Descripción
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We show a procedure for constructing a probabilistic atlas based on affine moment descriptors. It uses a normalization procedure over the labeled atlas. The proposed linear registration is defined by closed-form expressions involving only geometric moments. This procedure applies both to atlas construction as atlas-based segmentation. We model the likelihood term for each voxel and each label using parame\-tric or nonparametric distributions and the prior term is determined by applying the vote-rule. The probabilistic atlas is built with the variabili\-ty of our linear registration. We have two segmentation strategy: a) it applies the proposed affine registration to bring the target image into the coordinate frame of the atlas or b) the probabilistic atlas is non-rigidly aligning with the target image, where the probabilistic atlas is previously aligned to the target image with our affine registration. Finally, we adopt a graph cut - Bayesian framework for implementing the atlas-based segmentation. | |
Internacional
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Si |
Nombre congreso
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Computer Analysis of Images and Patterns - 14th International Conference, CAIP 2011 |
Tipo de participación
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960 |
Lugar del congreso
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Seville, Spain |
Revisores
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Si |
ISBN o ISSN
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978-3-642-23671-6 |
DOI
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10.1007/978-3-642-23672-3_18 |
Fecha inicio congreso
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29/08/2011 |
Fecha fin congreso
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31/08/2011 |
Desde la página
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144 |
Hasta la página
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151 |
Título de las actas
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COMPUTER ANALYSIS OF IMAGES AND PATTERNS Lecture Notes in Computer Science, 2011, Volume 6854/2011 |