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Proceedings Paper

Three applications of pulse-coupled neural networks
Author(s): Heggere S. Ranganath; Michele Ruggiero Banish; John R. Karpinsky; Rodney L. Clark; Glynn A. Germany; Philip G. Richards
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Paper 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.

Paper Details

Date Published: 22 March 1999
PDF: 7 pages
Proc. SPIE 3728, Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks, (22 March 1999); doi: 10.1117/12.343055
Show Author Affiliations
Heggere S. Ranganath, Univ. of Alabama in Huntsville (United States)
Michele Ruggiero Banish, MEMS Optical Inc. (United States)
John R. Karpinsky, MEMS Optical Inc. (United States)
Rodney L. Clark, MEMS Optical Inc. (United States)
Glynn A. Germany, Univ. of Alabama in Huntsville (United States)
Philip G. Richards, Univ. of Alabama in Huntsville (United States)

Published in SPIE Proceedings Vol. 3728:
Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks
Thomas Lindblad; Mary Lou Padgett; Jason M. Kinser, Editor(s)

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