A computer system for the leukocytes classification in medical images

The paper is about the development of a computer system for the white blood cells images classification. Solving the leukocytes classification task makes it possible to diagnose not only the blood diseases, but also a wide range of other diseases, as well as to evaluate the overall state of a person's health. Modern leukocytes classification methods have a fairly large number of shortcomings, which make a problem of finding the most effective method as a tool to solve this task. In our computer system we use the method based on using a trained convolutional neural network as a binary classifier for the leukocytes classificatio

Classification of medical images of patients with Covid-19 using transfer learning technology of convolutional neural network

The paper shows an approach to solving the problem of classifying X-ray images of the chest part of a healthy person and with the presence of COVID-19. The method is a trainable convolutional neural network. The results obtained allow improving existing approaches and methods in the field of classification of medical images with COVID-19, as well as obtaining an auxiliary mechanism for detecting COVID-19 in patient

Method for optimizing the shell of open pit mines based on parallel computing

One of the main stages in design of mineral development process is solution of finding optimal open pit problem. It is necessary to take into account the spatial distribution of mineral components and the allowable slope angles of the sides during solving this problem. The basis for performing calculations to optimize the extraction of reserves is a digital block model of the mineral deposit. The larger and more accurate block model of the ore deposit requires more computationally complex calculation process. In this regard, using of parallel computing in this area is very relevant. The importance of solving this problem determined by the need to have an accurate model of the open pit at various stages of its developmen

Analysis of thick and thin vessel pixel clustering for retinal blood vessel image segmentation

In this work, we revealed that digital image processing is an actual topic at present and it is widely used in various fields of medicine, including diagnosis of the eye fundus. An analysis of the dependence of the blood vessel segmentation results on the image of the eye fundus from various partitions to pixel classes corresponding to thick and thin vessels obtained by k-means clustering was mad