3DMPR -- A robust morphological approach for applying phase retrieval in proximity to highly-attenuating objects in CT

Abstract

X-ray imaging is a fast, precise and non-invasive method of imaging which, when combined with computed tomography, provides detailed 3D rendering of samples. Incorporating propagation-based phase contrast can vastly improve data quality for weakly attenuating samples via phase retrieval, allowing radiation exposure to be reduced. However, applying phase retrieval to multi-material samples commonly requires choice of which material boundary to tune the reconstruction. Selecting the boundary with strongest phase contrast increases noise suppression, but at the detriment of over-blurring other interfaces and potentially removing quantitative sample information. Additionally, conventional phase-retrieval algorithms cannot be used for regions bounded by more than one material, requiring alternative methods. Here we present a computationally-efficient, non-iterative nor AI-mediated method for applying strong phase retrieval, whilst preserving sharp boundaries for all materials within the sample. 3D phase retrieval is combined with morphological operations to prevent over-blurring artefacts from being introduced, while avoiding the potentially long convergence times required by iterative approaches. This technique, entitled 3DMPR, was tested on phase contrast images of a rabbit kitten brain encased by the surrounding dense skull. Using 24kVp synchrotron radiation with a 5m propagation distance, 3DMPR provided a 6.8-fold improvement in the signal-to-noise ratio (SNR) of brain tissue over the standard phase retrieval procedure, without over-smoothing the images.