A review of medical image classification using Adaptive Neuro-Fuzzy Inference System (ANFIS)

Abstract

Image classification is an issue which utilizes image processing, pattern recognition and classification methods. Automatic medical image classification is a progressive area in image classification and it expected to be more developed in the future. Due to this fact that automatic diagnosis which use intelligent methods such as medical image classification can assist pathologists by providing second opinions and reducing their workload. This paper reviews the application of adaptive neuro-fuzzy inference system (ANFIS) as classifier in medical image classification during the past 16 years. A brief comparison with other classifier, main advantages and drawbacks of this classifier are mentioned. ANFIS is a fuzzy inference system (FIS) implemented in the framework of an adaptive fuzzy neural network. It combines the explicit knowledge representation of a FIS with the learning power of artificial neural networks (ANNs). The objective of ANFIS is to integrate the best features of fuzzy systems and neural network.