Identification of Subject-Specific Motion Variations via Atlas-Based Deformation Refinement from Real-Time MRI

Dynamic magnetic resonance imaging has become increasingly efficient at capturing speech deformations of the velopharyngeal region in real time. With previously developed dynamic vocal tract atlases, quantification of group deformation statistics of a population in speech has become possible in a common atlas space. However, subject-specific deformation characteristics as an underlying property tend to be hidden in the spatial and temporal alignment process of atlas construction. We present a registration-based deformation characterization method that extracts subject-specific motion variations in two layers of registration steps. A dataset of fifteen human subjects is processed to reveal unique deformation patterns of each subject.