Image reconstruction without prior information

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dc.creatorCover, Keith S
dc.date2001-01-14
dc.date2003-10-14
dc.date.accessioned2026-07-07T05:45:19Z
dc.date.available2026-07-07T05:45:19Z
dc.descriptionA novel framework for designing image reconstruction algorithms for linear forward problems is proposed. The framework is based on the novel concept of conserving the information in the data during image reconstruction rather than supplementing it with prior information. The framework offers an explanation as to why the popular reconstruction algorithms for MRI, CT and convolution are generally expressible as left invertible matrices. Also, the framework can be used to improve linear deconvolution and tackle such stubborn linear inverse problems as the Laplace transform.
dc.description10 pages, REVTeX; reworded some sections
dc.identifierhttps://arxiv.org/abs/physics/0101058
dc.identifierhttp://arxiv.org/abs/physics/0101058
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/83950
dc.subjectData Analysis, Statistics and Probability
dc.subjectInstrumentation and Detectors
dc.subjectMedical Physics
dc.titleImage reconstruction without prior information
dc.typetext

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