Image Registration and Segmentation for the Quantitative Evaluation of Complex Medical Imaging and Diagnosis over Head – A Systematic Review

In medical imaging and diagnosis, 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 proposed work are: adaptive image registration based on mutual information and wavelet multi resolution analysis; adaptive segmentation with novel feature extraction based on the Dual-Tree Complex Wavelet Transform; volume calculation. This new approach has potential for development as a tool in the evaluation of medical diagnosis such as hydrocephalus.