| pubmed-article:15843735 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:15843735 | lifeskim:mentions | umls-concept:C0449468 | lld:lifeskim |
| pubmed-article:15843735 | lifeskim:mentions | umls-concept:C1516769 | lld:lifeskim |
| pubmed-article:15843735 | lifeskim:mentions | umls-concept:C0301630 | lld:lifeskim |
| pubmed-article:15843735 | lifeskim:mentions | umls-concept:C1512814 | lld:lifeskim |
| pubmed-article:15843735 | lifeskim:mentions | umls-concept:C1880157 | lld:lifeskim |
| pubmed-article:15843735 | lifeskim:mentions | umls-concept:C0032074 | lld:lifeskim |
| pubmed-article:15843735 | pubmed:issue | 9 | lld:pubmed |
| pubmed-article:15843735 | pubmed:dateCreated | 2005-4-21 | lld:pubmed |
| pubmed-article:15843735 | pubmed:abstractText | The objective of radiotherapy planning is to find a compromise between the contradictive goals of delivering a sufficiently high dose to the target volume while widely sparing critical structures. The search for such a compromise requires the computation of several plans, which mathematically means solving several optimization problems. In the case of intensity modulated radiotherapy (IMRT) these problems are large-scale, hence the accumulated computational expense is very high. The adaptive clustering method presented in this paper overcomes this difficulty. The main idea is to use a preprocessed hierarchy of aggregated dose-volume information as a basis for individually adapted approximations of the original optimization problems. This leads to a decisively reduced computational expense: numerical experiments on several sets of real clinical data typically show computation times decreased by a factor of about 10. In contrast to earlier work in this field, this reduction in computational complexity will not lead to a loss in accuracy: the adaptive clustering method produces the optimum of the original optimization problem. | lld:pubmed |
| pubmed-article:15843735 | pubmed:language | eng | lld:pubmed |
| pubmed-article:15843735 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:15843735 | pubmed:citationSubset | IM | lld:pubmed |
| pubmed-article:15843735 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:15843735 | pubmed:month | May | lld:pubmed |
| pubmed-article:15843735 | pubmed:issn | 0031-9155 | lld:pubmed |
| pubmed-article:15843735 | pubmed:author | pubmed-author:BortfeldThoma... | lld:pubmed |
| pubmed-article:15843735 | pubmed:author | pubmed-author:KüferKarl-Hei... | lld:pubmed |
| pubmed-article:15843735 | pubmed:author | pubmed-author:AlonsoFernand... | lld:pubmed |
| pubmed-article:15843735 | pubmed:author | pubmed-author:ScherrerAlexa... | lld:pubmed |
| pubmed-article:15843735 | pubmed:author | pubmed-author:MonzMichaelM | lld:pubmed |
| pubmed-article:15843735 | pubmed:issnType | Print | lld:pubmed |
| pubmed-article:15843735 | pubmed:day | 7 | lld:pubmed |
| pubmed-article:15843735 | pubmed:volume | 50 | lld:pubmed |
| pubmed-article:15843735 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:15843735 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:15843735 | pubmed:pagination | 2033-53 | lld:pubmed |
| pubmed-article:15843735 | pubmed:dateRevised | 2006-11-15 | lld:pubmed |
| pubmed-article:15843735 | pubmed:meshHeading | pubmed-meshheading:15843735... | lld:pubmed |
| pubmed-article:15843735 | pubmed:meshHeading | pubmed-meshheading:15843735... | lld:pubmed |
| pubmed-article:15843735 | pubmed:meshHeading | pubmed-meshheading:15843735... | lld:pubmed |
| pubmed-article:15843735 | pubmed:meshHeading | pubmed-meshheading:15843735... | lld:pubmed |
| pubmed-article:15843735 | pubmed:meshHeading | pubmed-meshheading:15843735... | lld:pubmed |
| pubmed-article:15843735 | pubmed:meshHeading | pubmed-meshheading:15843735... | lld:pubmed |
| pubmed-article:15843735 | pubmed:meshHeading | pubmed-meshheading:15843735... | lld:pubmed |
| pubmed-article:15843735 | pubmed:meshHeading | pubmed-meshheading:15843735... | lld:pubmed |
| pubmed-article:15843735 | pubmed:meshHeading | pubmed-meshheading:15843735... | lld:pubmed |
| pubmed-article:15843735 | pubmed:meshHeading | pubmed-meshheading:15843735... | lld:pubmed |
| pubmed-article:15843735 | pubmed:meshHeading | pubmed-meshheading:15843735... | lld:pubmed |
| pubmed-article:15843735 | pubmed:meshHeading | pubmed-meshheading:15843735... | lld:pubmed |
| pubmed-article:15843735 | pubmed:meshHeading | pubmed-meshheading:15843735... | lld:pubmed |
| pubmed-article:15843735 | pubmed:meshHeading | pubmed-meshheading:15843735... | lld:pubmed |
| pubmed-article:15843735 | pubmed:meshHeading | pubmed-meshheading:15843735... | lld:pubmed |
| pubmed-article:15843735 | pubmed:meshHeading | pubmed-meshheading:15843735... | lld:pubmed |
| pubmed-article:15843735 | pubmed:meshHeading | pubmed-meshheading:15843735... | lld:pubmed |
| pubmed-article:15843735 | pubmed:year | 2005 | lld:pubmed |
| pubmed-article:15843735 | pubmed:articleTitle | IMRT planning on adaptive volume structures--a decisive reduction in computational complexity. | lld:pubmed |
| pubmed-article:15843735 | pubmed:affiliation | Department of Optimization, Fraunhofer Institut for Industrial Mathematics, Gottlieb-Daimler-Strasse 49, 67663 Kaiserslautern, Germany. scherrer@itwm.fhg.de | lld:pubmed |
| pubmed-article:15843735 | pubmed:publicationType | Journal Article | lld:pubmed |
| pubmed-article:15843735 | pubmed:publicationType | Comparative Study | lld:pubmed |
| pubmed-article:15843735 | pubmed:publicationType | Research Support, Non-U.S. Gov't | lld:pubmed |
| pubmed-article:15843735 | pubmed:publicationType | Evaluation Studies | lld:pubmed |
| pubmed-article:15843735 | pubmed:publicationType | Validation Studies | lld:pubmed |
