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...

Full description

Saved in:

Bibliographic Details
Main Author:	wan Ahmad, Wan Siti Halimatul Munirah
Format:	Thesis
Published:	2009
Subjects:	R Medicine (General)
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-mmu-ep.1677
record_format	uketd_dc
spelling	my-mmu-ep.16772010-09-23T04:12:47Z Hybrid Medical Image Retrieval System For CT Brain Images 2009-12 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 http://shdl.mmu.edu.my/1677/ http://myto.perpun.net.my/metoalogin/logina.php masters Multimedia University Research Library
institution	Multimedia University
collection	MMU Institutional Repository
topic	R Medicine (General)
spellingShingle	R Medicine (General) wan Ahmad, Wan Siti Halimatul Munirah Hybrid Medical Image Retrieval System For CT Brain Images
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.
format	Thesis
qualification_level	Master's degree
author	wan Ahmad, Wan Siti Halimatul Munirah
author_facet	wan Ahmad, Wan Siti Halimatul Munirah
author_sort	wan Ahmad, Wan Siti Halimatul Munirah
title	Hybrid Medical Image Retrieval System For CT Brain Images
title_short	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_sort	hybrid medical image retrieval system for ct brain images
granting_institution	Multimedia University
granting_department	Research Library
publishDate	2009
_version_	1747829430004219904

Hybrid Medical Image Retrieval System For CT Brain Images

Similar Items