There is an urgent need for three-dimensional analysis of cardiomyocytes using a computer to clarify the mechanism of heart disease. However, because microscopic images include cells other than cardiomyocytes, it is necessary to classify the cells before analysis. Cardiomyocytes are characterized by a relatively low volume fraction of cell nuclei in the cytoplasm compared with other cells. In this study, these features were utilized to extract cell nuclei and cytoplasm from fluorescence microscopy images of neonatal mouse hearts and to classify cardiomyocytes and other cells based on volume ratio. The accuracy of the classification was approximately 90% when the correct answer data were created using the images of fluorescent cardiomyocytes, and the experimental results were compared. This method is considered, based on the experimental results, to be an effective approach for cardiomyocyte classification.
|