Assessment and evaluation of clinical parameters for the classification of head deformities
This project aims to evaluate different approaches for the assessment and classification of head deformities based on clinical parameters.
Algorithms will be implemented to automatically determine clinical parameters such as CI, CVAI, and the distances extracted for EEG for the target scans.
It will be evaluated how the measured clinical parameters correspond to the clinical labels assigned to the scans by the medical staff.
Different classification approaches with varying degree of complexity will be used. Easy and interpretable methods such as thresholding, linear and nonlinear regression should be compared with more complex methods such as bagged decision trees and support-vector-machines.