An Ultrasound Image Preprocessing System Using Memetic ANFIS Method

Ultrasound images are corrupted with speckle noise which makes it impossible for diagnosis. A novel memetic based approach to optimize neuro fuzzy system for reducing this speckle noise in sonogram images has been proposed. The system uses a 5 layer feed forward neural network with 5 input parameters representing the 5×5 window pixel. These are the fuzzy values which are optimized by memetic algorithm (MA) and fed into the system as input parameters. The population generations used in the system are optimized fuzzified input parameters. Fuzzification is based on IF THEN rules. The efficiency is improvised on adding weights in between the input and hidden layer. Then, the amplitude is measured. The system is compared with traditional adaptive mean and adaptive weighted mean methods. The results were 32% better and the computation time was less.

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