title: Is synthesizing MRI contrast useful for inter-modality analysis?
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.
authors: Martinos Center for Biomedical Imaging, MGH, Harvard Medical School, USA.
authors: Juan Eugenio
authors: JE
authors: Iglesias
authors: Martinos Center for Biomedical Imaging, MGH, Harvard Medical School, USA.
authors: Ender
authors: E
authors: Konukoglu
authors: Microsoft Research, Cambridge, UK.
authors: Darko
authors: D
authors: Zikic
authors: Microsoft Research, Cambridge, UK.
authors: Ben
authors: B
authors: Glocker
authors: Martinos Center for Biomedical Imaging, MGH, Harvard Medical School, USA.
authors: Koen
authors: K
authors: Van Leemput
authors: Martinos Center for Biomedical Imaging, MGH, Harvard Medical School, USA.
authors: Bruce
authors: B
authors: Fischl
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D003287:Contrast Media; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D064847:Multimodal Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique
chemical_list: D003287:Contrast Media