Amplifying image quality gain in x-ray phase contrast imaging of mastectomy samples with deep learning denoising

Abstract

Objective.Phase-contrast computed tomography (PCT) of the breast has previously been shown to produce higher-quality images at lower radiation doses without the need for breast compression. The present study is aimed at further reduction of the radiation dose in PCT, while preserving or further increasing the image quality, by applying supervised deep learning denoising of reconstructed PCT images. This work was carried out in preparation for live patient PCT breast cancer imaging, initially at specialised synchrotron facilities.Approach.PCT scans of 34 fresh full mastectomy samples were acquired using propagation-based phase-contrast imaging with 32 keV monochromatic parallel x-rays at mean..