Spiral CT image deblurring for cochlear implantation

Cochlear implantation is the standard treatment for profound hearing lass. Preimplantation and postinplantation spiral computed tomography (CT) is essential in several key clinical and research aspects. The maximum image resolution with commercial spiral CT scanners is insufficient to define clearly anatomical features and implant electrode positions in the inner ear. In this paper, we develop an expectation-maximization (EM)-like iterative deblurring algorithm to achieve spiral CT image super-resolution for cochlear implantation, assuming a spatially invariant linear spiral CT system with a three-dimensional (3-D) separable Gaussian point spread function (PSF), We experimentally validate the 3-D Gaussian blurring model via phantom measurement and profile fitting. The imaging process is further expressed as convolution of an isotropic 3-D Gaussian PSF and a blurred underlying volumetric image, Under practical conditions, an oblique reconstructed section is approximated as convolution of an isotropic two-dimensional (2-D) Gaussian PSP and the corresponding actual cross section. The spiral CT image deblurring algorithm is formulated with sieve and resolution kernels for suppressing noise and edge artifacts. A typical cochlear cross section is used for evaluation, demonstrating a resolution gain up to 30%-40% according to the correlation criterion. Physical phantoms, preimplantation and postimplantation patients are reconstructed into volumes of 0.1-mm cubic voxels, The patient images are digitally unwrapped along the central axis of the cochlea and the implanted electrode array respectively, then oblique sections orthogonal to the central axis formed. After deblurring, representation of structural features is substantially improved in all the cases.