Eulerian Video Magnification Adaptation for Live Cell Microscopy Analysis

In this paper an adaptation of the Eulerian Video Magnification technique is described for use with .TIFF files produced by a photo-conversion time lapse protocol for live cell microscopy, specifically for research into Acquired Immune Deficiency Syndrome. The tracking and characterisation of a protein found in Human Immunodeficiency Virus, to determine its dynamics and pathways is a key determinant in understanding the protein’s function. The aim of this algorithm is to process an image sequence in the temporal direction with the result being that changes in fluorescence for particular pixel locations, or regions of interest, are tracked and filtered thereby removing noise which is inherent with these types of images. This reduction in noise produced overall clearer results that will aid in further analysis of the live cells. In addition to this, this implementation attempts to adapt the existing EVM algorithm to aid in the analysis of photo-conversion experiments. The algorithm will decompose images into a multi-scale representation, and filter images in the temporal domain, recompose the image with amplifications applied to exaggerate particular motions in the images sequence. This paper also investigates the applicability of this magnification, to determine if it is practical in the situation of tracking protein dynamics. Modification of captured data is to be kept at a minimum to reduce the possibility of misinterpretation of the data.