Searching of Liver Ranges in CT Images by using Genetic Algorithms and Neural Networks

E. Ohta, Y. Mitsukura, M. Fukumi, and N. Akamatsu (Japan)

Keywords

Liver range, Feedback NN, Input position, Subdivision

Abstract

Recently, internal human organ disorders that medical image analysis can be used to detect is being actively re searched. The research, however, has concentrated on the extraction of pulmonary tumors. There is, therefore, little research being done on the extraction of liver tumors. This is because there is no difference between concentrated values of a healthy part and one with a tumor in liver CT images. In this paper, the extraction method of such liver tumors is proposed. Furthermore, in order to demonstrate the effectiveness of the proposed scheme, we show simulation examples, using real CT image data.

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