@inproceedings{78a0ee60d730452f941b87547bf366a5,
title = "Comparative Analysis of Deep Neural Network and Texture-Based Classifiers for Recognition of Acute Stroke using Non-Contrast CT Images",
abstract = "This work presents a computer technology for automatic recognition of acute stroke using non-contrast computed tomography brain images. The early diagnosis of acute stroke is of primary importance for deciding on a method for further treatment, and the developed system aims at assisting a radiology specialist in the decision making process. We consider deep neural network and texture-based classifiers in order to compare their efficiency on a moderate-sized sample of patients with acute stroke. We use U-net as a basic architecture of the neural network, and Haralick textural features, extracted from images, for kNN, SVM, Random Forest and Adaboost classifiers. Experiments with real CT images using cross-validation technique show that deep neural network outperforms the considered texture-based classifiers; however, the latter are faster in training. We demonstrate that texture-based approach is able to give potentially useful additional information for stroke recognition, such as estimates of textural features importance; visualization of differences in positive and negative class distributions.",
keywords = "acute stroke, classification, deep neural network, texture segmentation, U-net",
author = "Victor Nedel'ko and Roman Kozinets and Andrey Tulupov and Vladimir Berikov",
year = "2020",
month = may,
day = "1",
doi = "10.1109/USBEREIT48449.2020.9117784",
language = "English",
series = "Proceedings - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "376--379",
booktitle = "Proceedings - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020",
address = "United States",
note = "2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020 ; Conference date: 14-05-2020 Through 15-05-2020",
}