Predictors of Intracerebral Hematoma Enlargement Using Brain CT Images in Emergency Medical Care

Kazunori Oka, Takumi Hirahara, Yasunobu Nohara, Sozo Inoue, Koichi Arimura, Syoji Kobashi, Koji Iihara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Intracerebral hematoma (ICH) is the cause of intracerebral hemorrhage. Acute enlargement of the ICH is high risk, and emergency surgical treatment is required. Therefore, prediction of ICH enlargement is essential to improve a survival rate and outcome. The purpose of this study is to find factors to predict the ICH enlargement with thick slice head CT images. We propose three kinds of feature extraction methods, (1) shape and texture features, (2) layered texture features, and (3) anatomical location features. In addition, we introduce an ICH enlargement prediction method using support vector machine (SVM) and feature selection. The experimental results showed that the angular second order moment of the texture feature was the most effective in predicting the ICH enlargement. By using this feature, we were able to predict the ICH enlargement with an accuracy of 75.7%. In addition, we found that normalization of the location and posture improved the prediction accuracy by 2.7% compared to that without normalization.

Original languageEnglish
Title of host publication2021 5th IEEE International Conference on Cybernetics, CYBCONF 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages24-29
Number of pages6
ISBN (Electronic)9781665403207
DOIs
Publication statusPublished - Jun 8 2021
Event5th IEEE International Conference on Cybernetics, CYBCONF 2021 - Virtual, Sendai, Japan
Duration: Jun 8 2021Jun 10 2021

Publication series

Name2021 5th IEEE International Conference on Cybernetics, CYBCONF 2021

Conference

Conference5th IEEE International Conference on Cybernetics, CYBCONF 2021
Country/TerritoryJapan
CityVirtual, Sendai
Period6/8/216/10/21

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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