Mean of means: An automatic liver segmentation algorithm

Laramie Paxton, Yufeng Cao, Kevin Vixie, Yuan Wang, Chaan Ng, Brian Hobbs

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    We present an automatic liver segmentation method that utilizes the time series data in conjunction with the BK graph cut algorithm and uses a novel approach of computing a 'mean of means' for each of the sample healthy and tumor tissue intensities from a set of different tumors. Thus, there is no training process required since these are computed ahead of time using Regions of Interest provided by radiologists. We also use a Gaussian B-spline to fit these two vector means to curves as an approximation for the intensity signals for the healthy and tumor tissues. This method provides a reasonable degree of accuracy for an automatic segmentation scheme, yielding a mean Dice similarity coefficient (DSC) of 73 percent, a relative volume difference (RVD) of 19.5 percent, and a Jaccard Score (JS) of 58.5 percent. The algorithm is simple to implement computationally, and the mean runtime of 24 seconds is short given that no training process is needed.

    Original languageEnglish (US)
    Title of host publication2019 Joint 8th International Conference on Informatics, Electronics and Vision, ICIEV 2019 and 3rd International Conference on Imaging, Vision and Pattern Recognition, icIVPR 2019 with International Conference on Activity and Behavior Computing, ABC 2019
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages1-5
    Number of pages5
    ISBN (Electronic)9781728107868
    DOIs
    StatePublished - May 2019
    EventJoint 8th International Conference on Informatics, Electronics and Vision and 3rd International Conference on Imaging, Vision and Pattern Recognition, ICIEV and icIVPR 2019 - Spokane, United States
    Duration: May 30 2019Jun 2 2019

    Publication series

    Name2019 Joint 8th International Conference on Informatics, Electronics and Vision, ICIEV 2019 and 3rd International Conference on Imaging, Vision and Pattern Recognition, icIVPR 2019 with International Conference on Activity and Behavior Computing, ABC 2019

    Conference

    ConferenceJoint 8th International Conference on Informatics, Electronics and Vision and 3rd International Conference on Imaging, Vision and Pattern Recognition, ICIEV and icIVPR 2019
    Country/TerritoryUnited States
    CitySpokane
    Period5/30/196/2/19

    Keywords

    • Automatic
    • Graph cut
    • Liver segmentation
    • Medical imaging
    • Tumor

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Vision and Pattern Recognition
    • Information Systems
    • Signal Processing
    • Instrumentation

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