Automatic segmentation of the cerebellum of fetuses on 3D ultrasound images, using a 3D Point Distribution Model.
Annu Int Conf IEEE Eng Med Biol Soc
; 2010: 4731-4, 2010.
Article
em En
| MEDLINE
| ID: mdl-21096244
ABSTRACT
Analysis of fetal biometric parameters on ultrasound images is widely performed and it is essential to estimate the gestational age, as well as the fetal growth pattern. The use of three dimensional ultrasound (3D US) is preferred over other tomographic modalities such as CT or MRI, due to its inherent safety and availability. However, the image quality of 3D US is not as good as MRI and therefore there is little work on the automatic segmentation of anatomic structures in 3D US of fetal brains. In this work we present preliminary results of the development of a 3D Point Distribution Model (PDM), for automatic segmentation, of the cerebellum in 3D US of the fetal brain. The model is adjusted to a fetal 3D ultrasound, using a genetic algorithm which optimizes a model fitting function. Preliminary results show that the approach reported is able to automatically segment the cerebellum in 3D ultrasounds of fetal brains.
Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Algoritmos
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Reconhecimento Automatizado de Padrão
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Interpretação de Imagem Assistida por Computador
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Cerebelo
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Ultrassonografia Pré-Natal
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Imageamento Tridimensional
Tipo de estudo:
Diagnostic_studies
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Prognostic_studies
Limite:
Female
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Humans
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Male
Idioma:
En
Revista:
Annu Int Conf IEEE Eng Med Biol Soc
Ano de publicação:
2010
Tipo de documento:
Article
País de afiliação:
México