A fuzzy inference system combined with wavelet transform for breast mass classification
Pelin Görgel, Ahmet Sertbaş, Osman Nuri UCAN · 2012
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.