UCLA

Traditional algorithms prevalent in computational imaging and signal processingare hand-crafted empirical rules synthesized to achieve a desired goal. In contrast, our approach is to craft qualitatively new algorithms by emulating laws of physics. Here, we show that Non-Linear Schrodinger Equation (NLSE), the master equation in optical physics can be exploited to invent a new class of computational imaging algorithms with best-in-class performance. We demonstrate a new contrast enhancement algorithm that is computationally efficient, achieves superior color gamut performance, and is able to support real-time video enhancement at 4K and 8K resolutions. We also show how the NLSE operator becomes an edge detection algorithm with exceptional performance in low light levels. In certain cases, these algorithms have the potential to be implemented in physical optics. We demonstrate efficacy of these algorithms in solving a variety of problems for different real-world applications. Specially, we have developed CytoLive, an award-winning real-time live cell tracking tool utilizing our NLSE-guided algorithms to analyze time-lapse microscopy videos acquired under low light conditions. This tool preserves inherent cell behavior by overcoming phototoxicity and photobleaching and has the potential for accelerating research in drug discovery. Next, we discuss CytoEye, a cancer immunotherapy toolbox that mitigates the computational overload of analyzing giga-pixel sized pathology images of tumor microenvironment. Quantitative features extracted by this tool have the capability to predict whether or not patients respond to therapy { an important step toward personalized cancer immunotherapy.