Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Optimal Terrain Construction Problems and Applications in Intensity-Modulated Radiation Therapy
ESA '02 Proceedings of the 10th Annual European Symposium on Algorithms
Geometric algorithms for static leaf sequencing problems in radiation therapy
Proceedings of the nineteenth annual symposium on Computational geometry
Generalized geometric approaches for leaf sequencing problems in radiation therapy
ISAAC'04 Proceedings of the 15th international conference on Algorithms and Computation
Optimal Field Splitting with Feathering in Intensity-Modulated Radiation Therapy
AAIM '07 Proceedings of the 3rd international conference on Algorithmic Aspects in Information and Management
Minimum Cardinality Matrix Decomposition into Consecutive-Ones Matrices: CP and IP Approaches
CPAIOR '07 Proceedings of the 4th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
ESA '08 Proceedings of the 16th annual European symposium on Algorithms
The matrix orthogonal decomposition problem in intensity-modulated radiation therapy
COCOON'06 Proceedings of the 12th annual international conference on Computing and Combinatorics
Minimizing setup and beam-on times in radiation therapy
APPROX'06/RANDOM'06 Proceedings of the 9th international conference on Approximation Algorithms for Combinatorial Optimization Problems, and 10th international conference on Randomization and Computation
Field splitting problems in intensity-modulated radiation therapy
ISAAC'06 Proceedings of the 17th international conference on Algorithms and Computation
A new field splitting algorithm for intensity-modulated radiation therapy
COCOON'07 Proceedings of the 13th annual international conference on Computing and Combinatorics
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In this paper, we present a new geometric algorithm for the 3-D static leaf sequencing (SLS) problem arising in intensity-modulated radiation therapy (IMRT), a modern cancer treatment technique. The treatment time and machine delivery error are two crucial factors for measuring the quality of a solution (i.e., a treatment plan) for the SLS problem. In the current clinical practice, physicians prefer to use treatment plans with the lowest possible amount of delivery error, and are also very concerned about the treatment time. Previous SLS methods in both the literature and commercial treatment planning systems either cannot minimize the error or achieve that only by treatment plans which require a prolonged treatment time. In comparison, our new geometric algorithm is computationally efficient; more importantly, it guarantees that the output treatment plans have the lowest possible amount of delivery error, and the treatment time for the plans is significantly shorter. Our solution is based on a number of novel schemes and ideas (e.g., mountain reduction, block matching, profile-preserving cutting, etc) which may be of interest in their own right. Experimental results based on real medical data showed that our new algorithm runs fast and produces much better quality treatment plans than current commercial planning systems and well-known algorithms in medical literature.