title: ÐÐµÑÐ¾Ð´ Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ð¸ ÐÐ Ð¢-Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ñ
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: Deep learning method for segmentation of MRI images
Creators: name: ÐÐ°Ð½Ñ Ð®Ð¹ÑÑÐ½
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: 2024
Subjects: Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ñ Ð¼ÐµÐ´Ð¸ÑÐ¸Ð½ÑÐºÐ¸Ñ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹
Ð¼ÑÑ
Ð¶ÐµÐ»ÑÐ´Ð¾ÑÐºÐ¸ ÑÐµÑÐ´ÑÐ°
ÐÐ½ÑÐµÐ¿ÑÐ¸Ð¾Ð½Ð ÐµÑÐÐµÑV2
ÐÐ¾Ð±Ð¸Ð»ÐµÐÐµÑV2
ResNet-18
ResNet-50
Xception
deeplabv3
ÐºÐ¾ÑÑÑÐ¸ÑÐ¸ÐµÐ½Ñ ÑÑ Ð¾Ð´ÑÑÐ²Ð° dice
Ð¸Ð½Ð´ÐµÐºÑ jaccard
ÑÐ¾ÑÐ½Ð¾ÑÑÑ Ð¿Ð¸ÐºÑÐµÐ»ÐµÐ¹
deep learning
medical image segmentation
mri
cardiac ventricles
InceptionResNetV2
MobileNetV2
dice similarity coefficient
jaccard index
pixel accuracy

description: ÐÐ±ÑÐµÐºÑ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ â ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ñ Ð¶ÐµÐ»ÑÐ´Ð¾ÑÐºÐ¾Ð² ÑÐµÑÐ´ÑÐ° Ð½Ð° ÐÐ Ð¢-Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸ÑÑ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð°ÑÑÐ¸ÑÐµÐºÑÑÑ Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ. Ð¦ÐµÐ»Ñ ÑÐ°Ð±Ð¾ÑÑ â Ð¾ÑÐµÐ½Ð¸ÑÑ Ð¸ ÑÑÐ°Ð²Ð½Ð¸ÑÑ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÑ ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÑ Ð°ÑÑÐ¸ÑÐµÐºÑÑÑ Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ð¸ ÐÐ Ð¢-Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹ Ð¶ÐµÐ»ÑÐ´Ð¾ÑÐºÐ¾Ð², ÑÑÐ¾Ð±Ñ ÑÐ»ÑÑÑÐ¸ÑÑ ÐºÐ°ÑÐµÑÑÐ²Ð¾ Ð¸ ÑÐºÐ¾ÑÐ¾ÑÑÑ Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐºÐ¸ Ð¼ÐµÐ´Ð¸ÑÐ¸Ð½ÑÐºÐ¸Ñ Ð´Ð°Ð½Ð½ÑÑ. Ð ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð±ÑÐ»Ð¾ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¾ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ðµ Ð½ÐµÑÐºÐ¾Ð»ÑÐºÐ¸Ñ Ð°ÑÑÐ¸ÑÐµÐºÑÑÑ Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ, Ð²ÐºÐ»ÑÑÐ°Ñ InceptionResnetV2, MobileNetV2, ResNet-18, ResNet-50, Ð¸ Xception. ÐÑÐ»Ð¸ Ð¿Ð¾Ð»ÑÑÐµÐ½Ñ Ð²ÑÑÐ¾ÐºÐ¸Ðµ Ð·Ð½Ð°ÑÐµÐ½Ð¸Ñ Ð¿Ð¾ ÑÑÐµÐ¼ ÐºÐ»ÑÑÐµÐ²ÑÐ¼ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ°Ð¼ Ð¾ÑÐµÐ½ÐºÐ¸: ÐºÐ¾ÑÑÑÐ¸ÑÐ¸ÐµÐ½Ñ ÑÑÐ¾Ð´ÑÑÐ²Ð° Dice, Ð¸Ð½Ð´ÐµÐºÑÐ° Jaccard Ð¸ ÑÐ¾ÑÐ½Ð¾ÑÑÑ Ð¿Ð¸ÐºÑÐµÐ»ÐµÐ¹, ÑÑÐ¾ Ð¿Ð¾Ð´ÑÐµÑÐºÐ¸Ð²Ð°ÐµÑ Ð¸Ñ Ð¿ÑÐ¸Ð³Ð¾Ð´Ð½Ð¾ÑÑÑ Ð´Ð»Ñ ÐºÐ»Ð¸Ð½Ð¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ Ð² Ð´Ð¸Ð°Ð³Ð½Ð¾ÑÑÐ¸ÐºÐµ ÑÐµÑÐ´ÐµÑÐ½ÑÑ Ð·Ð°Ð±Ð¾Ð»ÐµÐ²Ð°Ð½Ð¸Ð¹. Ð ÐµÐ·ÑÐ»ÑÑÐ°ÑÑ ÑÐ°Ð±Ð¾ÑÑ Ð¸Ð¼ÐµÑÑ Ð½Ð¾Ð²Ð¸Ð·Ð½Ñ Ð¸ Ð·Ð½Ð°ÑÐ¸Ð¼Ñ Ð´Ð»Ñ Ð¾Ð±Ð»Ð°ÑÑÐ¸ Ð¼ÐµÐ´Ð¸ÑÐ¸Ð½ÑÐºÐ¾Ð¹ Ð²Ð¸Ð·ÑÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸. ÐÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð»Ð¸ÑÑ Ð¾ÑÐºÑÑÑÑÐµ Ð¾Ð±ÑÐ°Ð·Ð¾Ð²Ð°ÑÐµÐ»ÑÐ½ÑÐµ ÑÐµÑÑÑÑÑ Ð¸ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ñ Ð¿Ð¾Ð¸ÑÐºÐ° Ð¸ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ð¸. ÐÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¾ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ðµ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ðµ MATLAB Ð¸ Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½ÑÐµ Ð¸Ð½ÑÑÑÑÐ¼ÐµÐ½ÑÑ Ð´Ð»Ñ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ¸ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ. ÐÐ±Ð»Ð°ÑÑÑ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð² Ð²ÐºÐ»ÑÑÐ°ÐµÑ Ð¼ÐµÐ´Ð¸ÑÐ¸Ð½ÑÐºÑÑ Ð²Ð¸Ð·ÑÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ñ Ð¸ Ð´Ð¸Ð°Ð³Ð½Ð¾ÑÑÐ¸ÐºÑ ÑÐµÑÐ´ÐµÑÐ½ÑÑ Ð·Ð°Ð±Ð¾Ð»ÐµÐ²Ð°Ð½Ð¸Ð¹. Ð ÐµÐ·ÑÐ»ÑÑÐ°ÑÑ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð¼Ð¾Ð³ÑÑ Ð±ÑÑÑ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ñ Ð´Ð»Ñ ÑÐ»ÑÑÑÐµÐ½Ð¸Ñ ÐºÐ°ÑÐµÑÑÐ²Ð° Ð¸ ÑÐºÐ¾ÑÐ¾ÑÑÐ¸ Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐºÐ¸ Ð¼ÐµÐ´Ð¸ÑÐ¸Ð½ÑÐºÐ¸Ñ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹, ÑÑÐ¾ ÑÐ¿Ð¾ÑÐ¾Ð±ÑÑÐ²ÑÐµÑ Ð±Ð¾Ð»ÐµÐµ ÑÐ¾ÑÐ½Ð¾Ð¹ Ð´Ð¸Ð°Ð³Ð½Ð¾ÑÑÐ¸ÐºÐµ.
description: Object of study is the segmentation of cardiac ventricles on MRI images using deep learning architectures. The aim is to evaluate and compare the effectiveness of various deep learning architectures for the segmentation of MRI images of ventricles, to improve the quality and speed of medical data processing. As a result of the research, a comparison of several deep learning architectures including InceptionResnetV2, MobileNetV2, ResNet-18, ResNet-50, and Xception was conducted. High values were obtained for three key evaluation parameters: Dice Similarity Coefficient, Jaccard Index, and Pixel Accuracy, highlighting their suitability for clinical application in the diagnosis of heart diseases. The results are novel and significant for the field of medical imaging. Open educational resources and information search and analysis programs were used. MATLAB software and automated tools for developing deep learning algorithms were applied. The area of application of the results includes medical imaging and the diagnosis of heart diseases. The findings can be used to improve the quality and speed of processing medical images, contributing to more accurate diagnostics.