تحلیل تصاویر ریزآرایه به منظور تشخیص نوع سرطان سینه

Background: Microarray technology is a powerful tool to study and analyze the behavior of thousands of genes simultaneously. Images of microarray have an important role in the detection and treatment of diseases. The aim of this study is to provide an automatic method for the extraction and analysis of microarray images to detect cancerous diseases. Methods: The proposed system consists of three main phases of image processing, data mining, and detection of disease. The image processing phase is accompanied with some operations such as identifying the location of genes, deleting the background, and extracting the raw data from the images. The second phase includes data normalization and selection of more effective genes. The disease is identified and recognized in the third phase using the extracted data. Results: In this study it has been used from breast cancer microarray images from Stanford University database. The accuracy of the proposed method to locate genes and diagnosis of breast cancer is up to 98 and 95.45%, respectively. Conclusion: The obtained results indicate that the proposed method is more accurate than other existing methods in microarray analysis. In addition, the proposed method is easily implemented and less costly compared to the clinical tests.