Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/6545
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Computing | - |
dc.creator | Liu, Z | - |
dc.creator | Yan, J | - |
dc.creator | Zhang, DD | - |
dc.creator | Li, QL | - |
dc.date.accessioned | 2014-12-11T08:24:28Z | - |
dc.date.available | 2014-12-11T08:24:28Z | - |
dc.identifier.issn | 1559-128X | - |
dc.identifier.uri | http://hdl.handle.net/10397/6545 | - |
dc.language.iso | en | en_US |
dc.publisher | Optical Society of America | en_US |
dc.rights | © 2007 Optical Society of America. This paper was published in Applied Optics and is made available as an electronic reprint with the permission of OSA. The paper can be found at the following URL on the OSA website: http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-49-14-2639. Systematic or multiple reproduction or distribution to multiple locations via electronic or other means is prohibited and is subject to penalties under law. | en_US |
dc.subject | Biomedical engineering | en_US |
dc.subject | Chemical analysis | en_US |
dc.subject | Monochromators | en_US |
dc.subject | Support vector machines | en_US |
dc.title | Automated tongue segmentation in hyperspectral images for medicine | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.description.otherinformation | Author name used in this publication: Jing-qi Yan | en_US |
dc.description.otherinformation | Author name used in this publication: David Zhang | en_US |
dc.identifier.spage | 8328 | - |
dc.identifier.epage | 8334 | - |
dc.identifier.volume | 46 | - |
dc.identifier.issue | 34 | - |
dc.identifier.doi | 10.1364/AO.46.008328 | - |
dcterms.abstract | Automatic tongue area segmentation is crucial for computer aided tongue diagnosis, but traditional intensity-based segmentation methods that make use of monochromatic images cannot provide accurate and robust results. We propose a novel tongue segmentation method that uses hyperspectral images and the support vector machine. This method combines spatial and spectral information to analyze the medical tongue image and can provide much better tongue segmentation results. The promising experimental results and quantitative evaluations demonstrate that our method can provide much better performance than the traditional method. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Applied optics, 1 Dec. 2007, v. 46, no. 34, p. 8328-8334 | - |
dcterms.isPartOf | Applied optics | - |
dcterms.issued | 2007-12-01 | - |
dc.identifier.isi | WOS:000254673900017 | - |
dc.identifier.scopus | 2-s2.0-39049105243 | - |
dc.identifier.pmid | 18059676 | - |
dc.identifier.eissn | 2155-3165 | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_IR/PIRA | en_US |
dc.description.pubStatus | Published | en_US |
dc.description.oaCategory | VoR allowed | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Liu_Automated_Tongue_Segmentation.pdf | 980.97 kB | Adobe PDF | View/Open |
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