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Proceedings Paper

Characterization of high resolution MR images reconstructed by a GRAPPA based parallel technique
Author(s): Suchandrima Banerjee; Sharmila Majumdar
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Paper Abstract

This work implemented an auto-calibrating parallel imaging technique and applied it to in vivo magnetic resonance imaging (MRI) of trabecular bone micro-architecture. A Generalized auto-calibrating partially parallel acquisition (GRAPPA) based reconstruction technique using modified robust data fitting was developed. The MR data was acquired with an eight channel phased array receiver on three normal volunteers on a General Electric 3 Tesla scanner. Microstructures comprising the trabecular bone architecture are of the order of 100 microns and hence their depiction requires very high imaging resolution. This work examined the effects of GRAPPA based parallel imaging on signal and noise characteristics and effective spatial resolution in high resolution (HR) images, for the range of undersampling or reduction factors 2-4. Additionally quantitative analysis was performed to obtain structural measures of trabecular bone from the images. Image quality in terms of contrast and depiction of structures was maintained in parallel images for reduction factors up to 3. Comparison between regular and parallel images suggested similar spatial resolution for both. However differences in noise characteristics in parallel images compared to regular images affected the threshholding based quantification. This suggested that GRAPPA based parallel images might require different analysis techniques. In conclusion, the study showed the feasibility of using parallel imaging techniques in HR-MRI of trabecular bone, although quantification strategies will have to be further investigated. Reduction of acquisition time using parallel techniques can improve the clinical feasibility of MRI of trabecular bone for prognosis and staging of the skeletal disorder osteoporosis.

Paper Details

Date Published: 20 March 2006
PDF: 10 pages
Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61446A (20 March 2006); doi: 10.1117/12.652460
Show Author Affiliations
Suchandrima Banerjee, Univ. of California, Berkeley (United States)
Univ. of California, San Francisco (United States)
Sharmila Majumdar, Univ. of California, Berkeley (United States)
Univ. of California, San Francisco (United States)

Published in SPIE Proceedings Vol. 6144:
Medical Imaging 2006: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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