Abstract
An automatic diagnostic system of lung cancer based on the analysis of the sputum color images is presented. The system uses a segmentation method of sputum color images prepared by the Papanicolaou standard staining method. The segmentation is performed based on an energy function minimization using an unsupervised Hopfield neural network (HNN). The proposed technique has yielded correct segmentation of complex scene of sputum prepared by ordinary manual staining method in most of the tested images selected from a database containing thousands of sputum color images.