Abstract
This work aimes at the development of mathematical tools and information technology elements for automated extraction and characterization of objects in striatum section images. The latter are used to construct a Parkinson’s disease model at a preclinical stage. Experimental applications of the developed technique have confirmed its high efficiency and suitability for automated processing and analysis of brain section images (a 200 times increase in productivity and a 10 times decrease in the amount of animals and expendables).
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Gurevich, I., Myagkov, A., Yashina, V. (2012). A New Image-Mining Technique for Automation of Parkinson’s Disease Research. In: Köthe, U., Montanvert, A., Soille, P. (eds) Applications of Discrete Geometry and Mathematical Morphology. WADGMM 2010. Lecture Notes in Computer Science, vol 7346. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32313-3_11
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DOI: https://doi.org/10.1007/978-3-642-32313-3_11
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