Research Internships: Automated Image Analysis and Visualization Techniques to Support Tissue Engineering Research
Code of project: 2009-04
Project Supervisor: Dr Andy Bulpitt
Area of interest: This project is linked to the Computer Vision Research Group.
Appropriate for degree programmes: All single and joint honours students from the School of Computing
Pre-requisites:Further information about the prerequisites for this project is available from Dr Andy Bulpitt, but some programming experience is expected.
Project Outline
We wish to establish a new collaboration with researchers involved in tissue engineering in the Institute of Bio-Medical Engineering (Prof Eileen Ingham and Prof Jenifer Kirkham). This will involve developing our previous work on analysis of virtual slides to apply the technology to images of tissue constructs and explanted scaffolds.
In tissue engineering of heart valves and cartilage, scaffolds on which to culture cells (mostly fibroblasts) are currently studied by step-sectioning onto glass slides and microscopic examination with conventional histochemical and immunohistochemical stains. Quantification is manual or semi-automatic. 2D whole slide or 3D whole section visualization is not possible.
Using virtual pathology slides together the automated image analysis and visualization methods will allow scaffolds to be examined to:
- Quantify and localise fibroblasts using whole slide imaging
- Automatically obtain information about fibroblast phenotype (ie. Chondrocyte like or spindled)
- Derive information about collagen fibre direction and length automatically
- Visualize the results in 2d and 3d
The project will conduct some preliminary work in this area to evaluate the performance of existing image analysis techniques on these new types of image and identify areas that require further research to best support clinical and biological research in this area.