An image-based Entamoeba automatic detecting system

Abstract

The amoeba is a parasite which can compromise the human's health. Many people died of amoeba every year. Traditionally, pathologists use microscopy to execute the diagnosis in experiment. The pathologists adopt the number of amoebas in the amoebas to diagnose the severity of infection by the amoeba for a patient. However, the diagnosing quality and performance are heavily impacted by human's behaviors such as eyesight, strength and professional knowledge etc. Thus, in this paper, an image-based amoeba automatic detecting system is proposed to segment the amoebas cell from an amoeba image. The experimental results tell that the proposed method can precisely count the number of cells and detects their locations for most amoeba sample images.