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Parallel application of block-iterative methods in medical imaging and radiation therapy

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Abstract

Some row-action algorithms which exploit special objective function and constraints structure have proven advantageous for solving huge and sparse feasibility or optimization problems. Recently developed block-iterative versions of such special-purpose methods enable parallel computation when the underlying problem is appropriately decomposed. This opens the door for parallel computation in image reconstruction problems of computerized tomography and in the inverse problem of radiation therapy treatment planning, all in their fully discretized modelling approach. Since there is more than one way of deriving block-iterative versions of any row-action method, the choice has to be made with reference to the underlying real-world problem.

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This research was done with partial support of National Institutes of Health, Grant HL-28438 while the author was with the Medical Image Processing Group (MIPG) at the Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA.

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Censor, Y. Parallel application of block-iterative methods in medical imaging and radiation therapy. Mathematical Programming 42, 307–325 (1988). https://doi.org/10.1007/BF01589408

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