An efficient approach for limited-data chemical species tomography and its error bounds.

We present a computationally efficient reconstruction method for the limited-data chemical species tomography problem that incorporates projection of the unknown gas concentration function onto a low-dimensional subspace, and regularization using prior information obtained from a simple flow model. In this context, the contribution of this work is on the analysis of the projection-induced data errors and the calculation of bounds for the overall image error incorporating the impact of projection and regularization errors as well as measurement noise. As an extension to this methodology, we present a variant algorithm that preserves the positivity of the concentration image.

Spatially resolved and observer-free experimental quantification of spatial resolution in tomographic images.

We present a novel framework and experimental method for the quantification of spatial resolution of a tomography system. The framework adopts the "black box" view of an imaging system, considering only its input and output. The tomography system is locally stimulated with a step input, viz., a sharp edge. The output, viz., the reconstructed images, is analysed by Fourier decomposition of their spatial frequency components, and the local limiting spatial resolution is determined using a cut-off threshold. At no point is an observer involved in the process. The framework also includes a means of translating the quantification region in the imaging space, thus creating a spatially resolved map of objectively quantified spatial resolution. As a case-study, the framework is experimentally applied using a gaseous propane phantom measured by a well-established chemical species tomography system. A spatial resolution map consisting of 28 regions is produced. In isolated regions, the indicated performance is 4-times better than that suggested in the literature and varies by 57% across the imaging space. A mechanism based on adjacent but non-interacting beams is hypothesised to explain the observed behaviour. The mechanism suggests that, as also independently concluded by other methods, a geometrically regular beam array maintains maximum objectivity in reconstructions. We believe that the proposed framework, methodology, and findings will be of value in the design and performance evaluation of tomographic imaging arrays and systems.