Details of Grant 

EPSRC Reference:	GR/L51072/01
Title:	AUTOMATIC ANALYSIS OF FISH IMAGES
Principal Investigator:	Clocksin, Professor W
Other Investigators:	Hulten, Professor MA
Researcher Co-Investigators:
Project Partners:	Heart of England NHS Foundation Trust Pre Nexus Migration
Department:	Unknown
Organisation:	Aston University
Scheme:	Standard Research (Pre-FEC)
Starts:	01 October 1997	Ends:	30 June 1998	Value (£):	39,177
EPSRC Research Topic Classifications:
EPSRC Industrial Sector Classifications:	No relevance to Underpinning Sectors
Related Grants:
Panel History:
Summary on Grant Application Form
In the last few years fluorescence in-situ hybridization (FISH) has emerged as one of the most important new techniques for the analysis of human chromosomes, with applications in cancer diagnosis, radiation-induced translocation assay, and screening for genetic abnormalities. Many of these applications require the analysis of large numbers of cells and involve considerable skilled human effort. However, attempts to automate the analysis of FISH images have been based on conventional image processing techniques and have met with limited success. This project brings together one of the world's foremost groups in neural computing with a leading cytogenetics laboratory with the aim of exploiting recent developments in the neural computing field in order to find a robust and clinically-applicable solution to the FISH analysis problem. In particular, techniques based on Bayesian inference, which have been found to offer the best approach to the use of neural networks in pattern recognition, will be applied to this problem. In addition, novel generative modelling approaches based on mixture distributions and latent variable models, which offer a number of potential advantages, will also be explored. The project will address two of the most important classes of application for FISH; numerical chromosomal abnormality measurement and translocation detection.
Key Findings
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Organisation Website:	http://www.aston.ac.uk