Fuzzy C-means clustering-based multilayer perceptron neural network for liver CT images automatic segmentation | IEEE Conference Publication | IEEE Xplore

Fuzzy C-means clustering-based multilayer perceptron neural network for liver CT images automatic segmentation


Abstract:

A new liver segmentation algorithm is proposed. First, the threshold method was used to remove the ribs and spines in the initial image, and the fuzzy C-means clustering ...Show More

Abstract:

A new liver segmentation algorithm is proposed. First, the threshold method was used to remove the ribs and spines in the initial image, and the fuzzy C-means clustering algorithm and morphological reconstruction filtering were used to segment the initial liver CT image. Then the multilayer perceptron neural network was trained by the segmentation result of initial image with the back-propagation algorithm. The adjacent slice CT image was segmented with the trained multilayer perceptron neural network. Last, morphological reconstruction filtering was used to smooth the contour of the liver edge. The experimental results show that the proposed algorithm can effectively segment the livers from CT images, despite the gray level similarity of adjacent organs and different gray level of tumors in the liver.
Date of Conference: 26-28 May 2010
Date Added to IEEE Xplore: 01 July 2010
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Conference Location: Xuzhou

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