Abstract
Causal images in emission tomography are defined as those which could have generated the data by the statistical process that governs the physics of the measurement. The concept of causality was previously applied to deciding when to stop the MLE iterative procedure in PET. The present paper further explores the concept, indicates the difficulty of carrying out a correct hypothesis testing for causality, discusses the assumption needed to justify the tests proposed and discusses a possible methodology for a justification of that assumption. The paper also describes several methods that we have found to generate causal images and it shows that the set of causal images is rather large. This set includes images judged to be superior to the best maximum likelihood images, but is also includes unacceptable and noisy images. The paper concludes by proposing to use causality as a constraint in optimization problems.
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© 1992 Springer-Verlag Berlin Heidelberg
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Llacer, J., Veklerov, E., Nunez, J. (1992). The Concept of Causality in Image Reconstruction. In: Todd-Pokropek, A.E., Viergever, M.A. (eds) Medical Images: Formation, Handling and Evaluation. NATO ASI Series, vol 98. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-77888-9_15
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DOI: https://doi.org/10.1007/978-3-642-77888-9_15
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