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Automatic Detection of Defective Zebrafish Embryos via Shape Analysis

Zhao, Haifeng; Zhou, Jun; Robles-Kelly, Antonio; Lu, Jianfeng; Yang, Jing-Yu

Description

In this paper, we present a graph-based approach to automatically detect defective zebrafish embryos. Here, the zebrafish is segmented from the background using a texture descriptor and morphological operations. In this way, we can represent the embryo shape as a graph, for which we propose a vectorisation method to recover clique histogram vectors for classification. The clique histogram represents the distribution of one vertex with respect to its adjacent vertices. This treatment permits the...[Show more]

CollectionsANU Research Publications
Date published: 2009
Type: Conference paper
URI: http://hdl.handle.net/1885/56923
Source: Proceedings of the Digital Image Computing: Techniques and Applications (DICTA 2009)
DOI: 10.1109/DICTA.2009.76

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