Microscopic image segmentation based on color pixels classification
Mi‐Ra Park, Jesse Sheng Jin, Min Gang Xu, W. S. Felix Wong, Suhuai Luo, Yue Julia Cui · 2009
The computer-assisted microscopy systems can increase the accuracy of the analysis. To guarantee correct results in computer-assisted microscopy, accurate nuclei segmentation is crucially important since images segmentation is the first step towards image understanding and image analysis. In this paper, we present clustering techniques to segment homogeneous clusters in RGB color space and then label each cluster as a different region. According to the evaluation process, 97% of nuclei pixels were correctly delineated with our algorithm and on average 90% of nuclei were correctly detected. Our methods could be of value to computer-based systems designed to objectively interpret microscopic images by accurate nuclei segmentation.