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To that end, Mid and his students are using computational imaging to transform the way the mathematical theory behind microscopy works. The Image Lab's innovative computing environment, Imagining the Future of Computational Imaging (IVI), builds on Mid's decades-long involvement in mathematical imaging. Imagining the Future of Computational Imaging integrates theory with practice in a series of groundbreaking advances that will allow more researchers to build and understand high-quality imaging systems. Imagining the Future of Computational Imaging builds on Mid's decades-long involvement in mathematical imaging, but it is also unique because it applies a mathematical language that is easy to learn and powerful enough to perform sophisticated analysis. “Computer vision is a relatively young technology, but the demand for image analysis processing and image synthesis is far greater now than any time in the past,” said Mid. “I'm delighted by the potential this research, which I've been developing for years, may lead to.” “IVI is unique as a model system for integrating mathematics with visual analysis,” said Associate Professor of Molecular Biology and Biochemistry Steven H. Settler, who is leading one of IVI's many projects. In addition to being capable of predicting which proteins interact with which other proteins in a given sample, the software also produces high-quality images of different proteins at different levels of detail, including structural details. “The goal of this work is to develop applications which enable researchers to understand the dynamic behavior of proteins and to help develop new microscopes and other imaging systems,” Settler said. Imaging Sciences offers a unique computer-assisted computing environment that allows mid-career and post-doctoral faculty to design cutting-edge experiments to address many of our most important problems. The lab has several leading-edge imaging algorithms: “Binding Optimizer” (formerly known as “SOLID”), “Modeling for Image Analysis,” “Flexible Imaging with Computational Image Analysis,” “High-Definition Imaging for Computational Engineering,” and “High Performance Image Analysis for Data Mining” all use high-performance computing and statistical methods to explore the mysteries of complex imaging systems that can be imaged in complex environments. “Our approach to image analysis is unique. It allows us to do what people have been able to do for decades and achieve new results that were never possible before,” said Mid. “The possibilities of imaging biology in the laboratory are limitless.

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