Combining textual and visual features for cross-language medical image retrieval

Pei Cheng Cheng, Been Chian Chien, Hao Ren Ke, Wei Pang Yang

研究成果: 書貢獻/報告類型會議貢獻

3 引文 斯高帕斯(Scopus)

摘要

In this paper we describe the technologies and experimental results for the medical retrieval task and automatic annotation task. We combine textual and content-based approaches to retrieve relevant medical images. The content-based approach containing four image features and the text-based approach using word expansion are developed to accomplish these tasks. Experimental results show that combining both the content-based and text-based approaches is better than using only one approach. In the automatic annotation task we use Support Vector Machines (SVM) to learn image feature characteristics for assisting the task of image classification. Based on the SVM model, we analyze which image feature is more promising in medical image retrieval. The results show that the spatial relationship between pixels is an important feature in medical image data because medical image data always has similar anatomic regions. Therefore, image features emphasizing spatial relationship have better results than others.

原文英語
主出版物標題Accessing Multilingual Information Repositories - 6th Workshop of the Cross-Language Evalution Forum, CLEF 2005
發行者Springer Verlag
頁面712-723
頁數12
ISBN(列印)354045697X, 9783540456971
DOIs
出版狀態已發佈 - 2006
事件Accessing Multilingual Information Repositories - 6th Workshop of the Cross-Language Evalution Forum, CLEF 2005 - Vienna, 奥地利
持續時間: 2005 九月 212005 九月 23

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4022 LNCS
ISSN(列印)0302-9743
ISSN(電子)1611-3349

其他

其他Accessing Multilingual Information Repositories - 6th Workshop of the Cross-Language Evalution Forum, CLEF 2005
國家奥地利
城市Vienna
期間2005/09/212005/09/23

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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