Michael E. Kowalok

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We have developed an efficient treatment-planning algorithm for prostate implants that is based on region of interest (ROI) adjoint functions and a greedy heuristic. For this work, we define the adjoint function for an ROI as the sensitivity of the average dose in the ROI to a unit-strength brachytherapy source at any seed position. The greedy heuristic(More)
We continue our work on the development of an efficient treatment-planning algorithm for prostate seed implants by incorporation of an automated seed and needle configuration routine. The treatment-planning algorithm is based on region of interest (ROI) adjoint functions and a greedy heuristic. As defined in this work, the adjoint function of an ROI is the(More)
<lb>The Monte Carlo computer codes MCNP and MCNPX, developed at Los Alamos<lb>National Laboratory, are used for a wide variety of medical physics calculations. They have<lb>the ability to simulate coupled photons, electrons, positrons, protons and neutrons through<lb>general purpose 3-D geometries, with high quality data (or models where data is(More)
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