Retinal pigment epithelium (RPE) is a key site of pathogenesis of age-related macular degeneration (AMD). A key first step toward developing statistical quantifications of RPE morphology is image analysis of RPE flatmount. This thesis work aims to facilitate image analysis by developing a procedure for automated selecting regions with biological information from flatmount images. Our new approach, based on clustering analysis, can extract informative regions from a typical flatmount image of a mouse eye within one minute, a three order magnitude time saving improvement from the current manual procedure. This method is already contributing to the image analysis of RPE flatmounts.