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A Fast Binary Image Segmentation Algorithm and its Application to in Situ Hybridization Data

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4 Author(s)
Guanliang Liu ; Sch. of Comput. Sci., Nat. Univ. of Defense Technol., Changsha, China ; Zhigang Luo ; Bo Yuan ; Xiaotu Ma

High dimensional and high-resolution gene expression data generated by the in situ hybridization (ISH) technique provides biologists a powerful tool to study gene functions. Nevertheless, a major challenge in analyzing such data is how to efficiently retrieve genes showing certain spatial expression patterns and/or genes showing similar expression patterns as the query gene. The development of a fast image segmentation algorithm and an effective statistical scoring method is useful to address the above question. In this paper we propose a fast binary image segmentation algorithm, which can efficiently detect the spatially restricted expression regions of a gene and/or co-expression regions between genes. A naive permutation approach is applied to assess the statistical significance of the detected regions. Our method is expected to drive ISH data analysis toward a more systematic and objective direction.

Published in:

Biomedical Engineering and Informatics, 2009. BMEI '09. 2nd International Conference on

Date of Conference:

17-19 Oct. 2009