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Nullspace regularization and MAP reconstruction in the ill-posed inverse imaging problem

Kwee, IW; Tanikawa, Y; Proskurin, S; Arridge, SR; Delpy, DT; Yamada, Y; (1996) Nullspace regularization and MAP reconstruction in the ill-posed inverse imaging problem. PHOTON PROPAGATION IN TISSUES II, PROCEEDINGS OF , 2925 43 - 54.

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Abstract

The ill-posed inverse problem is not an issue that is only restricted to optical tomography, but indeed a very common issue in image reconstruction problems in astronomy, geological surveying, and medical imaging in general. In this paper toe investigate the consequences of ill-posed problems, and show that correct reconstruction is generally not possible using conventional linear inversion techniques because latter methods disregard contributions of the nullspace. We describe the rationale of a novel image reconstruction method that estimates the nullspace contibution using prior knowledge in a maximum-aposteriori-probability (MAP) framework. We illustrate our concept by an example of optical tomographic reconstruction from simulated and experimental data.

Type:Article
Title:Nullspace regularization and MAP reconstruction in the ill-posed inverse imaging problem
Location:VIENNA, AUSTRIA
Keywords:optical tomography, image reconstruction, maximum a posteriori probability, ill-posed problems, Bayesian probability, prior knowledge
UCL classification:UCL > School of BEAMS > Faculty of Engineering Science > Computer Science
UCL > School of BEAMS > Faculty of Engineering Science > Medical Physics and Bioengineering

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