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Use of proximal operator graph solver for radiation therapy inverse treatment planning
PURPOSE: Most radiation therapy optimization problems can be formulated as an unconstrained problem and solved efficiently by quasi‐Newton methods such as the Limited‐memory Broyden‐Fletcher‐Goldfarb‐Shanno (L‐BFGS) algorithm. However, several next generation planning techniques such as total variat...
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| Publicado no: | Med Phys |
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| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
John Wiley and Sons Inc.
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5508626/ https://ncbi.nlm.nih.gov/pubmed/28211070 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/mp.12165 |
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