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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| Format: | Article |
| Language: | English |
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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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| author | Fan Luo Jeanette W. Evans Norma C. Linney Matthias H. Schmidt Peter H. Gregson |
| author_facet | Fan Luo Jeanette W. Evans Norma C. Linney Matthias H. Schmidt Peter H. Gregson |
| author_sort | Fan Luo |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-20b4174e02fc4492afee1cdac0ee38fe |
| institution | Kabale University |
| issn | 1687-4188 1687-4196 |
| language | English |
| publishDate | 2010-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Biomedical Imaging |
| spelling | doaj-art-20b4174e02fc4492afee1cdac0ee38fe2025-02-03T01:31:13ZengWileyInternational Journal of Biomedical Imaging1687-41881687-41962010-01-01201010.1155/2010/248393248393Wavelet-Based Image Registration and Segmentation Framework for the Quantitative Evaluation of HydrocephalusFan Luo0Jeanette W. Evans1Norma C. Linney2Matthias H. Schmidt3Peter H. Gregson4Mathematics and Computing Science Department, Saint Mary's University, Halifax, NS, B3H 3C3, CanadaDepartment of Psychiatry, University of British Columbia, Vancouver, BC, V6T 2A1, CanadaMathematics and Computing Science Department, Saint Mary's University, Halifax, NS, B3H 3C3, CanadaDepartment of Radiology, Dalhousie University, Halifax, NS, B3H 2Y9, CanadaElectrical & Computer Engineering, Faculty of Engineering, Dalhousie University, Halifax, NS, B3J 1Z1, CanadaHydrocephalus, 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.http://dx.doi.org/10.1155/2010/248393 |
| spellingShingle | Fan Luo Jeanette W. Evans Norma C. Linney Matthias H. Schmidt Peter H. Gregson Wavelet-Based Image Registration and Segmentation Framework for the Quantitative Evaluation of Hydrocephalus International Journal of Biomedical Imaging |
| title | Wavelet-Based Image Registration and Segmentation Framework for the Quantitative Evaluation of Hydrocephalus |
| title_full | Wavelet-Based Image Registration and Segmentation Framework for the Quantitative Evaluation of Hydrocephalus |
| title_fullStr | Wavelet-Based Image Registration and Segmentation Framework for the Quantitative Evaluation of Hydrocephalus |
| title_full_unstemmed | Wavelet-Based Image Registration and Segmentation Framework for the Quantitative Evaluation of Hydrocephalus |
| title_short | Wavelet-Based Image Registration and Segmentation Framework for the Quantitative Evaluation of Hydrocephalus |
| title_sort | wavelet based image registration and segmentation framework for the quantitative evaluation of hydrocephalus |
| url | http://dx.doi.org/10.1155/2010/248393 |
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