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

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

抄録

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.

本文言語英語
ホスト出版物のタイトル2021 5th IEEE International Conference on Cybernetics, CYBCONF 2021
出版社Institute of Electrical and Electronics Engineers Inc.
ページ24-29
ページ数6
ISBN(電子版)9781665403207
DOI
出版ステータス出版済み - 6 8 2021
イベント5th IEEE International Conference on Cybernetics, CYBCONF 2021 - Virtual, Sendai, 日本
継続期間: 6 8 20216 10 2021

出版物シリーズ

名前2021 5th IEEE International Conference on Cybernetics, CYBCONF 2021

会議

会議5th IEEE International Conference on Cybernetics, CYBCONF 2021
国/地域日本
CityVirtual, Sendai
Period6/8/216/10/21

All Science Journal Classification (ASJC) codes

  • 人工知能
  • コンピュータ サイエンスの応用
  • コンピュータ ビジョンおよびパターン認識

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