Development of Computational Tools for Bio-image Processing and Analysis

I will present some of our recent work on the development of computational methods for bio-image processing and analysis. These methods aims to resolve, detect and track features of interest in noisy and diffraction limited fluorescence images. We have developed an automated particle tracking system capable of tracking the trajectories of thousands of single molecules in low signal to noise ratio and large time-lapse image data sets. The results provide the necessary information for quantitative analysis of molecular dynamics. I will also describe more recent work aimed at developing a computational super-resolution imaging technique, called translation microscopy (TRAM). TRAM can restore high-resolution images by using multiple diffraction-limited (low) resolution observations of a conventional microscope whilst translating the sample parallel to the image plane. I will discuss some testing results that demonstrate a ~7-fold increase in lateral spatial resolution in noisy biological environments, delivering multi-colour image resolution of ~30 nm.