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Stroke is one of the leading causes of death and physical disability worldwide. The most common method for stroke identification is computed tomography (CT) scanning, which provides detailed images of the brain to help diagnose various conditions, including strokes. This work aims to identify different types of ischemic strok+ e (chronic, subacute, and acute) using neural networks and image processing methods such as the adaptive ABTD method in CT images. The best results obtained for chronic stroke were a recall of 88.78%, accuracy of 86.32%, and F1-score of 87.53%.

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Identification of Different Types of Ischemic Stroke

  • 会议论文

  • 发表日期：

    2025年

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  • Emanuel T. de A. da Silva,
  • Brenda J. S. Nogueira,
  • Villaneve de O. Soares,
  • Pedro A. de A. da Silva,
  • Carlos D. M. Regis

摘要

Stroke is one of the leading causes of death and physical disability worldwide. The most common method for stroke identification is computed tomography (CT) scanning, which provides detailed images of the brain to help diagnose various conditions, including strokes. This work aims to identify different types of ischemic strok+ e (chronic, subacute, and acute) using neural networks and image processing methods such as the adaptive ABTD method in CT images. The best results obtained for chronic stroke were a recall of 88.78%, accuracy of 86.32%, and F1-score of 87.53%.