Wavelet-Based Image Registration and Segmentation Framework for the Quantitative Evaluation of Hydrocephalus

Abstract EN

Hydrocephalus, characterized by increased fluid in the cerebral ventricles, is traditionally evaluated by a visual assessment of serial CT scans.

The complex shape of the ventricular system makes accurate visual comparison of CT scans difficult.

The current research developed a quantitative method to measure the change in cerebral ventricular volume over time.

Key elements of the developed framework are: adaptive image registration based on mutual information and wavelet multiresolution analysis; adaptive segmentation with novel feature extraction based on the Dual-Tree Complex Wavelet Transform; volume calculation.

The framework, when tested on physical phantoms, had an error of 2.3%.

When validated on clinical cases, results showed that cases deemed to be normal/stable had a calculated volume change less than 5%.

Those with progressive/treated hydrocephalus had a calculated change greater than 20%.

These findings indicate that the framework is reasonable and has potential for development as a tool in the evaluation of hydrocephalus.