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Ultrasound Image Segmentation using Stochastic Templates
C. A. Glasbey
; Biomathematics and Statistics Scotland, JCMB, King's Buildings, Edinburgh EH9 3JZ, Scotland
Puni tekst: engleski, pdf (4 MB)
Glasbey, C.A. (1998). Ultrasound Image Segmentation using Stochastic Templates. Journal of computing and information technology, 6(2), 107-116. Preuzeto s https://hrcak.srce.hr/150228
Point distribution models (PDMs) are incorporated into Bayesian image analysis, thus combining two approaches to the fitting of stochastic templates. Manually segmented images are used to identify both a PDM and a likelihood function, leading to a posterior distribution from which inferences can be drawn. The methodology 1s explored and illustrated using 144 ultrasound images of sheep. A pseudo-likelihood is found to give better results than a likelihood based on the distribution of pixel values in the training images. Estimates of sheep fat and muscle depths are shown to be comparable in accuracy with manual interpretation of images.
Bayesian methods; Likelihood; Point distribution models
Hrčak ID: 150228
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