Abstract
This paper intends to enhance the image for the next usage of region growing technique for segmenting the region of liver away from other organs. The approach depends on a preprocessing phase to enhance the appearance of the boundaries of the liver. This is performed using contrast stretching and some morphological operations to prepare the image for next segmentation phase. The approach starts with combining Otsu’s global thresholding with dilation and erosion to remove image annotation and machine’s bed. The second step of image preparation is to connect ribs, and apply filters to enhance image and deepen liver boundaries. The combined filters are contrast stretching and texture filters. The last step is to use a simple region growing technique, which has low computational cost, but ignored for its low accuracy. The proposed approach is appropriate for many images, where liver could not be separated before, because of the similarity of the intensity with other close organs. A set of 44 images taken in pre-contrast phase, were used to test the approach. Validating the approach has been done using similarity index. The experimental results, show that the overall accuracy offered by the proposed approach results in 91.3 % accuracy.
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Mostafa, A., Elfattah, M.A., Fouad, A., Hassanien, A.E., Hefny, H. (2016). Enhanced Region Growing Segmentation for CT Liver Images. In: Gaber, T., Hassanien, A., El-Bendary, N., Dey, N. (eds) The 1st International Conference on Advanced Intelligent System and Informatics (AISI2015), November 28-30, 2015, Beni Suef, Egypt. Advances in Intelligent Systems and Computing, vol 407. Springer, Cham. https://doi.org/10.1007/978-3-319-26690-9_11
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DOI: https://doi.org/10.1007/978-3-319-26690-9_11
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