TY - GEN
T1 - Neural network diagnosis of avascular necrosis from magnetic resonance images
AU - Manduca, A.
AU - Christy, P.
AU - Ehman, R.
PY - 1991/12/1
Y1 - 1991/12/1
N2 - Artificial neural networks has been used to diagnose avascular necrosis (AVN) of the femoral head from magnetic resonance images. Multilayer perceptron networks, trained with conjugate gradient optimization, which diagnose AVN from single sagittal images of the femoral head with 100% accuracy on the training data and 97% accuracy on test data has been developed. These networks use only the raw image as input (with minimal preprocessing to average the images down to 32 × 32 size and to scale the input data values) and learn to extract their own features for the diagnosis decision. Various experiments with these networks, whose results are considered to be very encouraging for the use of neural networks in diagnostic radiology, are described.
AB - Artificial neural networks has been used to diagnose avascular necrosis (AVN) of the femoral head from magnetic resonance images. Multilayer perceptron networks, trained with conjugate gradient optimization, which diagnose AVN from single sagittal images of the femoral head with 100% accuracy on the training data and 97% accuracy on test data has been developed. These networks use only the raw image as input (with minimal preprocessing to average the images down to 32 × 32 size and to scale the input data values) and learn to extract their own features for the diagnosis decision. Various experiments with these networks, whose results are considered to be very encouraging for the use of neural networks in diagnostic radiology, are described.
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M3 - Conference contribution
AN - SCOPUS:0026298264
SN - 0780302168
T3 - Proceedings of the Annual Conference on Engineering in Medicine and Biology
SP - 1429
EP - 1431
BT - Proceedings of the Annual Conference on Engineering in Medicine and Biology
PB - Publ by IEEE
T2 - Proceedings of the 13th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Y2 - 31 October 1991 through 3 November 1991
ER -