Minimum message length clustering of spatially-correlated data with varying inter-class penalties (2007)

by Gerhard Visser, D L Dowe
Venue:In Proceedings of the 6th IEEE international conference on computer and information science (ICIS) 2007
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Wallace’s Approach to Unsupervised Learning: The Snob Program

by Murray A. Jorgensen, Geoffrey J. McLachlan , 2008
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Tomographic Reconstruction of Images from Noisy Projections- A Preliminary Study

by A. P. Dalgleish, D. L. Dowe, I. D. Svalbe
"... 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 and reconstruction methods which aim to assist in the reduction of this dosage, by studying the way ..."
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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 and reconstruction 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. 1

Information-Theoretic Image Reconstruction and Segmentation from Noisy Projections

by Gerhard Visser, David L. Dowe, Imants D. Svalbe
"... Abstract. The minimum message length (MML) principle for inductive inference has been successfully applied to image segmentation where the images are modelled by Markov random fields (MRF). We have extended this work to be capable of simultaneously reconstructing and segmenting images that have been ..."
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Abstract. The minimum message length (MML) principle for inductive inference has been successfully applied to image segmentation where the images are modelled by Markov random fields (MRF). We have extended this work to be capable of simultaneously reconstructing and segmenting images that have been observed only through noisy projections. The noise added to each projection depends on the classes of the pixels (material) that it passes through. The intended application is in low-dose (low-flux) X-ray computed tomography (CT) where irregular projections are used. 1

Ninimum Message Length and Statistically Consistent Invariant; (Objective?) Bayesian Probabilistic Inference -- From (Medical) “Evidence”

by David L. Dowe - SOCIAL EPISTEMOLOGY VOL. 22, NO. 4, OCTOBER–DECEMBER 2008, PP. 433–460 , 2008
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