Abstract
We evaluated the X-ray digital tomosynthesis (DT) reconstruction processing method for metal artifact reduction and the application of wavelet denoising to selectively remove quantum noise and suggest the possibility of image quality improvement using a novel application for chest. In orthopedic DT imaging, we developed artifact reduction methods based on a modified Shepp and Logan reconstruction filter kernel realized by taking into account additional weighing by direct current (DC) components in frequency domain space. Processing leads to an increase in the ratio of low-frequency components in an image. The effectiveness of the method in enhancing the visibility of a prosthetic case was quantified in terms of removal of ghosting artifacts. In chest DT imaging, the technique was implemented on a DT system and experimentally evaluated through chest phantom measurements, spatial resolution and compared with an existing post-reconstruction wavelet denoise algorithm by Badea et al. Our wavelet technique with balance sparsity-norm contrast-to-noise ratio (CNR) effectively decreased quantum noise in the reconstructed images with and improvement when applied to pre-reconstruction image for post-reconstruction. The results of our technique showed that although modulation transfer function (MTF) did not vary (preserving spatial resolution), the existing wavelet denoise algorithm caused MTF deterioration.
