Areas of Interest
I am developing a fully automated machine learning based approach for 3D segmentation of convexity subdural hematomas. Textural, statistical and geometrical features of sample points from 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.
- B.S., Amir Kabir University of Technology (Biomedical Engineering)