On compressed sensing in parallel MRI of cardiac perfusion using temporal wavelet and TV regularization

C. Bilen, Ivan Selesnick, Yao Wang, R. Otazo, D. Kim, L. Axel, D. K. Sodickson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Imaging of cardiac perfusion with MR is a challenging area of research especially due to the motion of the heart and limited time of data acquisition. Compressed sensing is a popular signal estimation method recently adopted by researchers in MRI which can improve the spatial and/or temporal resolution of the acquired images by reducing the number of necessary samples for image reconstruction. This paper focuses on performance of temporal regularization with total variation and wavelets in compressed sensing. The impact of the choice of regularization parameters on the image quality and the temporal variation of intensity in region of interests (ROIs) are discussed. It is found that selecting the regularization parameter so as to optimize the quality of the reconstructed image sequence as a whole, leads to erroneous reconstruction of certain regions due to over regularization.

Original languageEnglish (US)
Title of host publication2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings
Pages630-633
Number of pages4
DOIs
StatePublished - 2010
Event2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Dallas, TX, United States
Duration: Mar 14 2010Mar 19 2010

Other

Other2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010
CountryUnited States
CityDallas, TX
Period3/14/103/19/10

Fingerprint

Compressed sensing
Magnetic resonance imaging
Image reconstruction
Image quality
Data acquisition
Imaging techniques

Keywords

  • Cardiac perfusion
  • Compressed sensing
  • Parallel MRI

ASJC Scopus subject areas

  • Signal Processing
  • Software
  • Electrical and Electronic Engineering

Cite this

Bilen, C., Selesnick, I., Wang, Y., Otazo, R., Kim, D., Axel, L., & Sodickson, D. K. (2010). On compressed sensing in parallel MRI of cardiac perfusion using temporal wavelet and TV regularization. In 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings (pp. 630-633). [5495163] https://doi.org/10.1109/ICASSP.2010.5495163

On compressed sensing in parallel MRI of cardiac perfusion using temporal wavelet and TV regularization. / Bilen, C.; Selesnick, Ivan; Wang, Yao; Otazo, R.; Kim, D.; Axel, L.; Sodickson, D. K.

2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings. 2010. p. 630-633 5495163.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Bilen, C, Selesnick, I, Wang, Y, Otazo, R, Kim, D, Axel, L & Sodickson, DK 2010, On compressed sensing in parallel MRI of cardiac perfusion using temporal wavelet and TV regularization. in 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings., 5495163, pp. 630-633, 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010, Dallas, TX, United States, 3/14/10. https://doi.org/10.1109/ICASSP.2010.5495163
Bilen C, Selesnick I, Wang Y, Otazo R, Kim D, Axel L et al. On compressed sensing in parallel MRI of cardiac perfusion using temporal wavelet and TV regularization. In 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings. 2010. p. 630-633. 5495163 https://doi.org/10.1109/ICASSP.2010.5495163
Bilen, C. ; Selesnick, Ivan ; Wang, Yao ; Otazo, R. ; Kim, D. ; Axel, L. ; Sodickson, D. K. / On compressed sensing in parallel MRI of cardiac perfusion using temporal wavelet and TV regularization. 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings. 2010. pp. 630-633
@inproceedings{61393f9415e042bc914fd2de2a64fe7d,
title = "On compressed sensing in parallel MRI of cardiac perfusion using temporal wavelet and TV regularization",
abstract = "Imaging of cardiac perfusion with MR is a challenging area of research especially due to the motion of the heart and limited time of data acquisition. Compressed sensing is a popular signal estimation method recently adopted by researchers in MRI which can improve the spatial and/or temporal resolution of the acquired images by reducing the number of necessary samples for image reconstruction. This paper focuses on performance of temporal regularization with total variation and wavelets in compressed sensing. The impact of the choice of regularization parameters on the image quality and the temporal variation of intensity in region of interests (ROIs) are discussed. It is found that selecting the regularization parameter so as to optimize the quality of the reconstructed image sequence as a whole, leads to erroneous reconstruction of certain regions due to over regularization.",
keywords = "Cardiac perfusion, Compressed sensing, Parallel MRI",
author = "C. Bilen and Ivan Selesnick and Yao Wang and R. Otazo and D. Kim and L. Axel and Sodickson, {D. K.}",
year = "2010",
doi = "10.1109/ICASSP.2010.5495163",
language = "English (US)",
isbn = "9781424442966",
pages = "630--633",
booktitle = "2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings",

}

TY - GEN

T1 - On compressed sensing in parallel MRI of cardiac perfusion using temporal wavelet and TV regularization

AU - Bilen, C.

AU - Selesnick, Ivan

AU - Wang, Yao

AU - Otazo, R.

AU - Kim, D.

AU - Axel, L.

AU - Sodickson, D. K.

PY - 2010

Y1 - 2010

N2 - Imaging of cardiac perfusion with MR is a challenging area of research especially due to the motion of the heart and limited time of data acquisition. Compressed sensing is a popular signal estimation method recently adopted by researchers in MRI which can improve the spatial and/or temporal resolution of the acquired images by reducing the number of necessary samples for image reconstruction. This paper focuses on performance of temporal regularization with total variation and wavelets in compressed sensing. The impact of the choice of regularization parameters on the image quality and the temporal variation of intensity in region of interests (ROIs) are discussed. It is found that selecting the regularization parameter so as to optimize the quality of the reconstructed image sequence as a whole, leads to erroneous reconstruction of certain regions due to over regularization.

AB - Imaging of cardiac perfusion with MR is a challenging area of research especially due to the motion of the heart and limited time of data acquisition. Compressed sensing is a popular signal estimation method recently adopted by researchers in MRI which can improve the spatial and/or temporal resolution of the acquired images by reducing the number of necessary samples for image reconstruction. This paper focuses on performance of temporal regularization with total variation and wavelets in compressed sensing. The impact of the choice of regularization parameters on the image quality and the temporal variation of intensity in region of interests (ROIs) are discussed. It is found that selecting the regularization parameter so as to optimize the quality of the reconstructed image sequence as a whole, leads to erroneous reconstruction of certain regions due to over regularization.

KW - Cardiac perfusion

KW - Compressed sensing

KW - Parallel MRI

UR - http://www.scopus.com/inward/record.url?scp=78049381012&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78049381012&partnerID=8YFLogxK

U2 - 10.1109/ICASSP.2010.5495163

DO - 10.1109/ICASSP.2010.5495163

M3 - Conference contribution

SN - 9781424442966

SP - 630

EP - 633

BT - 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings

ER -