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Proceedings Paper

Comparison of neural network, human, and suboptimal Bayesian performance on a constrained reconstruction task
Author(s): David G. Brown; Mary S. Pastel; Kyle J. Myers; Robert F. Wagner
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Paper Abstract

Neural networks were applied to the task of detecting simulated low contrast lesions in limited-view reconstruction tomography images. Results were compared with those for theoretically derived machine observers and for human observers. Preliminary results indicated improved neural network performance for the small data set on which human observer data had been obtained, but further results for a larger data set give performance generally inferior to the best machine observer.

Paper Details

Date Published: 11 May 1994
PDF: 9 pages
Proc. SPIE 2167, Medical Imaging 1994: Image Processing, (11 May 1994); doi: 10.1117/12.175096
Show Author Affiliations
David G. Brown, Ctr. for Devices and Radiological Health/FDA (United States)
Mary S. Pastel, Ctr. for Devices and Radiological Health/FDA (United States)
Kyle J. Myers, Ctr. for Devices and Radiological Health/FDA (United States)
Robert F. Wagner, Ctr. for Devices and Radiological Health/FDA (United States)


Published in SPIE Proceedings Vol. 2167:
Medical Imaging 1994: Image Processing
Murray H. Loew, Editor(s)

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