Purpose: In order to more precisely differentiate cerebral structures in neuroimaging studies, a novel technique for enhancing the tissue contrast based on a combination of T1-weighted (T1w) and T2-weighted (T2w) MRI images was developed.
Methods: The combined image (CI) was calculated as CI = (T1w - sT2w)/(T1w + sT2w), where sT2w is the scaled T2-weighted image. The scaling factor was calculated to adjust the gray- matter (GM) voxel intensities in the T2w image so that their median value equaled that of the GM voxel intensities in the T1w image. The image intensity homogeneity within a tissue and the discriminability between tissues in the CI versus the separate T1w and T2w images were evaluated using the segmentation by the FMRIB Software Library (FSL) and FreeSurfer (Athinoula A. Martinos Center for Biomedical Imaging at Massachusetts General Hospital, Boston, MA) software.
Results: The combined image significantly improved homogeneity in the white matter (WM) and GM compared to the T1w images alone. The discriminability between WM and GM also improved significantly by applying the CI approach. Significant enhancements to the homogeneity and discriminability also were achieved in most subcortical nuclei tested, with the exception of the amygdala and the thalamus.
Conclusion: The tissue discriminability enhancement offered by the CI potentially enables more accurate neuromorphometric analyses of brain structures.
Keywords: MRI contrast enhancement; T1- T2-weighted image fusion; subcortical segmentation; tissue segmentation.
© 2014 Wiley Periodicals, Inc.