DocumentCode :
2518993
Title :
MULTICHANNEL ESTIMATION OF COIL SENSITIVITIES IN PARALLEL MRI
Author :
Morrison, Robert L. ; Jacob, Mathews ; Do, Minh N.
Author_Institution :
Dept. of Electr. & Comput. Eng., Illinois Univ., Urbana, IL
fYear :
2007
fDate :
12-15 April 2007
Firstpage :
117
Lastpage :
120
Abstract :
We consider the problem of estimating receiver coil sensitivity functions in parallel MRI. By exploiting the multichannel nature of the problem, where multiple acquisitions of the same image function are obtained with different sensitivity weightings, we obtain a subspace-based framework for directly solving for the sensitivity functions. The proposed approach does not rely on the sum-of-squares assumption used in existing estimation schemes; this assumption tends to be violated towards the center of the image, thus leading to errors in the sensitivity estimates. Our approach eliminates this problem, producing superior sensitivity estimates in comparison to the sum-of-squares technique. In addition, the proposed restoration procedure is non-iterative, computationally efficient, and applicable both to cases where pilot scans are available or where auto-calibration data are collected with each scan. We present experimental results using actual and simulated data to assess the performance of our approach in comparison with existing methods
Keywords :
biomedical MRI; channel estimation; image restoration; medical image processing; image restoration; multichannel estimation; parallel MRI; receiver coil sensitivity; sum-of-squares technique; Brain; Coils; Computational modeling; Deconvolution; Filtering; Finite impulse response filter; Image restoration; Jacobian matrices; Magnetic resonance imaging; Polynomials;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2007. ISBI 2007. 4th IEEE International Symposium on
Conference_Location :
Arlington, VA
Print_ISBN :
1-4244-0672-2
Electronic_ISBN :
1-4244-0672-2
Type :
conf
DOI :
10.1109/ISBI.2007.356802
Filename :
4193236
Link To Document :
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