Conference Paper

Automatic Liver Segmentation of Contrast Enhanced CT Images Based on Histogram Processing.

DOI: 10.1007/11539087_135 Conference: Advances in Natural Computation, First International Conference, ICNC 2005, Changsha, China, August 27-29, 2005, Proceedings, Part I
Source: DBLP


Pixel values of contrast enhanced computed tomography (CE-CT) images are randomly changed. Also, the middle liver part has
a problem to segregate the liver structure because of similar gray-level values of neighboring organs in the abdomen. In this
paper, an automatic liver segmentation method using histogram processing is proposed for overcoming randomness of CE-CT images
and removing other abdominal organs. Forty CE-CT slices of ten patients were selected to evaluate the proposed method. As
the evaluation measure, the normalized average area and area error rate were used. From the results of experiments, liver
segmentation using histogram process has similar performance as the manual method by medical doctor.

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    • "It is suggested in article [4] that, the error in such results may result in catastrophic mistakes in the whole diagnosis process. Another simple approach towards full automation of segmentation process is by making use of histogram [7]. The liver is largest and fairly homogeneous organ visible in abdominal CT image, which shows liver, Hence the histogram shows a peak, related to pixels of liver area. "

    International Journal of Computer Applications 08/2013; 75(13):6-10. DOI:10.5120/13169-0708
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    • "Different classes of automatic CT liver segmentation methods are reported. The simplest category involves threshold [6] or multi-threshold [7] segmentation applied on the intensity only. The segmentation accuracy achieved by this strategy is rather low, as the intensities inside the liver are neither always homogeneous, neither perfectly discriminative between the liver and other organs. "
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