The Algorithm for Preparing a Set of Data for Teaching Neural Networks on the Example of the Task to Analyze the Radiological Images of Lungs

Abstract

The methodology for preparing data for teaching neural networks is considered in solving two problems: checking the modality of computed tomography and checking the modality of radiographic images. The algorithm for preparing data for neural networks training is proposed. The influence of the stages (marking of images, normalization of data, determining the dynamic image range, the composition of the training sample) of the algorithm for the learning result is evaluated. The greatest influence in solving the task of modality verification of modality was the choice of optimal values of the dynamic range. The change in the composition of the training sample made it possible to increase the accuracy of the classification by 0.0073. When solving the task of checking the modality of images of computed tomography, the most impact on the result of the training of the neural network had the stage of data normalization. The assumption is put forward that there are special signs of images of this modality.