Hybrid Medical Image Retrieval System For CT Brain Images
This work covers a combination of text- and content-based image retrieval techniques for medical applications. By combining THIR with CBIR, the images can also be indexed by their visual content and would be retrieved based on visual similarity. All medical images are associated with textual patient...
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| Format: | Thesis |
| Published: |
2009
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| Online Access: | http://shdl.mmu.edu.my/1677/ |
| _version_ | 1848789857369849856 |
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| author | wan Ahmad, Wan Siti Halimatul Munirah |
| author_facet | wan Ahmad, Wan Siti Halimatul Munirah |
| author_sort | wan Ahmad, Wan Siti Halimatul Munirah |
| building | MMU Institutional Repository |
| collection | Online Access |
| description | This work covers a combination of text- and content-based image retrieval techniques for medical applications. By combining THIR with CBIR, the images can also be indexed by their visual content and would be retrieved based on visual similarity. All medical images are associated with textual patient's metadata that stores valuable information and can be used to get specific results. For this reason, traditional text-based retrieval is still helpful and a combination of both the accuracy of the retrieved results. Hence, a system that integrates both methods is expected to be more efficient in retrieving those desired medical images. |
| first_indexed | 2025-11-14T18:03:23Z |
| format | Thesis |
| id | mmu-1677 |
| institution | Multimedia University |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:03:23Z |
| publishDate | 2009 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | mmu-16772010-09-23T04:12:47Z http://shdl.mmu.edu.my/1677/ Hybrid Medical Image Retrieval System For CT Brain Images wan Ahmad, Wan Siti Halimatul Munirah R Medicine (General) This work covers a combination of text- and content-based image retrieval techniques for medical applications. By combining THIR with CBIR, the images can also be indexed by their visual content and would be retrieved based on visual similarity. All medical images are associated with textual patient's metadata that stores valuable information and can be used to get specific results. For this reason, traditional text-based retrieval is still helpful and a combination of both the accuracy of the retrieved results. Hence, a system that integrates both methods is expected to be more efficient in retrieving those desired medical images. 2009-12 Thesis NonPeerReviewed wan Ahmad, Wan Siti Halimatul Munirah (2009) Hybrid Medical Image Retrieval System For CT Brain Images. Masters thesis, Multimedia University. http://myto.perpun.net.my/metoalogin/logina.php |
| spellingShingle | R Medicine (General) wan Ahmad, Wan Siti Halimatul Munirah Hybrid Medical Image Retrieval System For CT Brain Images |
| title | Hybrid Medical Image Retrieval System For CT Brain Images |
| title_full | Hybrid Medical Image Retrieval System For CT Brain Images |
| title_fullStr | Hybrid Medical Image Retrieval System For CT Brain Images |
| title_full_unstemmed | Hybrid Medical Image Retrieval System For CT Brain Images |
| title_short | Hybrid Medical Image Retrieval System For CT Brain Images |
| title_sort | hybrid medical image retrieval system for ct brain images |
| topic | R Medicine (General) |
| url | http://shdl.mmu.edu.my/1677/ http://shdl.mmu.edu.my/1677/ |