Multiobjective evolutionary optimization of the number of beams, their orientations and weights for intensity-modulated radiation therapy

Schreibmann, E; Lahanas, M; Xing, L; Baltas, D

dc.contributor.author	Schreibmann, E	en
dc.contributor.author	Lahanas, M	en
dc.contributor.author	Xing, L	en
dc.contributor.author	Baltas, D	en
dc.date.accessioned	2014-03-01T01:21:06Z
dc.date.available	2014-03-01T01:21:06Z
dc.date.issued	2004	en
dc.identifier.issn	0031-9155	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/16066
dc.subject.classification	Engineering, Biomedical	en
dc.subject.classification	Radiology, Nuclear Medicine & Medical Imaging	en
dc.subject.other	Dosimetry	en
dc.subject.other	Evolutionary algorithms	en
dc.subject.other	Optimization	en
dc.subject.other	Radiotherapy	en
dc.subject.other	Tumors	en
dc.subject.other	Evolutionary optimization	en
dc.subject.other	Inverse planning	en
dc.subject.other	Medicine	en
dc.subject.other	algorithm	en
dc.subject.other	article	en
dc.subject.other	beam therapy	en
dc.subject.other	controlled study	en
dc.subject.other	head and neck cancer	en
dc.subject.other	histogram	en
dc.subject.other	intensity modulated radiation therapy	en
dc.subject.other	priority journal	en
dc.subject.other	prostate cancer	en
dc.subject.other	radiation dose distribution	en
dc.subject.other	Algorithms	en
dc.subject.other	Head and Neck Neoplasms	en
dc.subject.other	Humans	en
dc.subject.other	Male	en
dc.subject.other	Models, Statistical	en
dc.subject.other	Models, Theoretical	en
dc.subject.other	Phantoms, Imaging	en
dc.subject.other	Prostatic Neoplasms	en
dc.subject.other	Radiometry	en
dc.subject.other	Radiotherapy Dosage	en
dc.subject.other	Radiotherapy Planning, Computer-Assisted	en
dc.subject.other	Radiotherapy, Conformal	en
dc.subject.other	Time Factors	en
dc.title	Multiobjective evolutionary optimization of the number of beams, their orientations and weights for intensity-modulated radiation therapy	en
heal.type	journalArticle	en
heal.identifier.primary	10.1088/0031-9155/49/5/007	en
heal.identifier.secondary	http://dx.doi.org/10.1088/0031-9155/49/5/007	en
heal.language	English	en
heal.publicationDate	2004	en
heal.abstract	We propose a hybrid multiobjective (MO) evolutionary optimization algorithm (MOEA) for intensity-modulated radiotherapy inverse planning and apply it to optimize the number of incident beams, their orientations and intensity profiles. The algorithm produces a set of efficient solutions, which represent different clinical trade-offs and contains information such as variety of dose distributions and dose-volume histograms. No importance factors are required and solutions can be obtained in regions not accessible by conventional weighted sum approaches. The application of the algorithm using a test case, a prostate and a head and neck tumour case is shown. The results are compared with MO inverse planning using a gradient-based optimization algorithm. © 2004 IOP Publishing Ltd.	en
heal.publisher	IOP PUBLISHING LTD	en
heal.journalName	Physics in Medicine and Biology	en
dc.identifier.doi	10.1088/0031-9155/49/5/007	en
dc.identifier.isi	ISI:000220314800007	en
dc.identifier.volume	49	en
dc.identifier.issue	5	en
dc.identifier.spage	747	en
dc.identifier.epage	770	en