Automatic cell recognition in immunohistochemical gastritis stains using sequential thresholding and SVM network

Abstract

The paper presents program for automatic cell recognition and counting in selected immunohistochemical stains in the gastritis diseases. It is applied to cytoplasm reactivity markers, such as chromogranin A, serotonin and somatostatin antibodies. The program uses the sequential thresholding algorithm in combination with artificial neural network of support vector machine (SVM) type, to recognize the nuclei of the separated cells. The constructed algorithm imitates the human view of the image. The support vector machine is used for recognition of the immunoreactivity of the separated cell. The results corresponding to the exemplary images, confirm good accuracy, comparable to the human expert.