title: Ð ÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ñ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐºÐ¸ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹ Ð´Ð»Ñ Ð²ÑÑÐ²Ð»ÐµÐ½Ð¸Ñ Ð·Ð°Ð±Ð¾Ð»ÐµÐ²Ð°Ð½Ð¸Ñ Ð¿Ð¾ ÑÐµÐ½ÑÐ³ÐµÐ½Ð¾Ð²ÑÐºÐ¸Ð¼ ÑÐ½Ð¸Ð¼ÐºÐ°Ð¼
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Implementation of image processing algorithms for disease detection on x-ray images
Creators: name: ÐÑÐµÐ¼Ð»ÐµÐ²Ð°, ÐÐ½Ð½Ð°
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2022
Subjects: Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð°Ð½Ð°Ð»Ð¸Ð· Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹
Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ñ
ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ
ÑÐ²ÐµÑÑÐ¾ÑÐ½ÑÐµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
machine learning
image analysis
neural networks
segmentation
classification
convolutional neural networks

description: ÐÑÐµÐ´Ð¼ÐµÑÐ¾Ð¼ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ²Ð»ÑÑÑÑÑ Ð½Ð°Ð±Ð¾Ñ Ð´Ð°Ð½Ð½ÑÑ Ñ ÑÐµÐ½ÑÐ³ÐµÐ½Ð¾Ð²ÑÐºÐ¸Ð¼Ð¸ ÑÐ½Ð¸Ð¼ÐºÐ°Ð¼Ð¸, ÑÐ°ÐºÐ¶Ðµ ÑÐ¾Ð´ÐµÑÐ¶Ð°ÑÐ¸Ð¹ Ð¼Ð°ÑÐºÐ¸ Ð´Ð»Ñ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ð¸ Ð¸ Ð»ÐµÐ¹Ð±Ð»Ñ, ÑÐºÐ°Ð·ÑÐ²Ð°ÑÑÐ¸Ðµ Ð½Ð° Ð½Ð°Ð»Ð¸ÑÐ¸Ðµ Ð¸Ð»Ð¸ Ð¾ÑÑÑÑÑÑÐ²Ð¸Ðµ Ð½Ð°Ð»Ð¸ÑÐ¸Ñ Ð·Ð°Ð±Ð¾Ð»ÐµÐ²Ð°Ð½Ð¸Ñ. Ð¦ÐµÐ»Ñ Ð´Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ: ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ñ Ð¸ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ðµ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ, ÑÐ¿Ð¾ÑÐ¾Ð±Ð½ÑÑ Ñ Ð²ÑÑÐ¾ÐºÐ¾Ð¹ ÑÐ¾ÑÐ½Ð¾ÑÑÑÑ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÑÐ¸ÑÐ¾Ð²Ð°ÑÑ Ð½Ð°Ð»Ð¸ÑÐ¸Ðµ Ð¸Ð»Ð¸ Ð¾ÑÑÑÑÑÑÐ²Ð¸Ðµ ÑÐ¸Ð¼Ð¿ÑÐ¾Ð¼Ð¾Ð² Ð¿Ð°ÑÐ¾Ð»Ð¾Ð³Ð¸Ð¹ Ð¸ Ð·Ð°Ð±Ð¾Ð»ÐµÐ²Ð°Ð½Ð¸Ð¹ Ð¿Ð¾ ÑÐµÐ½ÑÐ³ÐµÐ½Ð¾Ð²ÑÐºÐ¸Ð¼ ÑÐ½Ð¸Ð¼ÐºÐ°Ð¼. ÐÐ°Ð´Ð°ÑÐ¸, ÐºÐ¾ÑÐ¾ÑÑÐµ Ð±ÑÐ»Ð¸ ÑÐµÑÐµÐ½Ñ Ð² ÑÐ¾Ð´Ðµ ÑÐ°Ð±Ð¾ÑÑ:1. ÐÐ·ÑÑÐ¸ÑÑ Ð¾ÑÐ½Ð¾Ð²Ð½ÑÑ ÑÐµÐ¾ÑÐ¸Ñ Ð² Ð¿ÑÐµÐ´Ð¼ÐµÑÐ½Ð¾Ð¹ Ð¾Ð±Ð»Ð°ÑÑÐ¸ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¸ ÑÑÑÑÐ¾Ð¹ÑÑÐ²Ð° ÑÐ°Ð±Ð¾ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹;2. ÐÑÐ¾Ð°Ð½Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°ÑÑ ÑÑÑÑÐºÑÑÑÑ Ð¸ Ð¿ÑÐ¸Ð½ÑÐ¸Ð¿ ÑÐ°Ð±Ð¾ÑÑ ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ñ Ð°ÑÑÐ¸ÑÐµÐºÑÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹, ÑÐ°ÑÑÐ¾ Ð¿ÑÐ¸Ð¼ÐµÐ½ÑÑÑÐ¸ÑÑÑ Ð´Ð»Ñ Ð¿Ð¾Ð´Ð¾Ð±Ð½ÑÑ Ð·Ð°Ð´Ð°Ñ.3. ÐÐ°Ð¿Ð¸ÑÐ°ÑÑ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½ÑÐ¹ ÐºÐ¾Ð´, Ð²ÑÐ¿Ð¾Ð»Ð½ÑÑÑÐ¸Ð¹ Ð½ÑÐ¶Ð½ÑÐµ Ð·Ð°Ð´Ð°ÑÐ¸ Ñ Ð²ÑÑÐ¾ÐºÐ¾Ð¹ ÑÐ¾ÑÐ½Ð¾ÑÑÑÑ.4. Ð¡Ð´ÐµÐ»Ð°ÑÑ Ð½ÐµÑÐºÐ¾Ð»ÑÐºÐ¾ ÑÐºÑÐ¿ÐµÑÐ¸Ð¼ÐµÐ½ÑÐ¾Ð², Ð¾ÑÐµÐ½Ð¸ÑÑ ÑÐ¾ÑÐ½Ð¾ÑÑÑ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð² Ð¸ Ð±ÑÑÑÑÐ¾Ð´ÐµÐ¹ÑÑÐ²Ð¸Ðµ ÑÐ°Ð±Ð¾ÑÑ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ñ;5. ÐÑÐ¾Ð²ÐµÑÑÐ¸ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ðµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð² Ð¸ ÑÐ´ÐµÐ»Ð°ÑÑ Ð²ÑÐ²Ð¾Ð´Ñ Ð¾ Ð¿ÑÐ¾Ð´ÐµÐ»Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÐµ. Ð ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ Ð²ÑÐ¿Ð¾Ð»Ð½ÐµÐ½Ð¸Ñ ÑÐ°Ð±Ð¾ÑÑ Ð±ÑÐ» ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½ÑÐ¹ ÐºÐ¾Ð´, ÑÐ¿Ð¾ÑÐ¾Ð±Ð½ÑÐ¹ Ð²ÑÐ¿Ð¾Ð»Ð½ÑÑÑ Ð¿ÐµÑÐµÑÐ¸ÑÐ»ÐµÐ½Ð½ÑÐµ Ð²ÑÑÐµ Ð·Ð°Ð´Ð°ÑÐ¸, Ð° ÑÐ°ÐºÐ¶Ðµ Ð¿ÑÐ¾Ð¸Ð·Ð²ÐµÐ´ÐµÐ½ Ð°Ð½Ð°Ð»Ð¸Ð· Ð¿Ð¾Ð»ÑÑÐ¸Ð²ÑÐ¸ÑÑÑ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð².
description: The subject of the study is a data set with X-ray images, also containing masks for segmentation and labels indicating the presence or absence of the presence of the disease. The purpose of this work is implementation and comparison of machine learning algorithms capable of classifying (with high accuracy) the presence or absence of symptoms of pathologies and diseases by X-ray images. Tasks that were solved during the work:1. To study the basic theory in the subject area of machine learning and the operation of neural networks;2. Analyze the structure and principle of operation of existing neural network architectures, often used for such tasks.3. Write a program code that performs the necessary tasks with high accuracy.4. Make several experiments, evaluate the accuracy of the results and the speed of the program;5. Compare the results and draw conclusions about the work done.As a result of the work, a program code capable of performing the tasks listed above was developed, as well as an analysis of the results.