Threshold Estimation Based on Local Minima for Nucleus and Cytoplasm Segmentation

Abstract

Background: Image segmentation is a process of partitioning the input image into its separate objects or regions. It is an essential step in image processing to segment the regions of interest (ROI) for further processing. We propose a method for segmenting neucleus and cytoplasm from the white blood cells (WBC).Methods: Initially, the method computes an initial value based on the minimum and maximum values of the input image. Then, a histogram of the input image is computed and then approximated to obtain function values. The method searches for the first local maximum and local minimum from the approximated function values. We approximate the required threshold from the first local minimum and the computed initial value based on defined conditions. The threshold is applied to the input image to binarize it and then perform post-processing to obtain the final segmented nucleus. We segment the whole WBC before segmenting the cytoplasm depending on the complexity of the objects in the image. For WBCs which are well separated from the RBCs, n thresholds are generated and then produce n thresholded images. Then, a standard Otsu method is used to binarize the average of the produced images. Morphological operations are applied on the binarized image and then use a single-pixel point from the segmented nucleus to segment the WBCs. For images in which RBCs touch the WBCs, we segment the whole WBC using SLIC and watershed methods. The cytoplasm is obtained by subtracting the segmented nucleus from the segmented WBC. Results: The method is tested on two different public data sets. Performance analysis is done and the results show that the proposed method segments well the nucleus and cytoplasm. Conclusion: We propose a method for nuclei and cytoplasm segmentation based on the local minima of the approximated function values from the histogram of image. The method has demonstrated its utility in segmenting nuclei, WBCs and cytoplasm and the results are reasonable.