Wavelets based Algorithm for the Evaluation of Enhanced Liver Areas

Detalhes bibliográficos
Autor(a) principal: Alvarez, Matheus [UNESP]
Data de Publicação: 2014
Outros Autores: Pina, Diana Rodrigues de, Giacomini, Guilherme [UNESP], Romeiro, Fernando Gomes, Duarte, Sergio Barbosa, Yamashita, Seizo, Arruda Miranda, Jose Ricardo de [UNESP], Ourselin, S., Styner, M. A.
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1117/12.2043822
http://hdl.handle.net/11449/112609
Resumo: Hepatocellular 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.
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spelling Wavelets based Algorithm for the Evaluation of Enhanced Liver AreasHCCmedical image segmentationlivermedical imagingcomputed tomographyimage processingHepatocellular 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.Univ Estadual Paulista UNESP, Botucatu Biosci Inst, Dept Phys & Biophys, BR-18618000 Sao Paulo, BrazilUniv Estadual Paulista UNESP, Botucatu Biosci Inst, Dept Phys & Biophys, BR-18618000 Sao Paulo, BrazilSpie - Int Soc Optical EngineeringUniversidade Estadual Paulista (Unesp)Alvarez, Matheus [UNESP]Pina, Diana Rodrigues deGiacomini, Guilherme [UNESP]Romeiro, Fernando GomesDuarte, Sergio BarbosaYamashita, SeizoArruda Miranda, Jose Ricardo de [UNESP]Ourselin, S.Styner, M. A.2014-12-03T13:10:52Z2014-12-03T13:10:52Z2014-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject9application/pdfhttp://dx.doi.org/10.1117/12.2043822Medical Imaging 2014: Image Processing. Bellingham: Spie-int Soc Optical Engineering, v. 9034, 9 p., 2014.0277-786Xhttp://hdl.handle.net/11449/11260910.1117/12.2043822WOS:000338543300155WOS000338543300155.pdfWeb of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengMedical Imaging 2014: Image Processinginfo:eu-repo/semantics/openAccess2023-11-12T06:12:12Zoai:repositorio.unesp.br:11449/112609Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462023-11-12T06:12:12Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Wavelets based Algorithm for the Evaluation of Enhanced Liver Areas
title Wavelets based Algorithm for the Evaluation of Enhanced Liver Areas
spellingShingle Wavelets based Algorithm for the Evaluation of Enhanced Liver Areas
Alvarez, Matheus [UNESP]
HCC
medical image segmentation
liver
medical imaging
computed tomography
image processing
title_short Wavelets based Algorithm for the Evaluation of Enhanced Liver Areas
title_full Wavelets based Algorithm for the Evaluation of Enhanced Liver Areas
title_fullStr Wavelets based Algorithm for the Evaluation of Enhanced Liver Areas
title_full_unstemmed Wavelets based Algorithm for the Evaluation of Enhanced Liver Areas
title_sort Wavelets based Algorithm for the Evaluation of Enhanced Liver Areas
author Alvarez, Matheus [UNESP]
author_facet Alvarez, Matheus [UNESP]
Pina, Diana Rodrigues de
Giacomini, Guilherme [UNESP]
Romeiro, Fernando Gomes
Duarte, Sergio Barbosa
Yamashita, Seizo
Arruda Miranda, Jose Ricardo de [UNESP]
Ourselin, S.
Styner, M. A.
author_role author
author2 Pina, Diana Rodrigues de
Giacomini, Guilherme [UNESP]
Romeiro, Fernando Gomes
Duarte, Sergio Barbosa
Yamashita, Seizo
Arruda Miranda, Jose Ricardo de [UNESP]
Ourselin, S.
Styner, M. A.
author2_role author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Alvarez, Matheus [UNESP]
Pina, Diana Rodrigues de
Giacomini, Guilherme [UNESP]
Romeiro, Fernando Gomes
Duarte, Sergio Barbosa
Yamashita, Seizo
Arruda Miranda, Jose Ricardo de [UNESP]
Ourselin, S.
Styner, M. A.
dc.subject.por.fl_str_mv HCC
medical image segmentation
liver
medical imaging
computed tomography
image processing
topic HCC
medical image segmentation
liver
medical imaging
computed tomography
image processing
description Hepatocellular 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.
publishDate 2014
dc.date.none.fl_str_mv 2014-12-03T13:10:52Z
2014-12-03T13:10:52Z
2014-01-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1117/12.2043822
Medical Imaging 2014: Image Processing. Bellingham: Spie-int Soc Optical Engineering, v. 9034, 9 p., 2014.
0277-786X
http://hdl.handle.net/11449/112609
10.1117/12.2043822
WOS:000338543300155
WOS000338543300155.pdf
url http://dx.doi.org/10.1117/12.2043822
http://hdl.handle.net/11449/112609
identifier_str_mv Medical Imaging 2014: Image Processing. Bellingham: Spie-int Soc Optical Engineering, v. 9034, 9 p., 2014.
0277-786X
10.1117/12.2043822
WOS:000338543300155
WOS000338543300155.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Medical Imaging 2014: Image Processing
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 9
application/pdf
dc.publisher.none.fl_str_mv Spie - Int Soc Optical Engineering
publisher.none.fl_str_mv Spie - Int Soc Optical Engineering
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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