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A plants analysis neural network by Siberian scientists will help automate diagnosis of cancer

Scientists of the Siberian Branch of the Russian Academy of Sciences are developing a neural network for the universal processing of microscopic images — the tool will automate analysis of microscopic images in general and the diagnosis of oncological diseases in particular, and it will also help get useful extracts from plant raw materials in an optimal way, said Igor Lomovsky, the acting head the Laboratory of Solid State Chemistry at the Institute of Solid State Chemistry and Mechanochemistry (ISSC) of the SB RAS.
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«We are studying how to properly prepare plant raw materials for extraction processes — i.e. the separation of useful substances. In order to understand these processes, it is necessary to analyse the microphotographs of ultrathin sections of particles, and it is for this purpose the neural network is created. Additionally, automatic processing of photographic images of biological systems will make it possible to reduce by half the load of physicians who are engaged in diagnostics of neoplasms by cells' cuts — the neural network will be able to distinguish automatically a normal wall from a tumour. The information system will also help automate a huge number of microscopic studies: most of them are still done manually,» Lomovsky explained.

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