Higher-order tasks: Human vs. machine performance

R. F. Wagner; K. J. Myers; D. G. Brown; M. J. Tapiovaara; A. E. Burgess

doi:10.1117/12.953203

1 May 1989 Higher-order tasks: Human vs. machine performance

R. F. Wagner, K. J. Myers, D. G. Brown, M. J. Tapiovaara, A. E. Burgess

Proceedings Volume 1090, Medical Imaging III: Image Formation; (1989) https://doi.org/10.1117/12.953203
Event: Medical Imaging III, 1989, Newport Beach, CA, United States

Abstract

The linear prewhitening matched filter (PWMF) is the optimal decision function for discriminating exactly-specified signals in additive Gaussian noise. When the signals are less well specified the optimal decision function contains higher than linear terms in the data. Several examples of detection and discrimination tasks are presented for which only the linear term is required and other examples for which higher order terms are necessary. Even in the nonlinear case decision functions can often be approximated by linear operations on the data followed by logical operations. This combination of linear weights plus logic operations is typical of neural network models, which are thought to be elementary models of human processing mechanisms. A number of experiments suggest that there is no decrease in performance of humans for some complex tasks that ideally require such nonlinear operations. However, there are other such tasks where human performance is degraded and this appears to be due more to the complexity of the task and the nature of the correlations in the image than the order of the task. This suggests applications in diagnostic imaging where it might be advantageous for a machine viewer to substitute or work in conjunction with the human observer.

Citation Download Citation

R. F. Wagner, K. J. Myers, D. G. Brown, M. J. Tapiovaara, and A. E. Burgess "Higher-order tasks: Human vs. machine performance", Proc. SPIE 1090, Medical Imaging III: Image Formation, (1 May 1989); https://doi.org/10.1117/12.953203

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