A new optimization method using a compressed sensing inspired solver for real-time LDR-brachytherapy treatment planning
This work discusses a novel strategy for inverse planning in low dose rate brachytherapy. It applies the idea of compressed sensing to the problem of inverse treatment planning and a new solver for this formulation is developed. An inverse planning algorithm was developed incorporating brachytherapy...
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| Hauptverfasser: | , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
16 February 2015
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| In: |
Physics in medicine and biology
Year: 2015, Jahrgang: 60, Heft: 6, Pages: 2179-2194 |
| ISSN: | 1361-6560 |
| DOI: | 10.1088/0031-9155/60/6/2179 |
| Online-Zugang: | Verlag, Volltext: http://dx.doi.org/10.1088/0031-9155/60/6/2179 Verlag, Volltext: http://stacks.iop.org/0031-9155/60/i=6/a=2179 
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| Verfasserangaben: | C. Guthier, K.P. Aschenbrenner, D. Buergy, M. Ehmann, F. Wenz and J.W. Hesser |
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| 245 | 1 | 2 | |a A new optimization method using a compressed sensing inspired solver for real-time LDR-brachytherapy treatment planning |c C. Guthier, K.P. Aschenbrenner, D. Buergy, M. Ehmann, F. Wenz and J.W. Hesser |
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| 520 | |a This work discusses a novel strategy for inverse planning in low dose rate brachytherapy. It applies the idea of compressed sensing to the problem of inverse treatment planning and a new solver for this formulation is developed. An inverse planning algorithm was developed incorporating brachytherapy dose calculation methods as recommended by AAPM TG-43. For optimization of the functional a new variant of a matching pursuit type solver is presented. The results are compared with current state-of-the-art inverse treatment planning algorithms by means of real prostate cancer patient data. The novel strategy outperforms the best state-of-the-art methods in speed, while achieving comparable quality. It is able to find solutions with comparable values for the objective function and it achieves these results within a few microseconds, being up to 542 times faster than competing state-of-the-art strategies, allowing real-time treatment planning. The sparse solution of inverse brachytherapy planning achieved with methods from compressed sensing is a new paradigm for optimization in medical physics. Through the sparsity of required needles and seeds identified by this method, the cost of intervention may be reduced. | ||
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