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OFAI-TR-93-12 ( 26kB g-zipped PostScript file)

Experiences with Neural Networks as a Diagnostic Tool in Medical Image Processing

Georg Dorffner, Erich Prem, M. Mackinger, S. Kundrat, Paolo Petta, Gerold Porenta, H. Sochor

Through recent years artificial neural networks have proven to be a useful technique in the interpretation of high-dimensional data such as images. However, an adequate application of neural networks is often plagued by a lack of systematic methodology. It is one of the goals of the EC funded ESPRIT-II project NEUFODI (Neural Networks for Forecasting and Diagnosis Applications) to study and develop techniques for using artificial neural networks as tools for diagnosis.

In this paper we report about part of this larger project, namely about experiences with applying neural networks to the interpretation of planar thallium-201 scintigrams for the assessment of coronary artery disease. This application should serve as an example of how neural networks can be successfully applied in the area of medical image processing. In this realm we will discuss several aspects about the practical use of this widely used technique.

Citation: Dorffner G., Prem E., Mackinger M., Kundrat S., Petta P., Porenta G., Sochor H.: Experiences with Neural Networks as a Diagnostic Tool in Medical Image Processing, In Europäische Perspektiven der Medizinischen Informatik, Biometrie und Epidemologie (Michaelis et al., Eds.), MMV München, pp. 407-411, 1993.