Pseudo super-resolution for improved calcification characterization for cone beam breast CT (CBBCT)

Abstract

Cone Beam Breast CT imaging (CBBCT) is a promising tool for diagnosis of breast tumors and calcifications. However, as the sizes of calcifications in early stages are very small, it is not easy to distinguish them from background tissues because of the relatively high noise level. Therefore, it is necessary to enhance the visualization of calcifications for accurate detection. In this work, the Papoulis-Gerchberg (PG) method was introduced and modified to improve calcification characterization. PG method is an iterative algorithm of signal extrapolation and has been demonstrated to be very effective in image restoration like super-resolution (SR) and inpainting. The projection images were zoomed by bicubic interpolation method, then the modified PG method were applied to improve the image quality. The reconstruction from processed projection images showed that this approach can effectively improve the image quality by improving the Modulation Transfer Function (MTF) with a limited increase in noise level. As a result, the detectability of calcifications was improved in CBBCT images.