Enhancing Tumor Detection Through ANFIS-Based Clustering in Biomedical Imaging

In Biomedicine, computer software is applied to the medical image for content analysis by MRI scanning for the program. Preprocessing, removal of noise, processing images in order to detect objects and analysis of the images for tumor assessment in terms of shape and volume form part of the MRI based brain tumor detection process. The author of this paper presents a method employing ANFIS models with clustering in order to determine the number of clusters necessary for identifying brain and lymph node tumors. ANFIS improves classification as well as cancer diagnosis and therapy by automating selection and refinement of treated clusters.