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PET imaging is an important tool commonly used for studying disease by research consortia which implement multi-centre studies to improve the statistical power of findings. The UK government launched the Dementias Platform UK to facilitate one of the world's largest dementia population study involving national centres equipped with state-of-the-art PET/MR scanners from two major vendors. However,...
We describe the main theoretical principles behind Time-resolved Optical Absorption and Scattering Tomography (TOAST). The problem is viewed as the optimisation of an error-norm derived from correlated statistics of the time-dependent photon intensity at the surface of an object. The field is compared with Electrical Impedance Tomography (EIT). Some inverse algorithms are suggested and one implemented...
This paper addresses the problem of image reconstruction in optical tomography with respect to the measurement types used. We demonstrate the difficulty of the simultaneous reconstruction of absorption and diffusion images, by using both a simple circular case with embedded inhomogeneities, and a complex neonatal head model, and show that improvements are possible by combining suitable measurement...
An approach to high throughput and high accuracy modelling of the geometric component of PET acquisition for the Siemens Biograph mMR PET/MR scanner is presented. The geometric components calculated in forward and back-projections are computationally expensive, however, they are inherently parallel and therefore, they are suitable for implementation on parallel computing platforms such as CUDA, consequently...
In this study, we aim at reconstructing single photon emission computed tomography (SPECT) images using a Bayesian framework to incorporate anatomical information from magnetic resonance (MR) as a priori knowledge about the activity distribution. This is achieved using an anatomically-driven Bowsher prior (BP). Standard BP has the potential to obtain similar results as other state-of-the-art prior...
We describe a nonparametric framework for incorporating information from co-registered anatomical images into positron emission tomographic (PET) image reconstruction through priors based on information theoretic similarity measures. We compare and evaluate the use of mutual information (MI) and joint entropy (JE) between feature vectors extracted from the anatomical and PET images as priors in PET...
In emission tomography (ET), fast developing Bayesian reconstruction methods can incorporate anatomical information derived from co-registered scanning modalities, such as magnetic resonance (MR) and computed tomography (CT). We propose a Bayesian image reconstruction method for single photon emission computed tomography (SPECT), using a joint entropy (JE) similarity measure to embed MR anatomical...
Model reduction is often required in optical diffusion tomography (ODT), typically due to limited available computation time or computer memory. In practice, this often means that we are bound to use sparse meshes in the model for the forward problem. Conversely, if we are given more and more accurate measurements, we have to employ increasingly accurate forward problem solvers in order to exploit...
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