In:
Journal of the Royal Statistical Society Series C: Applied Statistics, Oxford University Press (OUP), Vol. 51, No. 2 ( 2002-05-01), p. 209-221
Abstract:
We seek a computationally fast method for solving a difficult image segmentation problem: the positioning of boundaries on medical scanner images to delineate tissues of interest. We formulate a Bayesian model for image boundaries such that the maximum a posterioriestimator is obtainable very efficiently by dynamic programming. The prior model for the boundary is a biased random walk and the likelihood is based on a border appearance model, with parameter values obtained from training images. The method is applied successfully to the segmentation of ultrasound images and X-ray computed tomographs of sheep, for application in sheep breeding programmes.
Type of Medium:
Online Resource
ISSN:
0035-9254
,
1467-9876
DOI:
10.1111/1467-9876.00264
Language:
English
Publisher:
Oxford University Press (OUP)
Publication Date:
2002
detail.hit.zdb_id:
204797-4
detail.hit.zdb_id:
1482300-7
detail.hit.zdb_id:
1476894-X
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