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 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.
Arias
Pablo
P
Instituto de Ingeniería Eléctrica, Universidad de la República, Montevideo 11300, Uruguay. parias@fing.edu.uy
Pini
Alejandro
A
Sanguinetti
Gonzalo
G
Sprechmann
Pablo
P
Cancela
Pablo
P
Fernández
Alicia
A
Gómez
Alvaro
A
Randall
Gregory
G
D000465:Algorithms; D019412:Anatomy, Cross-Sectional / Q000379:methods*; D000818:Animals; D001185:Artificial Intelligence; D002417:Cattle; D005504:Food Analysis / Q000379:methods*; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008460:Meat; D018482:Muscle, Skeletal / Q000000981:diagnostic imaging*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012272:Ribs / Q000000981:diagnostic imaging; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014463:Ultrasonography / Q000379:methods*