Detection of architectural distortion in prior screening mammograms using Gabor filters, phase portraits, fractal dimension, and texture analysis

Página do item simplificado
dc.contributor.authorRangayyan, Rangaraj M.
dc.contributor.authorPrajna, Shormistha
dc.contributor.authorFABIO JOSE AYRES
dc.contributor.authorDesautels, J. E. Leo
dc.creatorRangayyan, Rangaraj M.
dc.creatorPrajna, Shormistha
dc.creatorDesautels, J. E. Leo
dc.date.accessioned2024-11-11T19:21:26Z
dc.date.available2024-11-11T19:21:26Z
dc.date.issued2008
dc.description.abstractObjective Mammography is a widely used screening tool for the early detection of breast cancer. One of the commonly missed signs of breast cancer is architectural distortion. The purpose of this study is to explore the application of fractal analysis and texture measures for the detection of architectural distortion in screening mammograms taken prior to the detection of breast cancer. Materials and methods A method based on Gabor filters and phase portrait analysis was used to detect initial candidates for sites of architectural distortion. A total of 386 regions of interest (ROIs) were automatically obtained from 14 “prior mammograms”, including 21 ROIs related to architectural distortion. From the corresponding set of 14 “detection mammograms”, 398 ROIs were obtained, including 18 related to breast cancer. For each ROI, the fractal dimension and Haralick’s texture features were computed. The fractal dimension of the ROIs was calculated using the circular average power spectrum technique. Results The average fractal dimension of the normal (false-positive) ROIs was significantly higher than that of the ROIs with architectural distortion (p = 0.006). For the “prior mammograms”, the best receiver operating characteristics (ROC) performance achieved, in terms of the area under the ROC curve, was 0.80 with a Bayesian classifier using four features including fractal dimension, entropy, sum entropy, and inverse difference moment. Analysis of the performance of the methods with free-response receiver operating characteristics indicated a sensitivity of 0.79 at 8.4 false positives per image in the detection of sites of architectural distortion in the “prior mammograms”. Conclusion Fractal dimension offers a promising way to detect the presence of architectural distortion in prior mammograms.pt
dc.formatDigital
dc.format.extentp. 347 – 361
dc.identifier.doi10.1007/s11548-007-0143-z
dc.identifier.urihttps://repositorio.insper.edu.br/handle/11224/7211
dc.language.isoInglês
dc.relation.ispartofInt J CARS
dc.subjectArchitectural distortionen
dc.subjectBreast canceren
dc.subjectPrior screening mammogramsen
dc.subjectScreen-detected breast canceren
dc.subjectFractal dimensionen
dc.subjectTexture analysisen
dc.subjectGabor filtersen
dc.subjectPhase portraitsen
dc.titleDetection of architectural distortion in prior screening mammograms using Gabor filters, phase portraits, fractal dimension, and texture analysis
dc.typejournal article
dspace.entity.typePublication
local.identifier.sourceUrihttps://link.springer.com/article/10.1007/s11548-007-0143-z#citeas
local.publisher.countryNão Informado
local.subject.cnpqCIENCIAS DA SAUDE::MEDICINA::RADIOLOGIA MEDICA
local.subject.cnpqCIENCIAS DA SAUDE::MEDICINA::CLINICA MEDICA::CANCEROLOGIA
local.subject.cnpqENGENHARIAS::ENGENHARIA BIOMEDICA
local.subject.cnpqENGENHARIAS::ENGENHARIA ELETRICA
local.subject.cnpqCIENCIAS EXATAS E DA TERRA::MATEMATICA::MATEMATICA APLICADA
local.typeArtigo Científico
publicationvolume.volumeNumber2
relation.isAuthorOfPublication37971022-7c69-4e93-9186-4c9431a1f95c
relation.isAuthorOfPublication.latestForDiscovery37971022-7c69-4e93-9186-4c9431a1f95c
Arquivos
Pacote Original
Agora exibindo 1 - 2 de 2
Imagem de Miniatura
Nome:
Primeira_Pagina_Artigo_2010_Detection_of_the_optic_nerve_head_in_fundus_images_of_the_retina_with_gabor_filters_and_phase_portrait_analysis_TC.pdf
Tamanho:
64 KB
Formato:
Adobe Portable Document Format
Baixar
N/D
Nome:
ACESSO~4.PDF
Tamanho:
576.24 KB
Formato:
Adobe Portable Document Format
Baixar
Licença do Pacote
Agora exibindo 1 - 1 de 1
N/D
Nome:
license.txt
Tamanho:
236 B
Formato:
Item-specific license agreed upon to submission
Descrição:
Baixar
Coleções
Coleção de Artigos Acadêmicos