Title :
Analysis method of mammogram based on neural network with fuzzy reasoning
Author_Institution :
Lab. of Image Process. & Recognition, Shanghai Univ. of Sci. & Technol., China
fDate :
31 Oct-3 Nov 1996
Abstract :
An analysis method for mammograms based on a neural network with fuzzy reasoning is presented. In order to analyse mammograms the image preprocessing is very important. Here, the authors study stripping the tumors from the mammogram based on the principle of maximum gray threshold and the parameters of the tumor are extracted from the tumor. Meanwhile, the membership function of feature parameters and fuzzy rules are deducted according to expert´s knowledge. The rules are used as input parameters of the hybrid neural network which is composed of a fuzzy reasoning cooperative network and a BP net. Finally, four classes of breast disease are classified from the mammograms by the hybrid neural network
Keywords :
diagnostic radiography; feature extraction; fuzzy neural nets; image classification; medical image processing; breast disease classes; feature parameters; fuzzy reasoning cooperative network; fuzzy reasoning neural network; hybrid neural network; image preprocessing; mammogram analysis method; maximum gray threshold; medical diagnostic imaging; membership function; tumor parameters; tumors; Breast cancer; Breast neoplasms; Cancer detection; Diseases; Fuzzy neural networks; Fuzzy reasoning; Fuzzy systems; Image processing; Network synthesis; Neural networks;
Conference_Titel :
Engineering in Medicine and Biology Society, 1996. Bridging Disciplines for Biomedicine. Proceedings of the 18th Annual International Conference of the IEEE
Conference_Location :
Amsterdam
Print_ISBN :
0-7803-3811-1
DOI :
10.1109/IEMBS.1996.652743