title: ÐÐ½ÑÐµÐ³ÑÐ°ÑÐ¸Ñ Ð¿ÑÐ¸Ð·Ð½Ð°ÐºÐ¾Ð² Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¸ ÑÐ°Ð´Ð¸Ð¾Ð¼Ð¸ÐºÐ¸ Ð´Ð»Ñ ÑÐ°ÑÑÐ¸ÑÐµÐ½Ð½Ð¾Ð¹ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð¿Ð¾ Ð´Ð°Ð½Ð½ÑÐ¼ ÐºÐ¾Ð¼Ð¿ÑÑÑÐµÑÐ½Ð¾Ð¹ ÑÐ¾Ð¼Ð¾Ð³ÑÐ°ÑÐ¸Ð¸
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: Integrating deep learning and radiomic features for enhanced classification from CT scans
Creators: name: Ð¡ÑÑÐ°ÐºÐ¾Ð², ÐÑÑÐ°Ñ
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: ÐºÐ¾Ð¼Ð¿ÑÑÑÐµÑÐ½Ð°Ñ ÑÐ¾Ð¼Ð¾Ð³ÑÐ°ÑÐ¸Ñ
Ð¸Ð·Ð²Ð»ÐµÑÐµÐ½Ð¸Ðµ Ð¸ Ð²ÑÐ±Ð¾Ñ Ð¿ÑÐ¸Ð·Ð½Ð°ÐºÐ¾Ð²
ÑÐ°Ð´Ð¸Ð¾Ð¼Ð¸ÐºÐ°
Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÑ
ÑÐ°Ðº Ð»ÐµÐ³ÐºÐ¸Ñ
ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
computed tomography
feature extraction and selection
radiomics
neural network
lung cancer
classification
machine learning
deep learning

description: ÐÐ±ÑÐµÐºÑ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ â ÐÐ¢ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ñ ÑÐ°ÐºÐ° Ð»ÑÐ³ÐºÐ¸Ñ. Ð¦ÐµÐ»Ñ ÑÐ°Ð±Ð¾ÑÑ â Ð¸Ð·ÑÑÐµÐ½Ð¸Ðµ Ð²Ð»Ð¸ÑÐ½Ð¸Ñ ÑÐ¾Ð²Ð¼ÐµÑÐµÐ½Ð¸Ñ ÑÐ°Ð´Ð¸Ð¾Ð¼Ð¸ÑÐµÑÐºÐ¸Ñ Ð¿ÑÐ¸Ð·Ð½Ð°ÐºÐ¾Ð² Ñ Ð³Ð»ÑÐ±Ð¾ÐºÐ¸Ð¼Ð¸ Ð¿ÑÐ¸Ð·Ð½Ð°ÐºÐ°Ð¼Ð¸ Ð² Ð·Ð°Ð´Ð°ÑÐ°Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹. Ð ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð±ÑÐ»Ð° Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð° ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹ ÐÐ¢ ÑÐ½Ð¸Ð¼ÐºÐ¾Ð² Ð¿Ð¾ Ð¸Ñ ÑÐ°Ð´Ð¸Ð¾Ð¼Ð¸ÑÐµÑÐºÐ¸Ð¼ Ð¸ Ð³Ð»ÑÐ±Ð¾ÐºÐ¸Ð¼ Ð¿ÑÐ¸Ð·Ð½Ð°ÐºÐ°Ð¼, Ð¿Ð¾ÑÐ»Ðµ ÑÐµÐ³Ð¾ Ð±ÑÐ»Ð¸ Ð¿Ð¾Ð»ÑÑÐµÐ½Ñ ÑÑÐ°Ð²Ð½Ð¸ÑÐµÐ»ÑÐ½ÑÐµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ ÑÐ¾Ð²Ð¼ÐµÑÐµÐ½Ð¸Ñ ÑÑÐ¸Ñ Ð¿ÑÐ¸Ð·Ð½Ð°ÐºÐ¾Ð² Ð¸ Ð¸Ñ ÑÐ¾Ð»Ñ Ð² Ð·Ð°Ð´Ð°ÑÐ°Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸. ÐÐµÑÐ¾Ð´ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¸Ñ ÐÐÐ , Ð¾Ð¿Ð¸ÑÐ°Ð½Ð½ÑÐ¹ Ð² Ð´Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÐµ, ÑÐ¾ÑÑÐ¾Ð¸Ñ Ð¸Ð· Ð¿ÑÐ¸Ð¾Ð±ÑÐµÑÐµÐ½Ð¸Ñ Ð±Ð°Ð·Ñ Ð´Ð°Ð½Ð½ÑÑ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹ ÐÐ¢ ÑÐ½Ð¸Ð¼ÐºÐ¾Ð², Ð¿Ð¾Ð´Ð³Ð¾ÑÐ¾Ð²ÐºÐ¸ Ð¸ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð´Ð»Ñ ÑÐ°Ð±Ð¾ÑÑ Ñ Ð´Ð°Ð½Ð½ÑÐ¼Ð¸ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸ÑÐ¼Ð¸, Ð¸Ð·Ð²Ð»ÐµÑÐµÐ½Ð¸Ñ Ð¿ÑÐ¸Ð·Ð½Ð°ÐºÐ¾Ð² Ð¸ Ð¿Ð¾ÑÐ»ÐµÐ´ÑÑÑÐµÐ¹ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ñ Ð¸Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼. ÐÑÐ¸ Ð¿Ð¾Ð´Ð³Ð¾ÑÐ¾Ð²ÐºÐµ Ðº ÑÐ°Ð±Ð¾ÑÐµ 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Ðµ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð»Ð¸ÑÑ ÑÑÐµÐ´ÑÑÐ²Ð° Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸Ð·Ð°ÑÐ¸Ð¸ (Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð¹) ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ¾Ðº. ÐÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ñ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½ÑÐµ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ðµ ÑÐ°ÐºÐ¸Ðµ ÐºÐ°Ðº: Matlab.
description: Object of study is CT images of lung cancer. The aim is to study the impact of combining radiomic features with deep features in image classification tasks. The study involved classifying CT images based on their radiomic and deep features. Comparative results were obtained by combining these features and evaluating their roles in classification tasks. The methodology described in this work consists of acquiring a database of CT images, preparing and training a neural network to process these images, extracting features, and subsequently classifying the images using these features. Open educational resources and programs for information search and analysis were used in the preparation of the work. Automation tools were not utilized. Software such as Matlab was applied.