Summary FluoRender is a software package for interactive visualization and analysis of multichannel and multidimensional fluorescence microscopy data. This project will serve the pressing needs of biologists utilizing fluorescence microscopy for flexible and reliable data analysis and address the problems in fundamental biomedical research that demands rapid measurements and workflow prototyping. Specific Aim 1: Interactive and collaborative measurement and analysis of large multidimensional microscopy data. We will add rapid measurement tools specifically designed for three pilot studies of our close collaborators at the University of Utah. FluoRender will take full advantage of latest graphics processing unit (GPU) computing techniques and streamed processing to handle large data at interactive speed, ensuring the success of the collaborative projects. Specific Aim 2: Applying machine learning to user workflows and data analysis. We will support diverse data analysis needs from FluoRender users and provide automatic workflow assembly using machine learning. We will incorporate user interactions in a human-in-the-loop approach to address the problem of insufficient training examples and enhance interpretability in machine learning. Specific Aim 3: Interoperability between FluoRender and other popular open-source image analysis software. We will support invoking ImageJ/Fiji modules from FluoRender user interface. Users will be able to apply familiar ImageJ/Fiji functions combined with FluoRender interactive tools. Frequently accessed external functions will be converted to native FluoRender implementations to improve efficiency and accuracy. Specific Aim 4: Immersive volumetric data presentation. We will support the augmented reality (AR) headsets and holographic displays for immersive data analysis. These emerging display technologies will have more natural user interactions than the virtual reality (VR) devices and be advantageous for analyzing 3D data in scientific research.

Narrative The proposed research will enhance software tools for understanding fundamental biology and will contribute to the knowledge about the nature of living systems. Biological processes in fundamental research can be imaged with microscopy and FluoRender, the proposed analysis tool, will aid biologists to understand these processes.