Efficient segmentation of nuclei in different color spaces

This presentation discusses the problem of segmentation of nuclei in cytological color images in different color spaces, namely RGB and HSI color spaces, for the detection of lung cancer cells. For the segmentation in each color space, the background and foreground of the images are first defined, and the chromatic mean values of the background and foreground are then extracted. In the learning phase, based on the chromatic mean values of the background and foreground of training samples, an adaptive threshold function is constructed for each color space using the B-Spline technique. The nuclei are then segmented by thresholding using the adaptive threshold function obtained in the learning phase. Comparisons between the segmentation in RGB color space and in HSI color space are carried out.