3DMPR - a robust morphological approach for applying phase retrieval in proximity to highly attenuating objects in computed tomography.

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 the 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 24 keV synchrotron radiation with a 5 m 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. Simultaneous quantification of edge resolution and SNR gain was performed with an aluminium-water phantom imaged using a microfocus X-ray tube at 35 kV