each scan, the Gibbs ringing artifact often hinders accurate reconstruction. These effects are exacerbated in the presence of random noise, which is inherent in MRI spectral data. Recently, numerical edge detection and reconstruction methods have been developed that effectively reduce the Gibbs oscillations while maintaining high resolution accuracy at the edges. This paper addresses the issue of noise in MRI reconstruction and its effects on the ability to recover the image. The numerical method we apply here not only recovers the images with very high accuracy, but it is also robust in the presence of noise.

Original language	English
Title of host publication	2002 IEEE International Symposium on Biomedical Imaging, ISBI 2002 - Proceedings
Publisher	IEEE Computer Society
Pages	497-500
Number of pages	4
ISBN (Electronic)	078037584X
DOIs	https://doi.org/10.1109/ISBI.2002.1029303
State	Published - 2002
Externally published	Yes
Event	IEEE International Symposium on Biomedical Imaging, ISBI 2002 - Washington, United States Duration: Jul 7 2002 → Jul 10 2002

Publication series

Name	Proceedings - International Symposium on Biomedical Imaging
Volume	2002-January
ISSN (Print)	1945-7928
ISSN (Electronic)	1945-8452

Conference

Conference	IEEE International Symposium on Biomedical Imaging, ISBI 2002
Country/Territory	United States
City	Washington
Period	07/7/02 → 07/10/02

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10.1109/ISBI.2002.1029303

Cite this

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title = "Reducing the effects of noise in MRI reconstruction",

abstract = "Fourier methods are a natural choice for reconstructing magnetic resonance images (MRI). Unfortunately, however, due to the many different tissues normally present in each scan, the Gibbs ringing artifact often hinders accurate reconstruction. These effects are exacerbated in the presence of random noise, which is inherent in MRI spectral data. Recently, numerical edge detection and reconstruction methods have been developed that effectively reduce the Gibbs oscillations while maintaining high resolution accuracy at the edges. This paper addresses the issue of noise in MRI reconstruction and its effects on the ability to recover the image. The numerical method we apply here not only recovers the images with very high accuracy, but it is also robust in the presence of noise.",

author = "Rick Archibald and Anne Gelb",

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year = "2002",

doi = "10.1109/ISBI.2002.1029303",

language = "English",

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Archibald, R & Gelb, A 2002, Reducing the effects of noise in MRI reconstruction. in 2002 IEEE International Symposium on Biomedical Imaging, ISBI 2002 - Proceedings., 1029303, Proceedings - International Symposium on Biomedical Imaging, vol. 2002-January, IEEE Computer Society, pp. 497-500, IEEE International Symposium on Biomedical Imaging, ISBI 2002, Washington, United States, 07/7/02. https://doi.org/10.1109/ISBI.2002.1029303

Reducing the effects of noise in MRI reconstruction. / Archibald, Rick; Gelb, Anne.
2002 IEEE International Symposium on Biomedical Imaging, ISBI 2002 - Proceedings. IEEE Computer Society, 2002. p. 497-500 1029303 (Proceedings - International Symposium on Biomedical Imaging; Vol. 2002-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - Fourier methods are a natural choice for reconstructing magnetic resonance images (MRI). Unfortunately, however, due to the many different tissues normally present in each scan, the Gibbs ringing artifact often hinders accurate reconstruction. These effects are exacerbated in the presence of random noise, which is inherent in MRI spectral data. Recently, numerical edge detection and reconstruction methods have been developed that effectively reduce the Gibbs oscillations while maintaining high resolution accuracy at the edges. This paper addresses the issue of noise in MRI reconstruction and its effects on the ability to recover the image. The numerical method we apply here not only recovers the images with very high accuracy, but it is also robust in the presence of noise.

AB - Fourier methods are a natural choice for reconstructing magnetic resonance images (MRI). Unfortunately, however, due to the many different tissues normally present in each scan, the Gibbs ringing artifact often hinders accurate reconstruction. These effects are exacerbated in the presence of random noise, which is inherent in MRI spectral data. Recently, numerical edge detection and reconstruction methods have been developed that effectively reduce the Gibbs oscillations while maintaining high resolution accuracy at the edges. This paper addresses the issue of noise in MRI reconstruction and its effects on the ability to recover the image. The numerical method we apply here not only recovers the images with very high accuracy, but it is also robust in the presence of noise.

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ER -

Reducing the effects of noise in MRI reconstruction

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