Intracranial Hemorrhage Segmentation Using Deep Convolutional Model

@article{Hssayeni2020IntracranialHS,
  title={Intracranial Hemorrhage Segmentation Using Deep Convolutional Model},
  author={Murtadha D. Hssayeni and Muayad S. Croock and Aymen Al-Ani and Hassan Falah Al-khafaji and Zakaria A. Yahya and Behnaz Ghoraani},
  journal={Data},
  year={2020},
  volume={5},
  pages={14}
}
  • Murtadha D. Hssayeni, Muayad S. Croock, +3 authors Behnaz Ghoraani
  • Published in Data 2020
  • Medicine, Computer Science, Engineering
  • Traumatic brain injuries could cause intracranial hemorrhage (ICH). ICH could lead to disability or death if it is not accurately diagnosed and treated in a time-sensitive procedure. The current clinical protocol to diagnose ICH is examining Computerized Tomography (CT) scans by radiologists to detect ICH and localize its regions. However, this process relies heavily on the availability of an experienced radiologist. In this paper, we designed a study protocol to collect a dataset of 82 CT… CONTINUE READING

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