Adaptation of mouse brain gene expression data for further Statistical Parametrical Mapping analysisстатья

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Дата последнего поиска статьи во внешних источниках: 28 мая 2015 г.

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[1] Adaptation of mouse brain gene expression data for further statistical parametrical mapping analysis / A. Osokin, A. Lebedev, D. Vetrov et al. // Proceedings of the 19th International Conference on Computer Graphics and Vision GraphiCon'2009. — GraphiCon. — MAKS Press Moscow, Russia, 2009. — P. 42–48. The paper describes a method for fully automatic 3D-reconstruction of mouse brain voxel model from a sequence of coronal 2D slices for statistical analysis of gene expression. Two images of each brain slice with different stains are used. The first stain highlights the histology of brain, which is used for slice matching. The second stain highlights the level of gene expression. The algorithm proceeds as follows. First, images are preprocessed to suppress image noise and equalize image brightness. Second we estimate the level of gene expression in each slice using the second stain. Then we construct 3D-model of the brain using the first stain. To do this all images are aligned via rigid-body transformations. After alignment neighboring slices are matched by estimation of non-linear deformations. As the distance between slices is significantly larger then image resolution we add intermediate virtual slices using morphing algorithm. Gene expression level is interpolated in identical way. The obtained 3D-model with the information about gene expression can be used for gene expression analysis via Statistical Parametric Mapping (SPM) package. The proposed method for 3D-reconstruction has been tested on images from Allen Brain Atlas, which is available in electronic form.

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