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Published on: July 28, 2016
An imaging workflow for characterizing phenotypical change in large histological mouse model datasets
Kishore Mosaliganti1, Tony Pan, Randall Ridgway
1Department of Biomedical Informatics, The Ohio State University, 3190 Graves Hall, 333 West 10th Avenue, Columbus, OH 43210, USA.
Motivation:
This paper presents a workflow designed to quantitatively characterize the 3D structural attributes of macroscopic tissue specimens acquired at a micron level resolution using light microscopy. The specific application is a study of the morphological change in a mouse placenta induced by knocking out the retinoblastoma gene.
Result:
This workflow includes four major components: (i) serial section image acquisition, (ii) image preprocessing, (iii) image analysis involving 2D pair-wise registration, 2D segmentation and 3D reconstruction, and (iv) visualization and quantification of phenotyping parameters. Several new algorithms have been developed within each workflow component. The results confirm the hypotheses that (i) the volume of labyrinth tissue decreases in mutant mice with the retinoblastoma (Rb) gene knockout and (ii) there is more interdigitation at the surface between the labyrinth and spongiotrophoblast tissues in mutant placenta. Additional confidence stem from agreement in the 3D visualization and the quantitative results generated.
Availability:
The source code is available upon request.
