Global Health Diagnostics via Mobile Phone Microscopy: Improving Contrast and Resolution

A lack of access to proper disease screening and diagnostics continues to plague low-resource countries. As a result, diseases that have long been forgotten in affluent areas still cause an enormous, yet preventable burden in areas without adequate medical systems. In those countries, only the centralized healthcare facilities have the luxury of modern diagnostic equipment, along with the expert personnel required to use that equipment. Advances in consumer technologies, particularly the mobile phone, offer the potential to address the lack of access to healthcare in low-resource regions by creating new data collection and interpretation methods. One example with potential to improve disease diagnosis is the mobile phone microscope. By adding lenses to a conventional mobile phone camera, controlling sample illumination and motion, and automatically interpreting images, mobile phone microscopes have been shown to detect the presence of a pathogens and guide treatment decisions.This thesis advances the state-of-the-art in mobile phone microscopy by introducing new applications, new contrast modalities, and resolution enhancements. First, I give an overview of the current prototype implementation of darkfield and fluorescence microscopy on a mobile phone microscopy platform developed by the Fletcher Lab, detailing the physical design of the system along with the assumptions and disadvantages associated with that design. I also show results of the microscope's initial on-site imaging of Fusarium at various banana plantations in the Philippines. Next, I introduce a new illumination scheme to overcome key limitations of the current implementation. I show that by using an LCD screen as the light source, it is possible to finely tune the illumination in a way that simultaneously captures uniform brightfield, darkfield, and phase contrast without the need for larger standard microscope optics. Finally, I take advantage of the smartphone's onboard image stabilizer to displace the sample image relative to the camera sensor. I use this displacement to demonstrate a simple dithering algorithm that requires no additional hardware while more than doubling the microscope's resolution. By combining these new methods, mobile phone microscopes of the future have the potential to provide high-quality disease diagnoses at the point-of-care