arXiv subjects

M. J. Kitchen

Publications and source records attributed to M. J. Kitchen.

5 recordsLinked to original sources

arXiv2023

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

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.

physics.med-ph↗

arXiv2022

Precise phase retrieval for propagation-based images using discrete mathematics

The ill-posed problem of phase retrieval in optics, using one or more intensity measurements, has a multitude of applications using electromagnetic or matter waves. Many phase retrieval algorithms are computed on pixel arrays using discrete Fourier transforms due to their high computational efficiency. However, the mathematics underpinning these algorithms is typically formulated using continuous mathematics, which can result in a loss in spatial resolution in the reconstructed images. Herein we investigate how phase retrieval algorithms for propagation-based phase-contrast X-ray imaging can be rederived using discrete mathematics and result in more precise retrieval for single- and multi-material objects and for spectral image decomposition. We validate this theory through experimental measurements of spatial resolution using computed tomography (CT) reconstructions of plastic phantoms and biological tissue, using detectors with a range of imaging system point spread functions (PSFs). We demonstrate that if the PSF substantially suppresses high spatial frequencies, the potential improvement from utilising the discrete derivation is limited. However, with detectors characterised by a single pixel PSF (e.g. direct, photon-counting X-ray detectors), a significant improvement in spatial resolution can be obtained, demonstrated here at up to 17%.

eess.IV↗

arXiv2022

Accurate measures of regional lung air volumes from chest X-rays of small animals

We present a robust technique for calculating regional volume changes within the lung from X-ray radiograph sequences captured during ventilation, without the use of computed tomography (CT). This technique is based on the change in transmitted X-ray intensity that occurs for each lung region as air displaces the attenuating lung tissue. Lung air volumes calculated from X-ray intensity changes showed a strong correlation ($R^2$=0.98) against the true volumes, measured from high-resolution CT. This correlation enables us to accurately convert projected intensity data into relative changes in lung air volume. We have applied this technique to measure changes in regional lung volumes from X-ray image sequences of mechanically ventilated, recently-deceased newborn rabbits, without the use of CT. This method is suitable for biomedical research studies and shows potential for clinical application.

physics.med-ph↗

arXiv2021

Tomographic Reconstruction using Tilted Laue Analyser Based X-ray Phase-Contrast Imaging

Analyser-Based Phase-Contrast imaging (ABPCI) is a phase-contrast imaging method that produces high contrast images of weakly absorbing materials. However, it is only sensitive to phase variations lying in the diffraction plane of the analyser crystal (i.e in one dimension; 1-D), as it is highly sensitive to phase variations lying in the diffraction plane of the analyser crystal. In order to accurately account for and measure phase effects produced by the wavefield-sample interaction, ABPCI and other 1-D phase sensitive methods must achieve 2-D phase sensitivity. We applied an inclined geometry method to a Laue geometry setup for X-ray ABPCI through rotation of the detector and object about the optical axis. This allowed this traditionally 1-D phase sensitive phase contrast method to possess 2-D phase sensitivity. We acquired tomographic datasets over 360 degrees of a multi-material phantom with the detector and sample tilted by 8 degrees. The real and imaginary parts of the refractive index were reconstructed for the phantom.

physics.med-ph↗

arXiv2016

Extraction of depth moments by exploiting the partial coherence of radiation

We retrieve depth information (moments) of an object using partially coherent fields and defocus induced holographic contrast. Our analysis leads to a form of tomography that does not require sample or source rotation. The tomography method presented here is performed with only two in-line images.

physics.optics↗