Abstract
On the example of X-ray images of human lungs, the analysis and construction of models of semantic segmentation of computer vision is carried out. The paper explores various approaches to medical image processing, comparing methods for implementing deep learning models and evaluating them. 5 models of neural networks have been developed to perform the segmentation task, implemented using such well-known libraries as: TensorFlow and PyTorch. The model with the best performance can be used to build a system for automatic segmentation of various images of patients and calculate the characteristics of their organs.
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