Shift-Compensated Volumetric Interpolation of Tomographic Sequences for Accurate 3D Reconstruction

In patients affected by craniosynostosis, i.e. a congenital cranial defect, diagnostic evaluation for a prompt surgical treatment is performed using low-dose three-dimensional computer tomography (CT), characterized by a poor spatial resolution (in terms of slice thickness). The limited number of CT images reduces the accuracy of the 3D reconstruction of the skull and leads to a coarser segmentation and modelling. In this paper, Motion Compensated Frame Interpolation (MCFI) techniques are applied for an effective axial interpolation of tomographic images sequences, with the main objective of obtaining a refined 3D reconstruction. The performance of the proposed method was assessed by using high-resolution CT sequences. After downsampling along the axial direction, the missing slices were recovered by using the proposed algorithm, to obtain an estimate of the original sequence. The experimental results show that the 3D models obtained from the downsampled/interpolated sequence are very close to those obtained from the original one thus providing a high-quality 3D skull reconstruction.