Computer-aided diagnosis of hyperacute stroke with thrombolysis decision support using a contralateral comparative method of CT image analysis

Yao Shieh*, Chien Hung Chang, Mengkai Shieh, Tsong Hai Lee, Yeu Jhy Chang, Ho Fai Wong, Shy Chyi Chin, Scott Goodwin

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

23 Scopus citations


New and improved techniques have been continuously introduced into CT and MR imaging modalities for the diagnosis and therapy planning of acute stroke. Nevertheless, non-contrast CT (NCCT) is almost always used by every institution as the front line diagnostic imaging modality due to its high affordability and availability. Consequently, the potential reward of extracting as much clinical information as possible from NCCT images can be very great. Intravenous tissue plasminogen activator (tPA) has become the gold standard for treating acute ischemic stroke because it is the only acute stroke intervention approved by the FDA. ASPECTS scoring based on NCCT images has been shown to be a reliable scoring method that helps physicians to make sound decisions regarding tPA administration. In order to further reduce inter-observer variation, we have developed the first end-to-end automatic ASPECTS scoring system using a novel method of contralateral comparison. Due to the self-adaptive nature of the method, our system is robust and has good generalizability. ROC analysis based on evaluation of 103 subjects who presented to the stroke center of Chang Gung Memorial Hospital with symptoms of acute stroke has shown that our system's dichromatic classification of patients into thrombolysis indicated or thrombolysis contraindicated groups has achieved a high accuracy rate with AUC equal to 90.2 %. The average processing time for a single case is 170 s. In conclusion, our system has the potential of enhancing quality of care and providing clinical support in the setting of a busy stroke or emergency center.

Original languageEnglish
Pages (from-to)392-406
Number of pages15
JournalJournal of Digital Imaging
Issue number3
StatePublished - 06 2014


  • Biomedical image analysis
  • Brain imaging
  • Computed tomography
  • Computer-aided analysis
  • Decision support
  • Hyperacute stroke
  • tPA


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