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Otimização de imagens de mamografia computadorizada

Authors: Alvarez, Matheus;

Otimização de imagens de mamografia computadorizada

Abstract

O propósito deste trabalho é apresentar uma metodologia de análise computacional de radiografias do fantoma de acreditação mamográfico (FAM) do colégio americano de radiologia (CAR) a ser utilizado em serviços de mamografia. Processamentos via transformada discreta de wavelet (TDW) são usados de maneira a realçar o contraste dos objetos teste a serem analisados, possibilitando condições automáticas da avaliação do desempenho de sistemas mamográficos. Os algoritmos desenvolvidos localizam a região do fantoma na radiografia de maneira totalmente automatizada, onde são aplicados processamentos via TDW, que realçam características geométricas e morfológicas do fantoma. Cada região da imagem é submetida a testes de reconhecimento de detalhes estruturais, visando a minimização de detecção de falsos positivos. Em seguida, parâmetros morfológicos e geométricos das imagens processadas são utilizados na quantificação do nível de qualidade final da imagem. Também foram investigados as possibilidades de otimizar a dose utilizada na obtenção de mamografias e o potencial de otimização dos algoritmos desenvolvidos. A análise das tabelas de contingência revelou uma associação significativa ( p < 0.001 ) para as avaliações de massas, fibras e microcalcificações, revelando um grau de concordância satisfatório entre algoritmos e radiologistas. As médias das diferenças para simuladores de massas, fibras e microcalcificações obtidas foram, respectivamente, -0,11±0,86, -0,01±0,82 e 0,14±0,88. Foi avaliado o potencial de diminuição de dose na obtenção da mamografia de uma mama padrão e um potencial de redução de dose de aproximadamente 50% da dose utilizada atualmente foi encontrado. A metodologia desenvolvida e validada pode ser utilizada na detecção de pequenas variações da...

The purpose of this paper is to present a methodology for computed analysis of the mammographic accreditation phantom (MAP) recommended by the American College of Radiology (ACR) radiographs. Wavelet enhancement by the discrete wavelet transform (DWT) are used in order to highlight the test objects to be analyzed. Enabling automatic conditions of evaluating the performance of mammographic systems. The algorithms presented here locate the region of the ACR MAP in the radiograph by a fully automatic process. DWT is used to enhance the contrast between the objects and the background this allows morphological operator to detect the test objects in each region. Then, Morphological and geometrical pparameters of the processed images are used to quantify the final level of image quality presented by the system. We also investigated the possibilities of optimizing the dose used in the acquisition of mammograms. Our analysis revealed a strong correlation (p<0.001) in the computed evaluation of the test objects and radiologists scores.The mean difference between the human and the computed score were -0.11±0.86, -0.01±0.82, 0.14±0.88. We have found a potential of dose reduction in approximated 50% of the currently radiation level without prejudicing the image quality level. The methodology were developed and validated to show that they can be used to detect small variations in the radiographs levels. Our... (Complete abstract click electronic access below)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Pós-graduação em Biologia Geral e Aplicada - IBB

Keywords

Wavelets (Matematica), Diagnóstico por imagem, Breast - Radiography, Mamas - Radiografia

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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