High Dynamic Range Processing for Magnetic Resonance Imaging

Andy H Hung, Taiyang Liang, Preeti A Sukerkar and Thomas J Meade

PLOS ONE, 2013, vol. 8, issue 11, 1-11

Abstract: Purpose: To minimize feature loss in T1- and T2-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 TR 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.

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0077883

DOI: 10.1371/journal.pone.0077883

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