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Lookup NU author(s): Dr Telmo Amaral,
Professor Ilias Kyriazakis
This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by Institute of Electrical and Electronics Engineers, 2016.
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The segmentation of 2D images of 3D non-rigid objects into their constituent parts can pose challenging problems, such as missing and occluded parts, weak constraints over the spatial arrangement of parts, and variance in form and appearance. These problems have been addressed via segmentation methods that incorporate spatial context information, such as the auto-context technique. In this paper, we address for the first time the problem of segmenting multiple organs in images of pig offal, a challenging image analysis task that constitutes an essential step towards automated screening at abattoir for signs of sub-clinical diseases. We applied auto-context segmentation to a large data set of images and explored the effect of complementing conventional context features with integral features suited to our application.
Author(s): Amaral T, Kyriazakis I, McKenna SJ, Plötz T
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: IEEE 13th International Symposium on Biomedical Imaging
Year of Conference: 2016
Online publication date: 13/04/2016
Acceptance date: 22/12/2015
Date deposited: 24/03/2016
Publisher: Institute of Electrical and Electronics Engineers
Library holdings: Search Newcastle University Library for this item