A spatio-temporally integrated and nonlinear particle tracking system for live cell imaging

Lead Research Organisation: Heriot-Watt University
Department Name: Sch of Engineering and Physical Science


Despite recent advances in light microscopy revolutionizing live cell imaging [1-2], the full potential of the increasing high sensitivity and resolution of modern microscopes has yet to be realised. A key barrier is the limited power and scope of image analysis techniques currently available to cell biologists. Although commercial programs promise automated particle identification and tracking and have been successfully used to assist image analysis in high signal to noise ratio environments, our extensive experimental tests have shown that they are inadequate to deal with live cell images that are of low signal to noise ratio, poor and variable contrast, and often comprise multiple particles in close proximity and with inconsistent movement. In many cases, particles can only be tracked manually by placing the cursor on objects over time. A major improvement would be to exploit advanced image processing and analysis algorithms to deal with complex time-lapse live cell data, in much the same way that new de-convolution algorithms have significantly improved wide-field imaging in Biology [3]. In this project, we propose to research and develop a nonlinear partial differential equation (PDE) method as a new approach to tracking biological particles in live cells. A key advantage of this method over all commercial software currently available to biologists is to make full use of temporal and spatial relationships in time-lapse data to assist in overcoming severe noise effects and recognition of targets in real biological conditions. Specifically, we will develop a spatio-temporally integrated and nonlinear particle tracking system based on the PDE approach and integrate it to the ImageJ image analysis suite [4] to provide a user-friendly graphical interface to biologists.
Description We have developed novel particle detection and tracking methods that can apply to bigological systems in low signal to noise environments to investigate the dynamics of organelles and single molecuels. The methods are currently been used in several leading labs in the UK and abroad.
Exploitation Route We are now developing a ImageJ plugin that will allow biologists without much IT knowledge to use the particel trascking software.
Sectors Pharmaceuticals and Medical Biotechnology

Description I have developed user friendly software that allows biologists to use for their applications. We are developing an ImageJ plugin which will allow much wider access by biologists.
First Year Of Impact 2010
Sector Pharmaceuticals and Medical Biotechnology
Impact Types Societal,Economic

Description Heriot-Watt and Oxford 
Organisation University of Oxford
Department Department of Biochemistry
Country United Kingdom 
Sector Academic/University 
PI Contribution We provide expertise in phyiscs and image processing to this project
Collaborator Contribution They provide expertise in cell biology
Impact At least three publications. This is a multi-disciplinary research between physics/enginering from us and biology from our partner.
Start Year 2008