Progressive label fusion framework for multi-atlas segmentation by dictionary evolution

Yantao Song, Guorong Wu, Quansen Sun, Khosro Bahrami, Chunming Li, Dinggang Shen

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

    11 Citations (Scopus)

    Abstract

    Accurate segmentation of anatomical structures in medical images is very important in neuroscience studies. Recently, multi-atlas patch-based label fusion methods have achieved many successes, which generally represent each target patch from an atlas patch dictionary in the image domain and then predict the latent label by directly applying the estimated representation coefficients in the label domain. However, due to the large gap between these two domains, the estimated representation coefficients in the image domain may not stay optimal for the label fusion. To overcome this dilemma, we propose a novel label fusion framework to make the weighting coefficients eventually to be optimal for the label fusion by progressively constructing a dynamic dictionary in a layer-by-layer manner, where a sequence of intermediate patch dictionaries gradually encode the transition from the patch representation coefficients in image domain to the optimal weights for label fusion. Our proposed framework is general to augment the label fusion performance of the current state-of-the-art methods. In our experiments, we apply our proposed method to hippocampus segmentation on ADNI dataset and achieve more accurate labeling results, compared to the counterpart methods with single-layer dictionary.

    Original languageEnglish
    Title of host publicationMedical Image Computing and Computer-Assisted Intervention – MICCAI 2015 - 18th International Conference, Proceedings
    EditorsAlejandro F. Frangi, Nassir Navab, Joachim Hornegger, William M. Wells
    PublisherSpringer Verlag
    Pages190-197
    Number of pages8
    ISBN (Print)9783319245737
    DOIs
    Publication statusPublished - 2015
    Event18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015 - Munich, Germany
    Duration: 2015 Oct 52015 Oct 9

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume9351
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Other

    Other18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015
    Country/TerritoryGermany
    CityMunich
    Period15/10/515/10/9

    Bibliographical note

    Publisher Copyright:
    © Springer International Publishing Switzerland 2015.

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • General Computer Science

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