Negar Farzaneh

21

Chair

• Kayvan Najarian

Dissertation Title 

Automated Decision Support System for Traumatic Injuries 

Research Interests

While at UM Negar developed a fully automated machine learning-based approach for 3D segmentation of convexity subdural hematomas. Textural, statistical, and geometrical features of sample points from the intracranial region are extracted based on head Computed Tomography (CT) images. Then, a tree bagger classifier is implemented to classify each pixel as hematoma or no-hematoma. This method yields sensitivity, specificity, and area under the receiver operating curve (AUC) of 85.02%, 73.74%, and 0.87 respectively.