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Liver MRI segmentation with edge-preserved intensity inhomogeneity correction

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Abstract

The accurate liver segmentation for MRI is challenging because of the intensity inhomogeneity. However, most existing intensity inhomogeneity correction sometimes leads to detail smoothing. In this paper, a novel model is proposed for liver segmentation based on the level set method with edge-preserved intensity inhomogeneity correction (EPIICLS). EPIICLS corrects the intensity inhomogeneity with the minimization of the local entropy. And the edge-preserving filter is applied to compensate the detail smoothing by cooperating with the original image. The intensity inhomogeneity correction works on the internal energy of the level set method, which efficiently makes the level set function automatically approximate the signed distance function. And the edge preservation works on the external energy function, which precisely drives the zero-level curve toward the liver boundaries. Experiment results show that the proposed model leads to better segmentation results.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Nos.61003175, 81071127 and No81600605),the Fundamental Research Funds for the Central Universities, the Research and Development Funds for Shenzhen Science and Technology (No. JCYJ20160608173106220), the Natural Science Foundation of Liaoning Province of China (No. 20170520153), the natural science fund guidance plan of Liaoning province (No.201602228), General Research Project for Liaoning Provincial Education Department of China (No. L2015146) and Clinical Capability Construction Project for Liaoning Provincial Hospitals, Health and Family Planning Commission, Liaoning Province Government of China (No. LNCCC-D23-2015).

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Authors and Affiliations

  1. Department of Biomedical Engineer, Dalian University of Technology, Dalian, 116024, China

    Hui Liu & Pinpin Tang

  2. Second Affiliated Hospital, Dalian Medical University, Dalian, 116027, China

    Dongmei Guo & HaiXia Liu

  3. School of Information Science and Engineering and Institute of Life Sciences, Shandong Normal University, Jinan, 250014, China

    Yuanjie Zheng

  4. Shenzhen University Health Science Center School of Biomedical Engineering, Shenzhen, 518060, China

    Guo Dan

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  1. Hui Liu
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  2. Pinpin Tang
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  3. Dongmei Guo
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  4. HaiXia Liu
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  5. Yuanjie Zheng
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  6. Guo Dan
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Correspondence to Hui Liu.

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Liu, H., Tang, P., Guo, D. et al. Liver MRI segmentation with edge-preserved intensity inhomogeneity correction. SIViP 12, 791–798 (2018). https://doi.org/10.1007/s11760-017-1221-5

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  • DOI: https://doi.org/10.1007/s11760-017-1221-5

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