Linked Life Data

16150629

Source:http://linkedlifedata.com/resource/pubmed/id/16150629

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PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2005-12-12
pubmed:abstractText
The efficacy of radiation therapy treatment depends on the patient setup accuracy at each daily fraction. A significant problem is reproducing the patient position during treatment planning for every fraction of the treatment process. We propose and evaluate an intensity based automatic registration method using multiple portal images and the pre-treatment CT volume. We perform both geometric and radiometric calibrations to generate high quality digitally reconstructed radiographs (DRRs) that can be compared against portal images acquired right before treatment dose delivery. We use a graphics processing unit (GPU) to generate the DRRs in order to gain computational efficiency. We also perform a comparative study on various similarity measures and optimization procedures. Simple similarity measure such as local normalized correlation (LNC) performs best as long as the radiometric calibration is carefully done. Using the proposed method, we achieved better than 1mm average error in repositioning accuracy for a series of phantom studies using two open field (i.e., 41 cm2) portal images with 90 degrees vergence angle.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
1361-8415
pubmed:author
pubmed:issnType
Print
pubmed:volume
10
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
96-112
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
Automatic registration of portal images and volumetric CT for patient positioning in radiation therapy.
pubmed:affiliation
Imaging and Visualization Department, Siemens Corporate Research, Inc., 755 College Road East, Princeton, NJ 08540, USA. akhamene@scr.siemens.com
pubmed:publicationType
Journal Article