@CONFERENCE\{IMM2006-04676,
    author       = "M. F. Hansen and R. Larsen and B. Ersb{\o}ll and L. B. Christensen",
    title        = "Coupled Shape Model Segmentation in Pig Carcasses",
    year         = "2006",
    booktitle    = "{ICPR} 2006, {IEEE} International Conference on Pattern Recognition 2006",
    volume       = "",
    series       = "",
    editor       = "",
    publisher    = "",
    organization = "",
    address      = "",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/4676-full.html",
    abstract     = "In this paper we are concerned with multi-object segmentation.
For each object we will train a level set function
based shape prior from a sample set of outlines. The outlines
are aligned in a multi-resolution scheme wrt. an Euclidean
similarity transformation in order to maximize the
overlap of the interior between all pairs of outlines. Then
the outlines are converted to level set functions. A shape
model is constructed from the mean level set and the first
few principal variations. We combine the prior model with
an observation model based on the Chan-Vese functional
assuming constant intensity levels inside the outline as well
as in a narrow band outside the outline. The maximum a
posteriori estimate of the outline is found by gradient descent
optimization. In order to segment a group of mutually
dependent objects we propose 2 procedures, 1) the objects
are found sequentially by conditioning the initialization of
the next search from already found objects; 2) all objects
are found simultaneously and a repelling force is introduced
in order to avoid overlap between outlines in the solution.
The methods are applied to segmentation of cross sections
of muscles in slices of {CT} scans of pig backs for quality assessment of bacon slices."
}