High dynamic range processing for magnetic resonance imaging.

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.