Decision support in screening mammography

Sean M. Hammond; Ian R. L. Davies; Paul T. Sowden; Jason Davies

doi:10.1117/12.236853

27 March 1996 Decision support in screening mammography

Sean M. Hammond, Ian R. L. Davies, Paul T. Sowden, Jason Davies

Proceedings Volume 2712, Medical Imaging 1996: Image Perception; (1996) https://doi.org/10.1117/12.236853
Event: Medical Imaging 1996, 1996, Newport Beach, CA, United States

Abstract

We are developing a statistical decision support system for use in screening mammography, and here we report on the rationale underlying its design, and on some preliminary tests of the system. A single expert radiologist described 200 mammograms, with known outcome, in terms of 38 critical features. We then compared discriminant function analysis (DFA), logistic regression (LR) and a backpropagation neural network (BNN) on their performance in classifying the 200 mammograms as normal or abnormal. All three approaches achieved greater than 90% correct classification, but DFA had low sensitivity and LR had a 9% miss rate, whereas the BNN detected all the cancers. External evaluation of LR and BNN on a new set of 167 mammograms showed that specificity was still high (greater than 96%) but sensitivity was less than 85%. We propose developing a system combining LR and BNN.

Citation Download Citation

Sean M. Hammond, Ian R. L. Davies, Paul T. Sowden, and Jason Davies "Decision support in screening mammography", Proc. SPIE 2712, Medical Imaging 1996: Image Perception, (27 March 1996); https://doi.org/10.1117/12.236853

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