Preprocess enhancement of CT image for liver segmentation with region growing algorithm

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Abstract

Liver cancer, although not being among the most frequent type of cancer in Brazil, but is considered of high complexity to be diagnosed and treated. In order to get a high hit rate of liver segmentation in CT images with the algorithm of region growing are compared several preprocess enhancement techniques, which are: contrast stretching, gamma transformation, laplacian operator, sobel operator. As the result, the better technique is the gamma transformation, reaching 99.99% of correct rate from exam 1, and 78.04% of correct rate from exam 2 (doing comparison with manual segmentation) and using mean squared error rate on same technique, was observed 0.33 for exam 1 and for exam 2 was of 12.05. Doing the comparison of this techniques for enhancement of CT images can be observed which one is better for do the enhancement of liver CT images before the use of segmentation technique, and for slices which radiological contrast reached a great performance.

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Anastácio, R., Leticia, L. R., Carneiro, P. C., Macedo, T. A. A., & Patrocinio, A. C. (2015). Preprocess enhancement of CT image for liver segmentation with region growing algorithm. In IFMBE Proceedings (Vol. 45, pp. 134–137). Springer Verlag. https://doi.org/10.1007/978-3-319-11128-5_34

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