Decision-making differences: novices, experts, and a neural network

David Manning; Sam Bunting; John Leach

doi:10.1117/12.383107

14 April 2000 Decision-making differences: novices, experts, and a neural network

David Manning, Sam Bunting, John Leach

Proceedings Volume 3981, Medical Imaging 2000: Image Perception and Performance; (2000) https://doi.org/10.1117/12.383107
Event: Medical Imaging 2000, 2000, San Diego, CA, United States

Abstract

We investigated the decision making performance of trained radiographers, novice radiographers and a neural network in the detection of fractures. Ground truth was established by the independent agreement of experienced radiologists for 740 single view digitized radiographs of the wrist. The images were categorized into negatives and positives; 520 of these were used to train the back propagation, three layer neural network in a supervised mode, and the remainder were used to create a test bank. The test was presented to 20 novice observers, 12 experienced radiographers trained in the detection of skeletal trauma and then to the trained neural network. ROC Az values for all the decision makers were not significantly different (p > 0.1) but there were significant differences in the values of True Positive and True Negative Fractions. The neural network showed a greater aptitude for distinguishing the normals. By filtering the neural net decisions through the human data we simulated the effect of assisted reporting. Results suggest that if fracture prevalence is very low in a population, a neural network demonstrating high specificity may have utility in reducing the number of images which must be reviewed by human experts.

Citation Download Citation

David Manning, Sam Bunting, and John Leach "Decision-making differences: novices, experts, and a neural network", Proc. SPIE 3981, Medical Imaging 2000: Image Perception and Performance, (14 April 2000); https://doi.org/10.1117/12.383107

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available