New starting point registration method for tagged MRI tongue motion estimation

Analysis of tongue motion has been proven useful in gaining a better understanding of speech and swallowing disorders. Tagged magnetic resonance imaging (MRI) has been used to image tongue motion, and the harmonic phase processing (HARP) method has been used to compute 3D motion from these images. However, HARP can fail with large motions due to so-called tag (or phase) jumping, yielding highly inaccurate results. The phase vector incompressible registration algorithm (PVIRA) was developed using the HARP framework to yield smooth, incompressible, and diffeomorphic motion fields, but it can also suffer from tag jumping. In this paper, we propose a new method to avoid tag jumping occurring in the later frames of tagged MR image sequences. The new approach uses PVIRA between successive time frames and then adds their stationary velocity fields to yield a starting point from which to initialize a final PVIRA stage between troublesome frames. We demonstrate on multiple data sets that this method avoids tag jumping and produces superior motion estimates compared with existing methods.