This paper describes the development of a neural
networks-based software system for the analysis and
diagnosis of sinus conditions. Traditional image processing
techniques and artificial neural networks tools and
algorithms such as the self-organizing maps (SOM) were
invoked in the development of the diagnosis system. The
data were in the form of anonymous CT-images of sinuses
obtained from a local hospital. A major problem faced the
development of the system was caused by the fragmented or
incomplete boundaries between different objects in the CTimages.
A new algorithm was developed and successfully
applied to complete such boundaries. The system was
thoroughly tested with real images and the results indicate a
potential for the system to be integrated within a CTscanning
system to automate the process of diagnosis

Title

7th IEEE, IET International symp. on comm. sys, networks and digital signal processing (CSNDSP 2010), Newcastle Upon Tyne, UK, 21-23 July 2010

Publisher

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Publisher Country

Palestine

Publication Type

Both (Printed and Online)

Volume

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Year

2010

Pages

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