Ultrasound image segmentation with shape priors : application to automatic cattle rib-eye area estimation
Automatic ultrasound (US) image segmentation is a difficult task due to the quantity of noise present in the images and the lack of information in several zones produced by the acquisition conditions. In this paper, we propose a method that combines shape priors and image information to achieve this...
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| Autor principal: | |
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| Otros Autores: | , , , , , , |
| Formato: | article |
| Lenguaje: | inglés |
| Publicado: |
2007
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/20.500.12008/38758 |
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| Sumario: | Automatic ultrasound (US) image segmentation is a difficult task due to the quantity of noise present in the images and the lack of information in several zones produced by the acquisition conditions. In this paper, we propose a method that combines shape priors and image information to achieve this task. In particular, we introduce knowledge about the rib-eye shape using a set of images manually segmented by experts. A method is proposed for the automatic segmentation of new samples in which a closed curve is fitted taking into account both the US image information and the geodesic distance between the evolving curve and the estimated mean rib-eye shape in a shape space. This method can be used to solve similar problems that arise when dealing with US images in other fields. The method was successfully tested over a database composed of 610 US images, for which we have the manual segmentations of two experts. |
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