Extraction of tongue carcinoma using genetic algorithm-induced fuzzy clustering and artificial neural network from MR images

A novel hierarchical image segmentation approach has been developed for the extraction of tongue carcinoma from magnetic resonance (MR) images. First, a genetic algorithm (GA)-induced fuzzy clustering is used for initial segmentation of MR images of head and neck. Then these segmented masses are refined to reduce the false-positives using an artificial neural network (ANN)-based symmetry detection and image analysis procedure. The proposed technique is applied to clinical MR images of tongue carcinoma and quantitative evaluations are performed. Experimental results suggest that the proposed approach provides an effective method for tongue carcinoma extraction with high accuracy and minimal user-dependency.