Skull Segmentation and Reconstruction From Newborn CT Images Using Coupled Level Sets.
IEEE J Biomed Health Inform
; 20(2): 563-73, 2016 Mar.
Article
en En
| MEDLINE
| ID: mdl-25667361
ABSTRACT
This study presents a new approach for segmentation and reconstruction of newborn's skull including bones, fontanels, and sutures from computed tomography (CT) images. The segmentation approach relies on propagation of a pair of interacting smooth surfaces based on geodesic active regions. These surfaces evolve in opposite directions; the exterior surface moves inward while the interior one moves in outward direction. The moving surfaces are forced to stop when arriving at the outer or the inner surface of the cranial bones using edge information. Since fontanels and sutures are not directly detectable in CT images, this method imposes specific propagation constraints for coupled interfaces to prevent the moving surfaces from intersecting each other and penetrating into the opposite region. Finally, an algorithm for level set initialization is introduced which enforces the evolving surfaces to conform to the shape of the head. The proposed method was evaluated using 18 neonatal CT images. The segmentation results achieved by the suggested method have been compared with manual segmentations by two different raters, performed to establish a reliable reference. The comparison of the two segmentation results using the Dice similarity coefficient and modified Hausdorff distance shows that the proposed approach provides satisfactory results.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Cráneo
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Tomografía Computarizada por Rayos X
/
Imagenología Tridimensional
Límite:
Humans
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Newborn
Idioma:
En
Revista:
IEEE J Biomed Health Inform
Año:
2016
Tipo del documento:
Article
Pais de publicación:
EEUU
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ESTADOS UNIDOS
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ESTADOS UNIDOS DA AMERICA
/
EUA
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UNITED STATES
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UNITED STATES OF AMERICA
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US
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USA