NCTU-DBLAB@Imageclefmed 2005: Medical image retrieval task

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


研究成果: 雜誌貢獻會議論文同行評審


In this paper, we use Support Vector Machine (SVM) to learn image feature characteristics for assisting the task of image classification. The ImageCLEF 2005 evaluation offers a superior test bed for medical image content retrieval. Several image visual features (including histogram, spatial layout, coherence moment and gabor features) have been employed in this paper to categorize the 1,000 test images into 57 classes. Based on the SVM model, we can examine which image feature is more promising in medical image retrieval. The result shows that the spatial relationship of pixels is a very important feature in medical image data, because medical image data always have similar anatomic regions (lung, liver, head, and so on); therefore image features emphasizing spatial relationship have better result than others.

期刊CEUR Workshop Proceedings
出版狀態已發佈 - 2005
事件2005 Cross Language Evaluation Forum Workshop, CLEF 2005, co-located with the 9th European Conference on Digital Libraries, ECDL 2005 - Wien, 奥地利
持續時間: 2005 9月 212005 9月 22

ASJC Scopus subject areas

  • 一般電腦科學


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