An Integration of Decision Tree and Visual Analysis to Analyze Intracranial Pressure

  • Soo-Yeon JiEmail author
  • Kayvan Najarian
  • Toan Huynh
  • Dong Hyun Jeong
Part of the Methods in Molecular Biology book series (MIMB, volume 1598)


In Traumatic Brain Injury (TBI), elevated Intracranial Pressure (ICP) causes severe brain damages due to hemorrhage and swelling. Monitoring ICP plays an important role in the treatment of TBI patients because ICP is considered a strong predictor of neurological outcome and a potentially amenable method to treat patients. However, it is difficult to predict and measure accurate ICP due to the complex nature of patients’ clinical conditions. ICP monitoring for severe TBI patient is a challenging problem for clinicians because traditionally known ICP monitoring is an invasive procedure by placing a device inside the brain to measure pressure. Therefore, ICP monitoring might have a high infection risk and cause medical complications. In here, an ICP monitoring using texture features is proposed to overcome this limitation. The combination of image processing methods and a decision tree algorithm is utilized to estimate ICP of TBI patients noninvasively. In addition, a visual analytics tool is used to conduct an interactive visual factor analysis and outlier detection.

Key words

Intracranial Pressure Traumatic Brain Injuries Image Processing CART Visual Analytics 


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Copyright information

© Springer Science+Business Media LLC 2017

Authors and Affiliations

  • Soo-Yeon Ji
    • 1
    Email author
  • Kayvan Najarian
    • 2
  • Toan Huynh
    • 3
  • Dong Hyun Jeong
    • 4
  1. 1.Department of Computer ScienceBowie State UniversityBowieUSA
  2. 2.Department of Computational Medicine and BioinformaticsUniversity of Michigan, Ann ArborAnn ArborUSA
  3. 3.Division of Trauma, Surgical Critical CareCarolinas Medical CenterCharlotteUSA
  4. 4.Department of Computer Science and Information TechnologyUniversity of the District of ColumbiaWashington, DCUSA

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