Abstract
Purpose: To minimize feature loss in T1- and T 2-weighted MRI by merging multiple MR images acquired at different TR and TE to generate an image with increased dynamic range. Materials and Methods: High Dynamic Range (HDR) processing techniques from the field of photography were applied to a series of acquired MR images. Specifically, a method to parameterize the algorithm for MRI data was developed and tested. T1- and T2-weighted images of a number of contrast agent phantoms and a live mouse were acquired with varying T R and TE parameters. The images were computationally merged to produce HDR-MR images. All acquisitions were performed on a 7.05 T Bruker PharmaScan with a multi-echo spin echo pulse sequence. Results: HDR-MRI delineated bright and dark features that were either saturated or indistinguishable from background in standard T1- and T2-weighted MRI. The increased dynamic range preserved intensity gradation over a larger range of T1 and T2 in phantoms and revealed more anatomical features in vivo. Conclusions: We have developed and tested a method to apply HDR processing to MR images. The increased dynamic range of HDR-MR images as compared to standard T1- and T2-weighted images minimizes feature loss caused by magnetization recovery or low SNR. © 2013 Hung et al.
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CITATION STYLE
Hung, A. H., Liang, T., Sukerkar, P. A., & Meade, T. J. (2013). High dynamic range processing for magnetic resonance imaging. PLoS ONE, 8(11). https://doi.org/10.1371/journal.pone.0077883
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