Digital Image Processing
Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
Automatic watershed segmentation of randomly textured color images
IEEE Transactions on Image Processing
Image segmentation using a texture gradient based watershed transform
IEEE Transactions on Image Processing
Combined morphological-spectral unsupervised image segmentation
IEEE Transactions on Image Processing
An automatic nonrigid registration for stained histological sections
IEEE Transactions on Image Processing
Fingerprint registration by maximization of mutual information
IEEE Transactions on Image Processing
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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.