An efficient deep neural network for automatic classification of acute intracranial hemorrhages in brain CT scans.

Journal: Computers in biology and medicine
Published Date: May 9, 2024

Abstract

BACKGROUND: Recent advancements in deep learning models have demonstrated their potential in the field of medical imaging, achieving remarkable performance surpassing human capabilities in tasks such as classification and segmentation. However, these modern state-of-the-art network architectures often demand substantial computational resources, which limits their practical application in resource-constrained settings. This study aims to propose an efficient diagnostic deep learning model specifically designed for the classification of intracranial hemorrhage in brain CT scans.

Authors

  • Yu-Ruei Chen
    School of Medicine, Chang Gung University, Taoyuan, Taiwan; Medical Education Department, Chang Gung Memorial Hospital, Taoyuan, Taiwan.
  • Chih-Chieh Chen
    Center for Artificial Intelligence in Medicine, Chang Gung Memorial Hospital, Taoyuan, Taiwan, Republic of China.
  • Chang-Fu Kuo
    Department of Rheumatology, Allergy, and Immunology, Chang Gung Memorial Hospital, Taipei, Taiwan, ROC.
  • Ching-Heng Lin
    Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan.

Keywords

External Resources

Popular Topics
Recent Journals