Publicação
Brain segmentation in head CT images
| Resumo: | Brain segmentation in head computed tomography scans is essential for the development of computer-aided diagnostic methods for identifying the brain diseases. In this paper we present a hybrid framework to brain segmentation which joints region-based information based on watershed transform with clustering techniques. A pre-processing step is used to reduce the spatial resolution without losing important image information. An initial partitioning of the image into primitive regions is set by applying a rainfalling watershed algorithm on the image gradient magnitude. This initial partition is the input to a computationally efficient region segmentation process which produces the final segmentation. We have applied our approach on several head CT images and the results reveal the robustness and accuracy of this method. |
|---|---|
| Autores principais: | Torres, Ana Sofia |
| Outros Autores: | Monteiro, Fernando C. |
| Assunto: | Brain segmentation Graph clustering Head CT images Watershed transform |
| Ano: | 2012 |
| País: | Portugal |
| Tipo de documento: | comunicação em conferência |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico de Bragança |
| Idioma: | inglês |
| Origem: | Biblioteca Digital do IPB |
| _version_ | 1867172779182260224 |
|---|---|
| author | Torres, Ana Sofia |
| author2 | Monteiro, Fernando C. |
| author2_role | author |
| author_facet | Torres, Ana Sofia Monteiro, Fernando C. |
| author_role | author |
| contributor_name_str_mv | Biblioteca Digital do IPB |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Torres, Ana Sofia\"},{\"Person.name\":\"Monteiro, Fernando C.\",\"Person.identifier.orcid\":\"0000-0002-1421-8006\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Biblioteca Digital do IPB |
| datacite.creators.creator.creatorName.fl_str_mv | Torres, Ana Sofia Monteiro, Fernando C. |
| datacite.date.Accepted.fl_str_mv | 2012-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2014-09-25T08:59:24Z |
| datacite.date.embargoed.fl_str_mv | 2014-09-25T08:59:24Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Brain segmentation Graph clustering Head CT images Watershed transform |
| datacite.titles.title.fl_str_mv | Brain segmentation in head CT images |
| dc.contributor.none.fl_str_mv | Biblioteca Digital do IPB |
| dc.creator.none.fl_str_mv | Torres, Ana Sofia Monteiro, Fernando C. |
| dc.date.Accepted.fl_str_mv | 2012-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2014-09-25T08:59:24Z |
| dc.date.embargoed.fl_str_mv | 2014-09-25T08:59:24Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10198/10584 |
| dc.language.none.fl_str_mv | eng |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | Brain segmentation Graph clustering Head CT images Watershed transform |
| dc.title.fl_str_mv | Brain segmentation in head CT images |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_5794 |
| description | Brain segmentation in head computed tomography scans is essential for the development of computer-aided diagnostic methods for identifying the brain diseases. In this paper we present a hybrid framework to brain segmentation which joints region-based information based on watershed transform with clustering techniques. A pre-processing step is used to reduce the spatial resolution without losing important image information. An initial partitioning of the image into primitive regions is set by applying a rainfalling watershed algorithm on the image gradient magnitude. This initial partition is the input to a computationally efficient region segmentation process which produces the final segmentation. We have applied our approach on several head CT images and the results reveal the robustness and accuracy of this method. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | conferencePaper |
| fulltext.url.fl_str_mv | https://bibliotecadigital.ipb.pt/bitstreams/a2446002-a01a-4efd-9c5c-618a44d28084/download |
| id | ipb_fa8fbade39e4feacbe8e2017967aa444 |
| identifier.url.fl_str_mv | http://hdl.handle.net/10198/10584 |
| instacron_str | ipb |
| institution | Instituto Politécnico de Bragança |
| instname_str | Instituto Politécnico de Bragança |
| language | eng |
| network_acronym_str | ipb |
| network_name_str | Biblioteca Digital do IPB |
| oai_identifier_str | oai:bibliotecadigital.ipb.pt:10198/10584 |
| organization_str_mv | urn:organizationAcronym:ipb |
| person_str_mv | Torres, Ana Sofia Monteiro, Fernando C. Monteiro, Fernando C. https://www.ciencia-id.pt/2019-BDBF-10E2 2019-BDBF-10E2 http://orcid.org/0000-0002-1421-8006 0000-0002-1421-8006 |
| publishDate | 2012 |
| reponame_str | Biblioteca Digital do IPB |
| repository_id_str | urn:repositoryAcronym:ipb |
| service_str_mv | urn:repositoryAcronym:ipb |
| spelling | engporBrain segmentation in head computed tomography scans is essential for the development of computer-aided diagnostic methods for identifying the brain diseases. In this paper we present a hybrid framework to brain segmentation which joints region-based information based on watershed transform with clustering techniques. A pre-processing step is used to reduce the spatial resolution without losing important image information. An initial partitioning of the image into primitive regions is set by applying a rainfalling watershed algorithm on the image gradient magnitude. This initial partition is the input to a computationally efficient region segmentation process which produces the final segmentation. We have applied our approach on several head CT images and the results reveal the robustness and accuracy of this method.application/pdfporBrain segmentation in head CT imagesTorres, Ana SofiaPersonalMonteiro, Fernando C.DSpacehttp://dspace.org/items/363b6c37-282c-4cd6-bb54-3c97cc700d78DSpacehttp://dspace.org/items/363b6c37-282c-4cd6-bb54-3c97cc700d78MonteiroFernando C.Ciência IDhttps://www.ciencia-id.pt2019-BDBF-10E2ORCIDhttp://orcid.org0000-0002-1421-8006Researcher IDhttps://www.researcherid.comH-9213-2016Scopus Author IDhttps://www.scopus.com8986162600HostingInstitutionOrganizationalBiblioteca Digital do IPBe-mailmailto:dspace@ipb.ptdspace@ipb.ptISBNIsPartOf978-989-8425-89-8DOIIsPartOf10.5220/00037947043404372014-09-25T08:59:24Z20122012-01-01T00:00:00ZHandlehttp://hdl.handle.net/10198/10584http://purl.org/coar/access_right/c_abf2open accessBrain segmentationGraph clusteringHead CT imagesWatershed transform449496 bytesother research producthttp://purl.org/coar/resource_type/c_5794conference paperhttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://bibliotecadigital.ipb.pt/bitstreams/a2446002-a01a-4efd-9c5c-618a44d28084/downloadInternational Conference on Bio-inspired Systems and Signal Processing434437Vilamoura - Portugal |
| spellingShingle | Brain segmentation in head CT images Torres, Ana Sofia Brain segmentation Graph clustering Head CT images Watershed transform |
| status | SINGLETON |
| subject.fl_str_mv | Brain segmentation Graph clustering Head CT images Watershed transform |
| title | Brain segmentation in head CT images |
| title_full | Brain segmentation in head CT images |
| title_fullStr | Brain segmentation in head CT images |
| title_full_unstemmed | Brain segmentation in head CT images |
| title_short | Brain segmentation in head CT images |
| title_sort | Brain segmentation in head CT images |
| topic | Brain segmentation Graph clustering Head CT images Watershed transform |
| topic_facet | Brain segmentation Graph clustering Head CT images Watershed transform |
| url | http://hdl.handle.net/10198/10584 |
| visible | 1 |