Psoas major muscle segmentation using higher-order shape prior

Tsutomu Inoue, Yoshiro Kitamura, Yuanzhong Li, Wataru Ito, Hiroshi Ishikawa

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

    5 Citations (Scopus)

    Abstract

    We propose a novel segmentation method based on higher-order graph cuts which enables the utilization of prior knowledge regarding anatomical shapes. We applied the method for segmentation of psoas major muscles by using combinations of logistic curves which representing their shapes. The higher-order terms consisting of variables (voxels) just inside or outside of the estimated shapes are added to the energy function to encourage the segmentation results to fit to the shapes. We verified the effectiveness of the method with 20 abdominal CT images. By comparing the segmentation results to the ground truth data prepared by a clinical expert, we validated the method where it achieved the Jaccard similarity coefficient (JSC) of 75.4 % (right major) and 77.5 % (left major). We also confirmed that the proposed method worked well for thick CT images.

    Original languageEnglish
    Title of host publicationMedical Computer Vision: Algorithms for Big Data - International Workshop, MCV 2015 and Held in Conjunction with MICCAI 2015, Revised Selected Papers
    PublisherSpringer Verlag
    Pages116-124
    Number of pages9
    Volume9601
    ISBN (Print)9783319420158
    DOIs
    Publication statusPublished - 2016
    EventInternational Workshop on Medical Image Computing for Computer Assisted Intervention, 2015 MICCAI - Germany, Germany
    Duration: 2015 Oct 92015 Oct 9

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume9601
    ISSN (Print)03029743
    ISSN (Electronic)16113349

    Other

    OtherInternational Workshop on Medical Image Computing for Computer Assisted Intervention, 2015 MICCAI
    CountryGermany
    CityGermany
    Period15/10/915/10/9

    Keywords

    • Abdominal CT images
    • Graph cuts
    • Higher-order potential
    • Psoas major muscle

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Computer Science(all)

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  • Cite this

    Inoue, T., Kitamura, Y., Li, Y., Ito, W., & Ishikawa, H. (2016). Psoas major muscle segmentation using higher-order shape prior. In Medical Computer Vision: Algorithms for Big Data - International Workshop, MCV 2015 and Held in Conjunction with MICCAI 2015, Revised Selected Papers (Vol. 9601, pp. 116-124). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9601). Springer Verlag. https://doi.org/10.1007/978-3-319-42016-5_11