Motion artifact and background noise suppression on optical microangiography frames using a naïve Bayes mask.
Appl Opt
; 53(19): 4164-71, 2014 Jul 01.
Article
em En
| MEDLINE
| ID: mdl-25089975
ABSTRACT
Optical coherence tomography (OCT) is a technique that allows for the three-dimensional (3D) imaging of small volumes of tissue (a few millimeters) with high resolution (â¼10 µm). Optical microangiography (OMAG) is a method of processing OCT data, which allows for the extraction of the tissue vasculature with capillary resolution from the OCT images. Cross-sectional B-frame OMAG images present the location of the patent blood vessels; however, the signal-to-noise-ratio of these images can be affected by several factors such as the quality of the OCT system and the tissue motion artifact. This background noise can appear in the en face projection view image. In this work we propose to develop a binary mask that can be applied on the cross-sectional B-frame OMAG images, which will reduce the background noise while leaving the signal from the blood vessels intact. The mask is created by using a naïve Bayes (NB) classification algorithm trained with a gold standard image which is manually segmented by an expert. The masked OMAG images present better contrast for binarizing the image and quantifying the result without the influence of noise. The results are compared with a previously developed frequency rejection filter (FRF) method which is applied on the en face projection view image. It is demonstrated that both the NB and FRF methods provide similar vessel length fractions. The advantage of the NB method is that the results are applicable in 3D and that its use is not limited to periodic motion artifacts.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Inteligência Artificial
/
Angiografia
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Interpretação de Imagem Assistida por Computador
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Aumento da Imagem
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Artefatos
/
Tomografia de Coerência Óptica
Tipo de estudo:
Diagnostic_studies
Idioma:
En
Revista:
Appl Opt
Ano de publicação:
2014
Tipo de documento:
Article