Intelligent data elimination for a rare event application

Ramkumar Narayanswamy; John L. Metz; Kristina M. Johnson

doi:10.1117/12.323161

1 October 1998 Intelligent data elimination for a rare event application

Ramkumar Narayanswamy, John L. Metz, Kristina M. Johnson

Proceedings Volume 3460, Applications of Digital Image Processing XXI; (1998) https://doi.org/10.1117/12.323161
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1998, San Diego, CA, United States

Abstract

Rare event applications are characterized by the event-of- interest being hidden in a large volume of routine data. The key to success in such situations is the development of a cascade of data elimination strategies, such that each stage enriches the probability of finding the event amidst the data retained for further processing. Automated detection of aberrant cells in cervical smear slides is an example of a rare event problem. Each slide can amount to 2.5 gigabytes of raw data and only 1 in 20 slides are abnormal. In this paper we examine the use of template matching, artificial neural networks, integrated optical density and morphological processing as algorithms for the first data elimination stage. Based on the experience gained, we develop a successful strategy with improves the overall event probability in the retained data from 0.01 initially to 0.87 after the second stage of processing.

Citation Download Citation

Ramkumar Narayanswamy, John L. Metz, and Kristina M. Johnson "Intelligent data elimination for a rare event application", Proc. SPIE 3460, Applications of Digital Image Processing XXI, (1 October 1998); https://doi.org/10.1117/12.323161

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