Micro scale computed tomography (CT) can resolve many features in cellular structures, bone formations, minerals properties and composite materials not seen at lower spatial-resolution. Those features enable us to build a more comprehensive model for the object of interest. CT resolution is limited by a fundamental trade off between source size and signal-to-noise ratio (SNR) for a given acquisition time. There is a limit on the X-ray flux that can be emitted from a certain source size, and fewer photons cause a lower SNR. A large source size creates penumbral blurring in the radiograph, limiting the effective spatial-resolution in the reconstruction. High cone-angle CT improves SNR by increasing the X-ray solid angle that passes through the sample. In the high cone-angle regime current source deblurring methods break down due to incomplete modelling of the physical process. This paper presents high cone-angle source de-blurring models. We implement these models using a novel multi-slice Richardson-Lucy (M-RL) and 3D Conjugate Gradient deconvolution on experimental high cone-angle data to improve the spatial-resolution of the reconstructed volume. In M-RL, we slice the back projection volume into subsets which can be considered to have a relative uniform convolution kernel. We compare these results to those obtained from standard reconstruction techniques and current source deblurring methods (i.e. 2D Richardson-Lucy in the radiograph and the volume respectively).

Date Published: 11 September 2014
PDF: 11 pages
Proc. SPIE 9212, Developments in X-Ray Tomography IX, 92120B (11 September 2014); doi: 10.1117/12.2062415

Published in SPIE Proceedings Vol. 9212:
Developments in X-Ray Tomography IX
Stuart R. Stock, Editor(s)