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Proceedings Paper

Content-based cell pathology image retrieval by combining different features
Author(s): Guangquan Zhou; Lu Jiang; Limin Luo; Xudong Bao; Huazhong Shu
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Paper Abstract

Content Based Color Cell Pathology Image Retrieval is one of the newest computer image processing applications in medicine. Recently, some algorithms have been developed to achieve this goal. Because of the particularity of cell pathology images, the result of the image retrieval based on single characteristic is not satisfactory. A new method for pathology image retrieval by combining color, texture and morphologic features to search cell images is proposed. Firstly, nucleus regions of leukocytes in images are automatically segmented by K-mean clustering method. Then single leukocyte region is detected by utilizing thresholding algorithm segmentation and mathematics morphology. The features that include color, texture and morphologic features are extracted from single leukocyte to represent main attribute in the search query. The features are then normalized because the numerical value range and physical meaning of extracted features are different. Finally, the relevance feedback system is introduced. So that the system can automatically adjust the weights of different features and improve the results of retrieval system according to the feedback information. Retrieval results using the proposed method fit closely with human perception and are better than those obtained with the methods based on single feature.

Paper Details

Date Published: 19 April 2004
PDF: 8 pages
Proc. SPIE 5371, Medical Imaging 2004: PACS and Imaging Informatics, (19 April 2004); doi: 10.1117/12.532926
Show Author Affiliations
Guangquan Zhou, Southeast Univ. (China)
Lu Jiang, Southeast Univ. (China)
Limin Luo, Southeast Univ. (China)
Xudong Bao, Southeast Univ. (China)
Huazhong Shu, Southeast Univ. (China)


Published in SPIE Proceedings Vol. 5371:
Medical Imaging 2004: PACS and Imaging Informatics
Osman M. Ratib; H. K. Huang, Editor(s)

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