Resolution enhancement in MRI

Eyal Carmi; Siuyan Liu; Noga Alon; Amos Fiat; Daniel Fiat

doi:10.1016/j.mri.2005.09.011

Resolution enhancement in MRI

Eyal Carmi, Siuyan Liu, Noga Alon, Amos Fiat, Daniel Fiat

Research output: Contribution to journal › Article › peer-review

93 Scopus citations

Abstract

We consider the problem of super-resolution reconstruction (SRR) in MRI. Subpixel-shifted MR images were taken in several fields of view (FOVs) to reconstruct a high-resolution image. A novel algorithm is presented. The algorithm can be applied locally and guarantees perfect reconstruction in the absence of noise. Results that demonstrate resolution improvement are given for phantom studies (mathematical model) as well as for MRI studies of a phantom carried out with a GE clinical scanner. The method raises questions that are discussed in the last section of the paper. Open questions should be answered in order to apply this method for clinical purposes.

Original language	English (US)
Pages (from-to)	133-154
Number of pages	22
Journal	Magnetic Resonance Imaging
Volume	24
Issue number	2
DOIs	https://doi.org/10.1016/j.mri.2005.09.011
State	Published - Feb 2006
Externally published	Yes

All Science Journal Classification (ASJC) codes

Biophysics
Radiology Nuclear Medicine and imaging
Biomedical Engineering

Keywords

Phantom
Resolution enhancement
Super-resolution reconstruction

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10.1016/j.mri.2005.09.011

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title = "Resolution enhancement in MRI",

abstract = "We consider the problem of super-resolution reconstruction (SRR) in MRI. Subpixel-shifted MR images were taken in several fields of view (FOVs) to reconstruct a high-resolution image. A novel algorithm is presented. The algorithm can be applied locally and guarantees perfect reconstruction in the absence of noise. Results that demonstrate resolution improvement are given for phantom studies (mathematical model) as well as for MRI studies of a phantom carried out with a GE clinical scanner. The method raises questions that are discussed in the last section of the paper. Open questions should be answered in order to apply this method for clinical purposes.",

keywords = "Phantom, Resolution enhancement, Super-resolution reconstruction",

author = "Eyal Carmi and Siuyan Liu and Noga Alon and Amos Fiat and Daniel Fiat",

note = "Funding Information: We wish to thank Hezy Yeshurun, Nahum Kiryati, Leonid P. Yaroslavsky and Kostya Malsev for their very useful remarks and discussions on problems of SRR in MRI. Arie Yeredor for his remarks on generalization of the Nyquist sampling theorem for infinite band-limited signals. Kevin King for useful discussions in regard to GE scanner MRI data acquisition and processing and for useful comments in regard to the paper. Anna Altshuler and Janusz Hankiewicz for technical assistance. Zvi Regev for useful discussions in regard to the scanner's electronics. This research was supported in part by the National Institute of Health Grant NS37804 to Daniel Fiat.",

year = "2006",

month = feb,

doi = "10.1016/j.mri.2005.09.011",

language = "English (US)",

volume = "24",

pages = "133--154",

journal = "Magnetic Resonance Imaging",

issn = "0730-725X",

publisher = "Elsevier Inc.",

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T1 - Resolution enhancement in MRI

AU - Carmi, Eyal

AU - Liu, Siuyan

AU - Alon, Noga

AU - Fiat, Amos

AU - Fiat, Daniel

N1 - Funding Information: We wish to thank Hezy Yeshurun, Nahum Kiryati, Leonid P. Yaroslavsky and Kostya Malsev for their very useful remarks and discussions on problems of SRR in MRI. Arie Yeredor for his remarks on generalization of the Nyquist sampling theorem for infinite band-limited signals. Kevin King for useful discussions in regard to GE scanner MRI data acquisition and processing and for useful comments in regard to the paper. Anna Altshuler and Janusz Hankiewicz for technical assistance. Zvi Regev for useful discussions in regard to the scanner's electronics. This research was supported in part by the National Institute of Health Grant NS37804 to Daniel Fiat.

PY - 2006/2

Y1 - 2006/2

N2 - We consider the problem of super-resolution reconstruction (SRR) in MRI. Subpixel-shifted MR images were taken in several fields of view (FOVs) to reconstruct a high-resolution image. A novel algorithm is presented. The algorithm can be applied locally and guarantees perfect reconstruction in the absence of noise. Results that demonstrate resolution improvement are given for phantom studies (mathematical model) as well as for MRI studies of a phantom carried out with a GE clinical scanner. The method raises questions that are discussed in the last section of the paper. Open questions should be answered in order to apply this method for clinical purposes.

AB - We consider the problem of super-resolution reconstruction (SRR) in MRI. Subpixel-shifted MR images were taken in several fields of view (FOVs) to reconstruct a high-resolution image. A novel algorithm is presented. The algorithm can be applied locally and guarantees perfect reconstruction in the absence of noise. Results that demonstrate resolution improvement are given for phantom studies (mathematical model) as well as for MRI studies of a phantom carried out with a GE clinical scanner. The method raises questions that are discussed in the last section of the paper. Open questions should be answered in order to apply this method for clinical purposes.

KW - Phantom

KW - Resolution enhancement

KW - Super-resolution reconstruction

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SP - 133

EP - 154

JO - Magnetic Resonance Imaging

JF - Magnetic Resonance Imaging

IS - 2

ER -

Resolution enhancement in MRI

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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