MICCAI 2013 - LNCS 8149-8151

Is Synthesizing MRI Contrast Useful for Inter-modality Analysis?

Juan Eugenio Iglesias¹, Ender Konukoglu¹, Darko Zikic², Ben Glocker², Koen Van Leemput^{1, 3, 4}, and Bruce Fischl¹

¹Martinos Center for Biomedical Imaging, MGH, Harvard Medical School, USA

²Microsoft Research, Cambridge, UK

³Department of Applied Mathematics and Computer Science, DTU, Denmark

⁴Departments of Information and Computer Science and of Biomedical, Engineering and Computational Science, Aalto University, Finland

Abstract. Availability of multi-modal magnetic resonance imaging (MRI) databases opens up the opportunity to synthesize different MRI contrasts without actually acquiring the images. In theory such synthetic images have the potential to reduce the amount of acquisitions to perform certain analyses. However, to what extent they can substitute real acquisitions in the respective analyses is an open question. In this study, we used a synthesis method based on patch matching to test whether synthetic images can be useful in segmentation and inter-modality cross-subject registration of brain MRI. Thirty-nine T1 scans with 36 manually labeled structures of interest were used in the registration and segmentation of eight proton density (PD) scans, for which ground truth T1 data were also available. The results show that synthesized T1 contrast can considerably enhance the quality of non-linear registration compared with using the original PD data, and it is only marginally worse than using the original T1 scans. In segmentation, the relative improvement with respect to using the PD is smaller, but still statistically significant.

LNCS 8149, p. 631 ff.

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