Applying enhancement filters in the pre-processing of images of lymphoma
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://iopscience.iop.org/article/10.1088/1742-6596/574/1/012122/meta http://hdl.handle.net/11449/128817 |
Resumo: | Lymphoma is a type of cancer that affects the immune system, and is classified as Hodgkin or non-Hodgkin. It is one of the ten types of cancer that are the most common on earth. Among all malignant neoplasms diagnosed in the world, lymphoma ranges from three to four percent of them. Our work presents a study of some filters devoted to enhancing images of lymphoma at the pre-processing step. Here the enhancement is useful for removing noise from the digital images. We have analysed the noise caused by different sources like room vibration, scraps and defocusing, and in the following classes of lymphoma: follicular, mantle cell and B-cell chronic lymphocytic leukemia. The filters Gaussian, Median and Mean-Shift were applied to different colour models (RGB, Lab and HSV). Afterwards, we performed a quantitative analysis of the images by means of the Structural Similarity Index. This was done in order to evaluate the similarity between the images. In all cases we have obtained a certainty of at least 75%, which rises to 99% if one considers only HSV. Namely, we have concluded that HSV is an important choice of colour model at pre-processing histological images of lymphoma, because in this case the resulting image will get the best enhancement. |
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Applying enhancement filters in the pre-processing of images of lymphomaLymphoma is a type of cancer that affects the immune system, and is classified as Hodgkin or non-Hodgkin. It is one of the ten types of cancer that are the most common on earth. Among all malignant neoplasms diagnosed in the world, lymphoma ranges from three to four percent of them. Our work presents a study of some filters devoted to enhancing images of lymphoma at the pre-processing step. Here the enhancement is useful for removing noise from the digital images. We have analysed the noise caused by different sources like room vibration, scraps and defocusing, and in the following classes of lymphoma: follicular, mantle cell and B-cell chronic lymphocytic leukemia. The filters Gaussian, Median and Mean-Shift were applied to different colour models (RGB, Lab and HSV). Afterwards, we performed a quantitative analysis of the images by means of the Structural Similarity Index. This was done in order to evaluate the similarity between the images. In all cases we have obtained a certainty of at least 75%, which rises to 99% if one considers only HSV. Namely, we have concluded that HSV is an important choice of colour model at pre-processing histological images of lymphoma, because in this case the resulting image will get the best enhancement.Universidade Federal de Uberlândia, Faculdade de Engenharia MecânicaUniversidade Federal de Uberlândia, Faculdade de Ciência da ComputaçãoUniversidade Federal do ABC, Centro de Matemática, Ciência da Computação e CogniçãoUniversidade Estadual Paulista, Departamento de Ciência da Computação e Estatística, Instituto de Biociências, Letras e Ciências Exatas de São José do Rio PretoIop Publishing LtdUniversidade Federal de Uberlândia (UFU)Universidade Estadual Paulista (Unesp)Universidade Federal do ABC (UFABC)Silva, Sérgio HenriqueNascimento, Marcelo Zanchetta doNeves, Leandro Alves [UNESP]Batista, Valério Ramos2015-10-21T13:13:59Z2015-10-21T13:13:59Z2015-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject1-4application/pdfhttp://iopscience.iop.org/article/10.1088/1742-6596/574/1/012122/meta3rd International Conference On Mathematical Modeling In Physical Sciences (IC-MSQUARE 2014). Bristol: Iop Publishing Ltd, v. 574, p. 1-4, 2015.1742-6588http://hdl.handle.net/11449/12881710.1088/1742-6596/574/1/012122WOS:000352595600122WOS000352595600122.pdf2139053814879312Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng3rd International Conference On Mathematical Modeling In Physical Sciences (IC-MSQUARE 2014)0,241info:eu-repo/semantics/openAccess2023-10-30T06:12:23Zoai:repositorio.unesp.br:11449/128817Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:28:34.599528Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Applying enhancement filters in the pre-processing of images of lymphoma |
title |
Applying enhancement filters in the pre-processing of images of lymphoma |
spellingShingle |
Applying enhancement filters in the pre-processing of images of lymphoma Silva, Sérgio Henrique |
title_short |
Applying enhancement filters in the pre-processing of images of lymphoma |
title_full |
Applying enhancement filters in the pre-processing of images of lymphoma |
title_fullStr |
Applying enhancement filters in the pre-processing of images of lymphoma |
title_full_unstemmed |
Applying enhancement filters in the pre-processing of images of lymphoma |
title_sort |
Applying enhancement filters in the pre-processing of images of lymphoma |
author |
Silva, Sérgio Henrique |
author_facet |
Silva, Sérgio Henrique Nascimento, Marcelo Zanchetta do Neves, Leandro Alves [UNESP] Batista, Valério Ramos |
author_role |
author |
author2 |
Nascimento, Marcelo Zanchetta do Neves, Leandro Alves [UNESP] Batista, Valério Ramos |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade Federal de Uberlândia (UFU) Universidade Estadual Paulista (Unesp) Universidade Federal do ABC (UFABC) |
dc.contributor.author.fl_str_mv |
Silva, Sérgio Henrique Nascimento, Marcelo Zanchetta do Neves, Leandro Alves [UNESP] Batista, Valério Ramos |
description |
Lymphoma is a type of cancer that affects the immune system, and is classified as Hodgkin or non-Hodgkin. It is one of the ten types of cancer that are the most common on earth. Among all malignant neoplasms diagnosed in the world, lymphoma ranges from three to four percent of them. Our work presents a study of some filters devoted to enhancing images of lymphoma at the pre-processing step. Here the enhancement is useful for removing noise from the digital images. We have analysed the noise caused by different sources like room vibration, scraps and defocusing, and in the following classes of lymphoma: follicular, mantle cell and B-cell chronic lymphocytic leukemia. The filters Gaussian, Median and Mean-Shift were applied to different colour models (RGB, Lab and HSV). Afterwards, we performed a quantitative analysis of the images by means of the Structural Similarity Index. This was done in order to evaluate the similarity between the images. In all cases we have obtained a certainty of at least 75%, which rises to 99% if one considers only HSV. Namely, we have concluded that HSV is an important choice of colour model at pre-processing histological images of lymphoma, because in this case the resulting image will get the best enhancement. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-10-21T13:13:59Z 2015-10-21T13:13:59Z 2015-01-01 |
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://iopscience.iop.org/article/10.1088/1742-6596/574/1/012122/meta 3rd International Conference On Mathematical Modeling In Physical Sciences (IC-MSQUARE 2014). Bristol: Iop Publishing Ltd, v. 574, p. 1-4, 2015. 1742-6588 http://hdl.handle.net/11449/128817 10.1088/1742-6596/574/1/012122 WOS:000352595600122 WOS000352595600122.pdf 2139053814879312 |
url |
http://iopscience.iop.org/article/10.1088/1742-6596/574/1/012122/meta http://hdl.handle.net/11449/128817 |
identifier_str_mv |
3rd International Conference On Mathematical Modeling In Physical Sciences (IC-MSQUARE 2014). Bristol: Iop Publishing Ltd, v. 574, p. 1-4, 2015. 1742-6588 10.1088/1742-6596/574/1/012122 WOS:000352595600122 WOS000352595600122.pdf 2139053814879312 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
3rd International Conference On Mathematical Modeling In Physical Sciences (IC-MSQUARE 2014) 0,241 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
1-4 application/pdf |
dc.publisher.none.fl_str_mv |
Iop Publishing Ltd |
publisher.none.fl_str_mv |
Iop Publishing Ltd |
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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1808128658854903808 |