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dc.contributor.authorAlvarez, Matheus-
dc.contributor.authorPina, Diana Rodrigues de-
dc.contributor.authorGiacomini, Guilherme-
dc.contributor.authorRomeiro, Fernando Gomes-
dc.contributor.authorDuarte, Sergio Barbosa-
dc.contributor.authorYamashita, Seizo-
dc.contributor.authorArruda Miranda, Jose Ricardo de-
dc.contributor.authorOurselin, S.-
dc.contributor.authorStyner, M. A.-
dc.identifier.citationMedical Imaging 2014: Image Processing. Bellingham: Spie-int Soc Optical Engineering, v. 9034, 9 p., 2014.-
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.publisherSpie - Int Soc Optical Engineering-
dc.sourceWeb of Science-
dc.subjectmedical image segmentationen
dc.subjectmedical imagingen
dc.subjectcomputed tomographyen
dc.subjectimage processingen
dc.titleWavelets based Algorithm for the Evaluation of Enhanced Liver Areasen
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
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.rights.accessRightsAcesso restrito-
dc.relation.ispartofMedical Imaging 2014: Image Processing-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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