A New Framework of Multiphase Segmentation and Its Application to Partial Volume Segmentation
We proposed a novel framework of multiphase segmentation based on stochastic theory and phase transition theory. Our main contribution lies in the introduction of a constructed function so that its composition with phase function forms membership functions. In this way, it saves memory space and als...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2011-01-01
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| Series: | Applied Computational Intelligence and Soft Computing |
| Online Access: | http://dx.doi.org/10.1155/2011/786369 |
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| _version_ | 1832548518306250752 |
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| author | Fuhua Chen Yunmei Chen Hemant D. Tagare |
| author_facet | Fuhua Chen Yunmei Chen Hemant D. Tagare |
| author_sort | Fuhua Chen |
| collection | DOAJ |
| description | We proposed a novel framework of multiphase segmentation
based on stochastic theory and phase transition theory. Our main
contribution lies in the introduction of a constructed function so that its
composition with phase function forms membership functions. In this way,
it saves memory space and also avoids the general simplex constraint problem
for soft segmentations. The framework is then applied to partial volume
segmentation. Although the partial volume segmentation in this paper is focused
on brain MR image, the proposed framework can be applied to any
segmentation containing partial volume caused by limited resolution and
overlapping. |
| format | Article |
| id | doaj-art-09c84b174daa46ee97977da01540e24c |
| institution | Kabale University |
| issn | 1687-9724 1687-9732 |
| language | English |
| publishDate | 2011-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applied Computational Intelligence and Soft Computing |
| spelling | doaj-art-09c84b174daa46ee97977da01540e24c2025-02-03T06:13:50ZengWileyApplied Computational Intelligence and Soft Computing1687-97241687-97322011-01-01201110.1155/2011/786369786369A New Framework of Multiphase Segmentation and Its Application to Partial Volume SegmentationFuhua Chen0Yunmei Chen1Hemant D. Tagare2Department of Mathematics, University of Florida, Gainesville, FL 32611-8105, USADepartment of Mathematics, University of Florida, Gainesville, FL 32611-8105, USADepartment of Diagnostic Radiology, Yale University, New Haven, CT 06520-8042, USAWe proposed a novel framework of multiphase segmentation based on stochastic theory and phase transition theory. Our main contribution lies in the introduction of a constructed function so that its composition with phase function forms membership functions. In this way, it saves memory space and also avoids the general simplex constraint problem for soft segmentations. The framework is then applied to partial volume segmentation. Although the partial volume segmentation in this paper is focused on brain MR image, the proposed framework can be applied to any segmentation containing partial volume caused by limited resolution and overlapping.http://dx.doi.org/10.1155/2011/786369 |
| spellingShingle | Fuhua Chen Yunmei Chen Hemant D. Tagare A New Framework of Multiphase Segmentation and Its Application to Partial Volume Segmentation Applied Computational Intelligence and Soft Computing |
| title | A New Framework of Multiphase Segmentation and Its Application to Partial Volume Segmentation |
| title_full | A New Framework of Multiphase Segmentation and Its Application to Partial Volume Segmentation |
| title_fullStr | A New Framework of Multiphase Segmentation and Its Application to Partial Volume Segmentation |
| title_full_unstemmed | A New Framework of Multiphase Segmentation and Its Application to Partial Volume Segmentation |
| title_short | A New Framework of Multiphase Segmentation and Its Application to Partial Volume Segmentation |
| title_sort | new framework of multiphase segmentation and its application to partial volume segmentation |
| url | http://dx.doi.org/10.1155/2011/786369 |
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