Full metadata record
DC FieldValueLanguage
dc.contributor.authorWalek, Petr
dc.contributor.authorJan, Jiří
dc.contributor.authorOuředníček, Petr
dc.contributor.authorSkotáková, Jarmila
dc.contributor.authorJíra, Igor
dc.contributor.editorSkala, Václav
dc.identifier.citationJournal of WSCG. 2012, vol. 20, no. 1, p. 73-80.en
dc.identifier.issn1213-6972 (hardcopy)
dc.identifier.issn1213–6980 (CD-ROM)
dc.identifier.issn1213–6964 (on-line)
dc.description.abstractRadiation dose reduction is a very topical problem in medical X-ray CT imaging and plenty of strategies have been introduced recently. Hybrid iterative reconstruction algorithms are one of them enabling dose reduction up to 70 %. The paper describes data preprocessing and feature extraction from iteratively reconstructed images in order to assess their quality in terms of image noise and compare it with quality of images reconstructed from the same data by the conventional filtered back projection. The preprocessing stage consists in correction of a stair-step artifact and in fast, precise bone and soft tissue segmentation. Noise patterns of differently reconstructed images can therefore be examined separately in these tissue types. In order to remove anatomical structures and to obtain the pure noise, subtraction of images reconstructed by the iterative iDose algorithm from images reconstructed by the filtered back projection is performed. The results of these subtractions called here residual noise images and are the used to further extract parameters of the noise. The noise parameters, which are intended to serve as input data for consequent multidimensional statistical analysis, are the standard deviation and power spectrum of the residual noise. This approach enables evaluation of noise properties in the whole volume of real patient data, in contrast to noise analysis performed in small regions of interest or in images of phantoms.en
dc.format8 s.cs
dc.publisherVáclav Skala - UNION Agencycs
dc.relation.ispartofseriesJournal of WSCGen
dc.rights© Václav Skala - UNION Agencycs
dc.subjectrentgenová počítačová tomografiecs
dc.subjectsnížení dávky zářenícs
dc.subjectsegmentace lebkycs
dc.titlePreprocessing for quantitative statistical noise analysis of MDCT brain images reconstructed using hybrid iterative (iDose) algorithmen
dc.subject.translatedX-ray computed tomographyen
dc.subject.translatedradiation dose reductionen
dc.subject.translatedskull segmentationen
Appears in Collections:Number 1 (2012)

Files in This Item:
File Description SizeFormat 
Valek.pdf724 kBAdobe PDFView/Open

Please use this identifier to cite or link to this item: http://hdl.handle.net/11025/1065

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.