Radiation therapy is one of the commonly used cancer therapies. The radiation treatment poses a tuning problem: it needs to be effective enough to destroy the tumor, but it should maintain the functionality of the organs close to the tumor. Towards this goal the design of a radiation treatment has to be customized for each patient. Part of this design are intensity matrices that define the radiation dosage in a discretization of the beam head. To minimize the treatment time of a patient the beam-on time and the setup time need to be minimized. For a given row of the intensity matrix, the minimum beam-on time is equivalent to the minimum number of binary vectors with the consecutive "1"s property that sum to this row, and the minimum setup time is equivalent to the minimum number of distinct vectors in a set of binary vectors with the consecutive "1"s property that sum to this row. We give a simple linear time algorithm to compute the minimum beam-on time. We prove that the minimum setup time problem is APX-hard and give approximation algorithms for it using a duality property. For the general case, we give a 24 13 approximation algorithm. For unimodal rows, we give a 9 7 approximation algorithm. We also consider other variants for which better approximation ratios exist.
Bansal et al. REF provide a ¾ ½¿-approximation algorithm for the single-row problem and give better approximations for more constrained versions.
Minimizing setup and beam-on times in radiation therapy
In Proceedings of APPROX 2006
Mathematics Computer Science