Optical flow based volumetric spatio-temporal interpolation

Acquisition of three-dimensional medical images with excellent spatial resolution is achieved almost always at the cost-dictating expense of increased acquisition time. This can be mitigated using shape-respecting inter-slice interpolation of sparsely acquired datasets. Existing shape and registration based interpolation techniques are suboptimal. This paper proposes a new optical flow based approach to interpolate between sparse data. The Horn and Schunck technique is used to estimate the pixel-wise flow vectors across the slices; intermediate data planes can be reconstructed from these flow vectors. The proposed technique is accurate and computationally fast. Coupled with anatomy aware sparse acquisitions, the proposed technique shows promise of judiciously managing the patient-specific acquisition.