Lung cancer cell recognition based on multiple color space

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.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.