A Fuzzy Inference System Combined with Wavelet Transform for Breast Mass Classification


Gorgel P. , Sertbas A. , Ucan O. N.

35th International Conference on Telecommunications and Signal Processing (TSP), Prague, Czech Republic, 3 - 04 July 2012, pp.644-647 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/tsp.2012.6256376
  • City: Prague
  • Country: Czech Republic
  • Page Numbers: pp.644-647

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 neurofuzzy subtractive clustering classification method achieved a classification accuracy of 85% without using FWT multiresolution analysis and 92% with FWT. The satisfying results demonstrate that the developed system could help the radiologists for a true diagnosis.