Abstract
Although Computed Tomography (CT) is a mature discipline, the development of techniques that will further reduce radiation dose are still essential. This paper makes steps towards projection andreconstruction methods which aim to assist in the reduction of this dosage, by studying the way noise propagates from projection space to image space. Inference methods Maximum Likelihood Estimation (MLE), Akaike’s Information Criterion (AIC) and Minimum Message Length (MML) are used to obtain accurate models obtained from minimal data.
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Dalgleish, A.P., Dowe, D.L., Svalbe, I.D. (2007). Tomographic Reconstruction of Images from Noisy Projections - A Preliminary Study. In: Orgun, M.A., Thornton, J. (eds) AI 2007: Advances in Artificial Intelligence. AI 2007. Lecture Notes in Computer Science(), vol 4830. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76928-6_55
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DOI: https://doi.org/10.1007/978-3-540-76928-6_55
Publisher Name: Springer, Berlin, Heidelberg
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