eTheses Repository

Use of prior information and probabilistic image reconstruction for optical tomographic imaging

Basevi, Hector Richard Abraham (2015)
Ph.D. thesis, University of Birmingham.

Loading
PDF (12Mb)Accepted Version

Abstract

Preclinical bioluminescence tomographic reconstruction is underdetermined. This work addresses the use of prior information in bioluminescence tomography to improve image acquisition, reconstruction, and analysis.

A structured light surface metrology method was developed to measure surface geometry and enable robust and automatic integration of mirrors into the measurement process. A mouse phantom was imaged and accuracy was measured at 0.2mm with excellent surface coverage.

A sparsity-regularised reconstruction algorithm was developed to use instrument noise statistics to automatically determine the stopping point of reconstruction. It was applied to in silico and in simulacra data and successfully reconstructed and resolved two separate luminescent sources within a plastic mouse phantom.

A Bayesian framework was constructed that incorporated bioluminescence properties and instrument properties. Distribution expectations and standard deviations were estimated, providing reconstructions and measures of reconstruction uncertainty. The reconstructions showed superior performance when applied to in simulacra data compared to the sparsity-based algorithm.

The information content of measurements using different sets of wavelengths was quantified using the Bayesian framework via mutual information and applied to an in silico problem. Significant differences in information content were observed and comparison against a condition number-based approach indicated subtly different results.

Type of Work:Ph.D. thesis.
Supervisor(s):Styles, Iain B and Dehghani, Hamid and Frampton, Jon
School/Faculty:Colleges (2008 onwards) > College of Engineering & Physical Sciences
Department:School of Chemistry
Subjects:QD Chemistry
T Technology (General)
Institution:University of Birmingham
ID Code:5876
This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder.
Export Reference As : ASCII + BibTeX + Dublin Core + EndNote + HTML + METS + MODS + OpenURL Object + Reference Manager + Refer + RefWorks
Share this item :
QR Code for this page

Repository Staff Only: item control page