Cell Recognition of Microscopy Images of TPEF (Two Photon Excited Florescence) Probes

The behavior of a cell can be described through tissue morphogenesis, which involves the migration, division or death of tissue, and is regulated with the molecular scale. Automated cell detection from microscopy image has become an important step in cell-based experiments. We have developed a method to detect abnormal behavior of the cell through real-time images. Our method consists of pixel classification using K-Means and Bayesian classification. It is based on the combination of gray level threshold. Furthermore, Fast Fourier Transfer (FFT), covariance coefficient and verification of cell variation were applied to investigate the cells after drug injection. We have considered different types of confocal microscopy images. The images were taken after every five min. The NL1 compound has high fluorescent, which selectively targets the mitochondria, and mitochondria are sensitive to the environmental changes. Identification of cells in a TPEF probe test is very important for determining cell abnormalities. Detection of abnormal cells is very crucial in the early stage diseases, and it is beneficial for mitochondrial microenvironment related diseases.