Content-based cell pathology image retrieval by combining different features

Guangquan Zhou; Lu Jiang; Limin Luo; Xudong Bao; Huazhong Shu

doi:10.1117/12.532926

19 April 2004 Content-based cell pathology image retrieval by combining different features

Guangquan Zhou, Lu Jiang, Limin Luo, Xudong Bao, Huazhong Shu

Proceedings Volume 5371, Medical Imaging 2004: PACS and Imaging Informatics; (2004) https://doi.org/10.1117/12.532926
Event: Medical Imaging 2004, 2004, San Diego, California, United States

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.

Citation Download Citation

Guangquan Zhou, Lu Jiang, Limin Luo, Xudong Bao, and Huazhong Shu "Content-based cell pathology image retrieval by combining different features", Proc. SPIE 5371, Medical Imaging 2004: PACS and Imaging Informatics, (19 April 2004); https://doi.org/10.1117/12.532926

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