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Modern Automated Microscopy Systems in Oncology

In the article, the authors investigated modern automated microscopy systems used in oncology and analyzed recent methods of image processing at different levels of computer vision. The researchers described a class of biomedical images, such as cytological images of breast precancerous conditions. Literature review has shown that the actual problem is biomedical image processing. The adaptive method of biomedical pre-processing and automated segmentation method has been developed. The method of automated selection of segmentation algorithms based on the use of Gromov-Frechet metric, Gromov-Hausdorff metric, and knowledge base has been developed. Convolution neural network method for histological and cytological image classification based on a combination of convolutional and sub-sampling layers and their input parameters has been developed. Computer experiments have been carried out at each level of computer vision in automated microscopy systems. The generalized structure and components of the intelligent automated microscopy system for histological and cytological image processing have been developed.