Wavelets based Algorithm for the Evaluation of Enhanced Liver Areas
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , , , , , , , |
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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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 |
|
_version_ |
1803649689914966016 |