Pattern recognition in mammographic images used by the residents in mammography

Página do item simplificado
dc.contributor.authorDos Santos J.B.
dc.contributor.authorDe Almeida J.R.
dc.contributor.authorSilva L.A.
dc.date.accessioned2024-03-13T01:06:14Z
dc.date.available2024-03-13T01:06:14Z
dc.date.issued2013
dc.description.abstractThis paper presents a computational strategy for content based image retrieval (CBIR-Content-Based Image Retrieval), considering the similarity in relation to an image already selected. The identification of similarity is obtained by feature extraction, using the technique of wavelet combined with Hu moments. The classification of mammographic is performed using Artificial Neural Networks, through the classifier Self-Organizing Map (SOM). The proposed method is tested with a database of the Laboratory of Medical Image Classification (QUALIM) Department of Diagnostic Imaging, Federal University of São Paulo (UNIFESP). © 2013 IEEE.
dc.identifier.doi10.1109/ICCMA.2013.6506175
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/36704
dc.relation.ispartofInternational Conference on Computer Medical Applications, ICCMA 2013
dc.rightsAcesso Restrito
dc.subject.otherlanguageCBIR
dc.subject.otherlanguageData Mining
dc.subject.otherlanguageDigital Image Processing
dc.subject.otherlanguagePattern Recognition
dc.subject.otherlanguageSOM
dc.titlePattern recognition in mammographic images used by the residents in mammography
dc.typeArtigo de evento
local.scopus.citations2
local.scopus.eid2-s2.0-84877824947
local.scopus.subjectCBIR
local.scopus.subjectComputational strategy
local.scopus.subjectContent-Based Image Retrieval
local.scopus.subjectContents-based image retrievals
local.scopus.subjectFeatures extraction
local.scopus.subjectHu moments
local.scopus.subjectMammographic
local.scopus.subjectMammographic images
local.scopus.subjectMedical image classification
local.scopus.subjectSelf-organizing-maps
local.scopus.updated2024-05-01
local.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84877824947&origin=inward
Arquivos
Coleções
Artigo de evento