Automated Disease Identification With 3-D Optical Imaging: A Medical Diagnostic Tool

Abstract

Digital holographic microscopy is an ideal tool for 3-D cell imaging and characterization. It provides a host of cell parameters based on cell morphology and its temporal dynamics or time variation. These parameters can be used to study and quantify cell growth and cell physiology. When coupled with classification algorithms, this technique can also be used to identify and classify cells such as blood cells for automated disease identification. A compact, portable version of this 3-D optical imaging system has the potential to become a device for compact field portable biological data collection, analysis, and cell identification leading to disease diagnosis with mobile devices, low cost instruments for deployment in remote areas with limited access to healthcare to combat disease. In this paper, we present an overview of our reported work on the development of digital holographic microscopes and their applications in 3-D cell imaging, cell parameter extraction and cell classification for potential automated disease identification.