1. Wavelet-Based Image Registration and Segmentation Framework for the Quantitative Evaluation of Hydrocephalus
- Author
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Fan Luo, Jeanette W. Evans, Norma C. Linney, Matthias H. Schmidt, and Peter H. Gregson
- Subjects
Medical physics. Medical radiology. Nuclear medicine ,R895-920 ,Medical technology ,R855-855.5 - Abstract
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.
- Published
- 2010
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