FluoRender: Rapid Quantitative Analysis and Adaptive Workflows for Fluorescence Microscopy Data in Fundamental Biomedical Research

FluoRender is a software package for interactive visualization and analysis of multichannel and multidimensional fluorescence microscopy data. This project will continue to serve the pressing needs of biologists utilizing fluorescence microscopy for flexible and reliable data analysis. FluoRender also addresses the problems in fundamental biomedical research that demand rapid measurements and workflow prototyping.

This next round of NIH funding will allow further research and development in the following areas:

Interactive and collaborative measurement and analysis of large multidimensional microscopy data. We aim 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.

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.

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.

FluoRender can be downloaded here