Wavelet-Based Image Registration and Segmentation Framework for the Quantitative Evaluation of Hydrocephalus
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 t...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2010-01-01
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| Series: | International Journal of Biomedical Imaging |
| Online Access: | http://dx.doi.org/10.1155/2010/248393 |
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| Summary: | 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. |
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| ISSN: | 1687-4188 1687-4196 |