Three applications of pulse-coupled neural networks

Heggere S. Ranganath; Michele Ruggiero Banish; John R. Karpinsky; Rodney L. Clark; Glynn A. Germany; Philip G. Richards

doi:10.1117/12.343055

22 March 1999 Three applications of pulse-coupled neural networks

Heggere S. Ranganath, Michele Ruggiero Banish, John R. Karpinsky, Rodney L. Clark, Glynn A. Germany, Philip G. Richards

Proceedings Volume 3728, Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks; (1999) https://doi.org/10.1117/12.343055
Event: Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks: Neural Networks Fuzzy Systems, Evolutionary Systems and Virtual Re, 1998, Stockholm, Sweden

Abstract

Image segmentation is one of the major application areas for Pulsed Coupled Neural Networks (PCNN). Previous research has shown that the ability of PCNN to ignore minor variations in intensity and small spatial discontinuities in images is beneficial to image segmentation as well as image smoothing. This paper describes research and development projects in progress in which PCNN is used for the segmentation of three different types of digital images. The software for the diagnosis of Pulmonary Embolism from VQ lung scans uses PCNN in single burst mode for segmenting perfusion and ventilation images. The second project is attempting to detect ischemia by comparing 3D SPECT (Single Photon Emission Computed Tomography) images of heart obtained during stress and rest conditions, respectively. The third application is a space science project which deals with the study of global auroral images obtained from Ultraviolet Imager. The paper also describes an hardware implementation of PCNN as an electro-optical chip.

Citation Download Citation

Heggere S. Ranganath, Michele Ruggiero Banish, John R. Karpinsky, Rodney L. Clark, Glynn A. Germany, and Philip G. Richards "Three applications of pulse-coupled neural networks", Proc. SPIE 3728, Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks, (22 March 1999); https://doi.org/10.1117/12.343055

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KEYWORDS

Image segmentation

Neurons

Neural networks

Image processing

Ischemia

Lung

Single photon emission computed tomography

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