Brain tumors detection by combination of adaptive neuro-fuzzy inference system and hierarchical clustering

Detection of brain tumors region is a crucial step in automatic detection and treatment systems. This paper presents a hybrid method based on adaptive neuro-fuzzy inference system (ANFIS) and hierarchical clustering to identify location and region of brain tumors. For this purpose, first the center line of brain is detected, and then brain region is divided into non-overlapped blocks. Then, for each block intensity and texture features are extracted. With exploitation symmetry features of two hemispheres of the brain, blocks containing tumor tissue are recognized using ANFIS classifier. Finally by smoothing brain MRI image and exploiting hierarchical clustering, exact region of tumor is specified. The proposed method was tested on Harvard MRI dataset. The obtained performance of the proposed method with criterions accuracy, sensitivity and specificity are 98.1±4.7%, 94.1±3.2% and 98.7±4.9% respectively.