Publicação:
Wavelets based Algorithm for the Evaluation of Enhanced Liver Areas

dc.contributor.authorAlvarez, Matheus [UNESP]
dc.contributor.authorPina, Diana Rodrigues de
dc.contributor.authorGiacomini, Guilherme [UNESP]
dc.contributor.authorRomeiro, Fernando Gomes
dc.contributor.authorDuarte, Sergio Barbosa
dc.contributor.authorYamashita, Seizo
dc.contributor.authorArruda Miranda, Jose Ricardo de [UNESP]
dc.contributor.authorOurselin, S.
dc.contributor.authorStyner, M. A.
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-12-03T13:10:52Z
dc.date.available2014-12-03T13:10:52Z
dc.date.issued2014-01-01
dc.description.abstractHepatocellular carcinoma (HCC) is a primary tumor of the liver. After local therapies, the tumor evaluation is based on the mRECIST criteria, which involves the measurement of the maximum diameter of the viable lesion. This paper describes a computed methodology to measure through the contrasted area of the lesions the maximum diameter of the tumor by a computational algorithm 63 computed tomography (CT) slices from 23 patients were assessed. Non-contrasted liver and HCC typical nodules were evaluated, and a virtual phantom was developed for this purpose. Optimization of the algorithm detection and quantification was made using the virtual phantom. After that, we compared the algorithm findings of maximum diameter of the target lesions against radiologist measures. Computed results of the maximum diameter are in good agreement with the results obtained by radiologist evaluation, indicating that the algorithm was able to detect properly the tumor limits A comparison of the estimated maximum diameter by radiologist versus the algorithm revealed differences on the order of 0.25 cm for large-sized tumors (diameter > 5 cm), whereas agreement lesser than 1.0cm was found for small-sized tumors. Differences between algorithm and radiologist measures were accurate for small-sized tumors with a trend to a small increase for tumors greater than 5 cm. Therefore, traditional methods for measuring lesion diameter should be complemented with non-subjective measurement methods, which would allow a more correct evaluation of the contrast-enhanced areas of HCC according to the mRECIST criteria.en
dc.description.affiliationUniv Estadual Paulista UNESP, Botucatu Biosci Inst, Dept Phys & Biophys, BR-18618000 Sao Paulo, Brazil
dc.description.affiliationUnespUniv Estadual Paulista UNESP, Botucatu Biosci Inst, Dept Phys & Biophys, BR-18618000 Sao Paulo, Brazil
dc.format.extent9
dc.identifierhttp://dx.doi.org/10.1117/12.2043822
dc.identifier.citationMedical Imaging 2014: Image Processing. Bellingham: Spie-int Soc Optical Engineering, v. 9034, 9 p., 2014.
dc.identifier.doi10.1117/12.2043822
dc.identifier.fileWOS000338543300155.pdf
dc.identifier.issn0277-786X
dc.identifier.urihttp://hdl.handle.net/11449/112609
dc.identifier.wosWOS:000338543300155
dc.language.isoeng
dc.publisherSpie - Int Soc Optical Engineering
dc.relation.ispartofMedical Imaging 2014: Image Processing
dc.rights.accessRightsAcesso aberto
dc.sourceWeb of Science
dc.subjectHCCen
dc.subjectmedical image segmentationen
dc.subjectliveren
dc.subjectmedical imagingen
dc.subjectcomputed tomographyen
dc.subjectimage processingen
dc.titleWavelets based Algorithm for the Evaluation of Enhanced Liver Areasen
dc.typeTrabalho apresentado em evento
dcterms.rightsHolderSpie-int Soc Optical Engineering
dspace.entity.typePublication
unesp.campusUniversidade Estadual Paulista (Unesp), Instituto de Biociências, Botucatupt
unesp.departmentFísica e Biofísica - IBBpt

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