LIVER INTENSITY DETERMINATION IN THE 3D ABDOMINAL MR IMAGE USING NEURAL NETWORK

Authors

  • Le Trong Ngoc Industrial University of Ho Chi Minh City, 12 Nguyen Van Bao, Go Vap, Ho Chi Minh city, Vietnam

DOI:

https://doi.org/10.15625/2525-2518/54/3A/11963

Keywords:

liver segmentation, MR image, neural network, regression problem.

Abstract

This study presents an approach to automatically identify the liver range intensity in the 3D abdominal MR images using neural network. The proposed scheme consists of three main stages. First, the T1-weighted MR images of the liver in the portal-venous phase are reduced noise by applying the anisotropic diffusion algorithm. The histogram of the 3D reduced image is determined. The function approximation is applied to the computed histogram by using the neural network. The peaks are computed and the peak corresponding to the liver region is determined. This peak plays an important role for a fully automatic liver segmentation. The another salient point of this proposed approach is that the neural network is trained by an effective algorithm called extreme learning machine, this algorithm can offer a good performance with high learning speed in many applications.

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Published

2018-03-20

Issue

Section

Articles