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Abstract:
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Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan 807, R.O.C. Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan 807, R.O.C. In this paper, a novel method for designing templates of cellular neural networks (CNNs) is discussed to cancel the image noise. The discrete-time cellular neural network (DTCNN) combining with particle swarm optimization (PSO) is applied to medical image noise cancellation. Computed tomography is familiar diagnosis in medical field, and it is often polluted by outside interference. Based on PSO method, the templates of cellular neural network is optimized to diminish noise interference in polluted medical computed tomography image. The demonstrated examples are presented to illustrate the effective results of the proposed methodology.
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