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- W2040777056 abstract "Purpose: To develop a graphics processing unit (GPU) based ultra fast direct aperture optimization (DAO) algorithm in intensity modulated radiation therapy (IMRT) treatment planning. Method and Materials: While DAO problems are well-studied, most of them focus on heuristic search methods such as simulated annealing and the computational efficiency is often very low. In contrast, we formulate this problem as a large-scale convex programming problem in terms of all multi-leaf collimator (MLC) deliverable apertures and their associated intensities. An exact method called column generation method is used which iteratively adds high-quality deliverable apertures while the treatment plan quality is improved. The efficiency of this approach has been ensured by exploiting fine-grained parallelism to effectively utilize the computational recourses on GPU. Results: A clinical prostate IMRT case with various beamlet and voxel sizes is used to evaluate our implementation. High quality treatment plans are obtained at a high efficiency. In particular, for a 9-field prostate case with 5×5 mm2 beamlet size and 2.5×2.5×2.5 mm3 voxel size, the implementation takes only 7.1 seconds to generate 50 MLC apertures on an NVIDIA Tesla C1060 GPU. Conclusion: This work solved a major problem in developing ultra fast (re-)planning technologies for fast treatment planning in conventional IMRT and for real-time re-planning for online adaptive radiotherapy." @default.
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- W2040777056 date "2010-06-01" @default.
- W2040777056 modified "2023-09-22" @default.
- W2040777056 title "WE-B-BRA-01: GPU-Based Ultra Fast Direct Aperture Optimization in IMRT Treatment Planning" @default.
- W2040777056 doi "https://doi.org/10.1118/1.3469341" @default.
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