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

CLAS-NS: Mathematics and Statistical Sciences, School of (SMSS)

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

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

Other

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

ASJC Scopus subject areas

Biomedical Engineering
Radiology Nuclear Medicine and imaging

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10.1109/ISBI.2002.1029303

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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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language = "English (US)",

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volume = "2002-January",

pages = "497--500",

booktitle = "Proceedings - International Symposium on Biomedical Imaging",

publisher = "IEEE Computer Society",

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T1 - Reducing the effects of noise in MRI reconstruction

AU - Archibald, Rick

AU - Gelb, Anne

PY - 2002

Y1 - 2002

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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U2 - 10.1109/ISBI.2002.1029303

DO - 10.1109/ISBI.2002.1029303

M3 - Conference contribution

AN - SCOPUS:84948695120

SN - 078037584X

VL - 2002-January

SP - 497

EP - 500

BT - Proceedings - International Symposium on Biomedical Imaging

PB - IEEE Computer Society

T2 - IEEE International Symposium on Biomedical Imaging, ISBI 2002

Y2 - 7 July 2002 through 10 July 2002

ER -

Reducing the effects of noise in MRI reconstruction

Abstract

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