Pyramidal neural networking for mammogram tumour pattern recognition
Guoxin Xing, R. Feltham · 1994
There has been much interest in developing neural networks to solve complicated information processing problems such as automatic diagnosis of x-ray mammograms. In New Zealand the authors are investigating a pyramidal neural network and adaptive contrast enhancement image processing technique for developing a knowledge-system for medical image interpretation. In this paper the authors present the pyramidal network architecture with experimental breast cancer tumour pattern mapping results. The pyramidal network configuration has overcome the problem of hidden layer size. To facilitate the learning the authors introduced a novel method of standard coding mechanism by using local overlapping and minimum value thresholding. The outcome of this unique mapping is promising in designing a useful expert system.>