Abstract
Currently, automation and robotization of research is being introduced into all areas of medicine and veterinary medicine, including histological analysis. At the same time, it is necessary to provide an automated decision-making system for quality control of histological images preparation. The technological process of histologic analysis running in spatial and temporal basis has been studied. The process of histologic analysis is a complex dynamic system including the stages of biomaterial preparation and study of morphostructural changes in tissues. The problem of process flow description is based on the law of mass conservation during biosphere transfer, which takes into account the equation of flow continuity in Euler and Lagrange variables. In controlling the histologic process, the errors associated with process failure were taken into account. The solution was obtained using an impulsive transient Green's function. In the period 2000-2023, according to statistical data, an increase in the number of cancer cases was observed, which makes the development of an automated histological analyzer relevant. The aim of the study was to build a control model for the automated process of histological analysis. Research Methods. The approaches to the device design were based on the theory of histologic analysis, application of continuum mechanics methods, methods of solving differential equations using Green's function. Results. The technique of histologic analysis was studied. The analytical solution describing the control of the automated technological process of histological analysis in conditions of possible disturbances caused by perturbations, such as "marriage" and time delay in the preparation of histological specimens has been obtained. Preparation of high-quality histological images will accelerate the diagnosis in the study of morphostructural changes in tissues, which will help to reduce the risks of developing not only cancer, but also other diseases. Conclusion. Express analyzer of histological analysis will reduce the time of preparation of histological images and the burden on highly qualified medical personnel.
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