DocumentCode :
2819142
Title :
A fuzzy inference system combined with wavelet transform for breast mass classification
Author :
Görgel, Pelin ; Sertbas, Ahmet ; Ucan, Osman N.
Author_Institution :
Comput. Eng. Dept., Univ. of Istanbul, Istanbul, Turkey
fYear :
2012
fDate :
3-4 July 2012
Firstpage :
644
Lastpage :
647
Abstract :
This paper proposes a combination of the Fast Wavelet Transform (FWT) and Adaptive Neuro-fuzzy Inference System (ANFIS) methods. The goal is classification of breast masses as benign or malignant by applying this method consecutively to the extracted features of the Region of Interests (ROIs). This study is developed to decrease the number of the missing cancerous regions or unnecessary biopsies. The neuro-fuzzy subtractive clustering classification method achieved a classification accuracy of 85% without using FWT multi-resolution analysis and 92% with FWT. The satisfying results demonstrate that the developed system could help the radiologists for a true diagnosis.
Keywords :
cancer; feature extraction; fuzzy neural nets; fuzzy reasoning; gynaecology; image classification; medical image processing; pattern clustering; radiology; wavelet transforms; ANFIS; FWT; ROI; adaptive neuro-fuzzy inference system methods; biopsies; breast mass classification; cancerous regions; extracted features; fast wavelet transform; neuro-fuzzy subtractive clustering classification method; radiologists; region of interests; Cancer; Computers; Feature extraction; Shape; Training; Wavelet transforms; ANFIS; Breast cancer; fast wavelet transform; mass classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Telecommunications and Signal Processing (TSP), 2012 35th International Conference on
Conference_Location :
Prague
Print_ISBN :
978-1-4673-1117-5
Type :
conf
DOI :
10.1109/TSP.2012.6256376
Filename :
6256376
Link To Document :
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