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Proceedings Paper

Lung cancer cell recognition based on multiple color space
Author(s): Jianfeng Lu; Shijin Li; Jingyu Yang; Leijian Liu; Anguang He; Keli Liu
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Paper Abstract

In this paper, we propose a set of effective algorithms to automatically detect the lung cancer cells in the cytological color image of examines' sputum smears. To increase the stability and efficiency of the detection of the cancer cells, a hierarchical processing architecture is adopted for the segmentation and recognition. For segmentation, RGB space and Lab space are combined to segment cell. By this method, both the nucleus and cytoplasm of cancer cells can be separated from background. Then, the candidate cancer cells are selected using some morphological features of nuclei, the purpose of this step is to pick out most of non cancer cells and leave a few doubtful cells for further verification, therefore improve the efficiency of the whole recognition process. As the last step, all the candidate cell, some statistic parameters in different color space are calculated, which are used as features for recognition. Experiment results are given.

Paper Details

Date Published: 6 October 1998
PDF: 9 pages
Proc. SPIE 3522, Intelligent Robots and Computer Vision XVII: Algorithms, Techniques, and Active Vision, (6 October 1998); doi: 10.1117/12.325784
Show Author Affiliations
Jianfeng Lu, Nanjing Univ. of Science and Technology (China)
Shijin Li, Nanjing Univ. of Science and Technology (China)
Jingyu Yang, Nanjing Univ. of Science and Technology (China)
Leijian Liu, Nanjing Univ. of Science and Technology (China)
Anguang He, China Medical Univ./Tumor Institute (China)
Keli Liu, China Medical Univ./Tumor Institute (China)


Published in SPIE Proceedings Vol. 3522:
Intelligent Robots and Computer Vision XVII: Algorithms, Techniques, and Active Vision
David P. Casasent, Editor(s)

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