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Preprocess Enhancement of CT Image for Liver Segmentation with Region Growing Algorithm

  • Conference paper

Part of the book series: IFMBE Proceedings ((IFMBE,volume 45))

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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© 2015 Springer International Publishing Switzerland

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Anastácio, R., Mamere, L.R.d.O., Carneiro, P.C., Macedo, T.A.A., Patrocinio, A.C. (2015). Preprocess Enhancement of CT Image for Liver Segmentation with Region Growing Algorithm. In: Lacković, I., Vasic, D. (eds) 6th European Conference of the International Federation for Medical and Biological Engineering. IFMBE Proceedings, vol 45. Springer, Cham. https://doi.org/10.1007/978-3-319-11128-5_34

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  • DOI: https://doi.org/10.1007/978-3-319-11128-5_34

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11127-8

  • Online ISBN: 978-3-319-11128-5

  • eBook Packages: EngineeringEngineering (R0)

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