Cytological color image processing system for diagnosis of lung cancers
Lei-Jian Liu, Yulong Cao, Hua F. Wang, Jingyu Yang · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1993
Image processing techniques have already been widely used in various medical applications for decades. With the development of computer and image processing techniques, more and more medical diagnostic systems have been put into use. This presentation describes a cytological color image processing system developed for the health inspection for early stage lung cancers. As most of the existing microscopic diagnostic systems use morphological, and gray or color features respectively, which results in the instability of the diagnosis and limitation in their applications, we make use of both morphological and color features of the cells in our system. To increase the stability and efficiency of the diagnosis, we adopt a hierarchical processing architecture for the segmentation and classification of cells. First, all the nuclei are segmented by thresholding in a special color space. Then, the segmented nuclei are classified as normal cells or candidate cancer cells using their morphological features. Finally, suing the chromatic features of the nuclei, all the candidate cancer cells are verified and further classified. At last, experiment results are given to show the feasibility of the approach proposed here.