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Effective Reconstructive Ultrasound Images Using Hopfield Aritificial Neural Network

S. Suganyadevi, B. Mahalakshmi

Abstract


Digital image processing is a wide area and it is used for large applications. One of the major application areas of digital image processing is medicine industry. Medicine industries are highly improved in analyzing medical images, especially in the ultrasound medical images. These images are used to determine the conditions of inner organs like abdominal organs, heart, breast, muscles, tendons, arteries and veins. But in an ultrasound imaging speckle noise shows its presence while doing the visualization process like image acquisition or restoration processing. Lots of techniques are continuously established to this problem. Hence this paper proposes the study of Wavelet Network (WN) and neural network for efficient reconstruction of ultrasound medical images. The Hopfield Artificial Neural Networking (H-ANN) reconstructs high qualified images with minimal time. The performance of these techniques is measured by the statistical quantity parameters like CNR, PSNR, &RMSE.


Keywords


Wavelet Network, Speckle Noise Reconstruction, H-ANN, CNR&RMSE.

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References


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