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Proceedings Paper

Neural network platform for recognizing a sequence of cell images
Author(s): Alexandra Psarrou; Hilary Buxton
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Paper Abstract

The aim of the research introduced in this paper is to develop a unified neural network platform to model the behavior of cancerous cells. Neural networks are used to both extract features from the cell images and control the process for recognizing whether a sequence of cell images match the locomotive and social behavior of a cancerous cell and its probability to metastasize. The problem first tackled is the extraction of cell features from the images as, for example, the center of the cell. This paper gives an overview of the application and presents the results drawn from two neural network architectures, an `all connected' and a`locally connected' network, used for the extraction of cell centroid areas from images. Both networks are implemented on a distributed array of processors (DAP) and trained using the backpropagation learning algorithm.

Paper Details

Date Published: 16 September 1992
PDF: 10 pages
Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); doi: 10.1117/12.139983
Show Author Affiliations
Alexandra Psarrou, Queen Mary and Westfield College (United Kingdom)
Hilary Buxton, Queen Mary and Westfield College (United Kingdom)


Published in SPIE Proceedings Vol. 1709:
Applications of Artificial Neural Networks III
Steven K. Rogers, Editor(s)

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