Classification of microcalcifications on digital mammograms based of FPGA
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/10.1201/b15810-57 http://hdl.handle.net/11449/220631 |
Resumo: | Breast cancer is a disease that is the death cause of many women around the world [2] and the best way to treat this disease is by detecting it in its early stages and starting the treatment right away [6]. As computers can be used to manipulate images, one way to aid radiologists in breast cancer early diagnosis is by the detection and classification of microcalcifications on digital mammograms, small calcium accumulations [3] that can be the first sign of a tumor that cannot yet be detected by palpable exams. Michele Le Gal developed a classification scheme to aid radiologists to determine whether a breast tumor is malignant or not without the need for surgeries [5], reducing the need for therapies and recurrent treatment [6]. This classification scheme is based on the shape of microcalcifications, and Figure 1 shows samples from each type of microcalcification, while Table 1 shows the percentage of malignant cancer associated with each type of microcalcification. |
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Classification of microcalcifications on digital mammograms based of FPGABreast cancer is a disease that is the death cause of many women around the world [2] and the best way to treat this disease is by detecting it in its early stages and starting the treatment right away [6]. As computers can be used to manipulate images, one way to aid radiologists in breast cancer early diagnosis is by the detection and classification of microcalcifications on digital mammograms, small calcium accumulations [3] that can be the first sign of a tumor that cannot yet be detected by palpable exams. Michele Le Gal developed a classification scheme to aid radiologists to determine whether a breast tumor is malignant or not without the need for surgeries [5], reducing the need for therapies and recurrent treatment [6]. This classification scheme is based on the shape of microcalcifications, and Figure 1 shows samples from each type of microcalcification, while Table 1 shows the percentage of malignant cancer associated with each type of microcalcification.São Paulo State University Departamento de Engenharia ElétricaInstituto Federal de São PauloSão Paulo State University Departamento de Ciência de Computação e EstatísticaSão Paulo State University Departamento de Engenharia ElétricaSão Paulo State University Departamento de Ciência de Computação e EstatísticaUniversidade Estadual Paulista (UNESP)Instituto Federal de São PauloDócusse, T. A. [UNESP]da Silva, A. C.R. [UNESP]Pereira, A. S. [UNESP]Marranghello, N. [UNESP]2022-04-28T19:03:37Z2022-04-28T19:03:37Z2014-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject323-324http://dx.doi.org/10.1201/b15810-57Computational Vision and Medical Image Processing IV - Proceedings of Eccomas Thematic Conference on Computational Vision and Medical Image Processing, VIPIMAGE 2013, p. 323-324.http://hdl.handle.net/11449/22063110.1201/b15810-572-s2.0-84973138894Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengComputational Vision and Medical Image Processing IV - Proceedings of Eccomas Thematic Conference on Computational Vision and Medical Image Processing, VIPIMAGE 2013info:eu-repo/semantics/openAccess2022-04-28T19:03:37Zoai:repositorio.unesp.br:11449/220631Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462022-04-28T19:03:37Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Classification of microcalcifications on digital mammograms based of FPGA |
title |
Classification of microcalcifications on digital mammograms based of FPGA |
spellingShingle |
Classification of microcalcifications on digital mammograms based of FPGA Dócusse, T. A. [UNESP] |
title_short |
Classification of microcalcifications on digital mammograms based of FPGA |
title_full |
Classification of microcalcifications on digital mammograms based of FPGA |
title_fullStr |
Classification of microcalcifications on digital mammograms based of FPGA |
title_full_unstemmed |
Classification of microcalcifications on digital mammograms based of FPGA |
title_sort |
Classification of microcalcifications on digital mammograms based of FPGA |
author |
Dócusse, T. A. [UNESP] |
author_facet |
Dócusse, T. A. [UNESP] da Silva, A. C.R. [UNESP] Pereira, A. S. [UNESP] Marranghello, N. [UNESP] |
author_role |
author |
author2 |
da Silva, A. C.R. [UNESP] Pereira, A. S. [UNESP] Marranghello, N. [UNESP] |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) Instituto Federal de São Paulo |
dc.contributor.author.fl_str_mv |
Dócusse, T. A. [UNESP] da Silva, A. C.R. [UNESP] Pereira, A. S. [UNESP] Marranghello, N. [UNESP] |
description |
Breast cancer is a disease that is the death cause of many women around the world [2] and the best way to treat this disease is by detecting it in its early stages and starting the treatment right away [6]. As computers can be used to manipulate images, one way to aid radiologists in breast cancer early diagnosis is by the detection and classification of microcalcifications on digital mammograms, small calcium accumulations [3] that can be the first sign of a tumor that cannot yet be detected by palpable exams. Michele Le Gal developed a classification scheme to aid radiologists to determine whether a breast tumor is malignant or not without the need for surgeries [5], reducing the need for therapies and recurrent treatment [6]. This classification scheme is based on the shape of microcalcifications, and Figure 1 shows samples from each type of microcalcification, while Table 1 shows the percentage of malignant cancer associated with each type of microcalcification. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-01-01 2022-04-28T19:03:37Z 2022-04-28T19:03:37Z |
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/10.1201/b15810-57 Computational Vision and Medical Image Processing IV - Proceedings of Eccomas Thematic Conference on Computational Vision and Medical Image Processing, VIPIMAGE 2013, p. 323-324. http://hdl.handle.net/11449/220631 10.1201/b15810-57 2-s2.0-84973138894 |
url |
http://dx.doi.org/10.1201/b15810-57 http://hdl.handle.net/11449/220631 |
identifier_str_mv |
Computational Vision and Medical Image Processing IV - Proceedings of Eccomas Thematic Conference on Computational Vision and Medical Image Processing, VIPIMAGE 2013, p. 323-324. 10.1201/b15810-57 2-s2.0-84973138894 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Computational Vision and Medical Image Processing IV - Proceedings of Eccomas Thematic Conference on Computational Vision and Medical Image Processing, VIPIMAGE 2013 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
323-324 |
dc.source.none.fl_str_mv |
Scopus 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_ |
1799964612923228160 |