Artificial enlargement of a training set for statistical shape models

Jyrki Lötjönen, Kari Antila, Elina Lamminmäki, J. Koikkalainen, M. Lilja, T. Cootes

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    11 Citations (Scopus)

    Abstract

    Different methods were evaluated to enlarge artificially a training set which is used to build a statistical shape model. In this work, the shape model was built from MR data of 25 subjects and it consisted of ventricles, atria and epicardium. The method adding smooth non-rigid deformations to original training set examples produced the best results. The results indicated also that artificial deformation modes model better an unseen object than an equal number of standard PCA modes generated from original data.
    Original languageEnglish
    Title of host publicationFunctional Imaging and Modeling of the Heart
    Subtitle of host publicationThird International Workshop, FIMH 2005
    PublisherSpringer
    Pages92-101
    ISBN (Electronic)978-3-540-32081-4
    ISBN (Print)978-3-540-26161-2
    DOIs
    Publication statusPublished - 2005
    MoE publication typeA4 Article in a conference publication
    Event3rd International Workshop on Functional Imaging and Modeling of the Heart, FIMH 2005 - Barcelona, Spain
    Duration: 2 Jun 20054 Jun 2005
    Conference number: 3

    Publication series

    SeriesLecture Notes in Computer Science
    Volume3504
    ISSN0302-9743

    Conference

    Conference3rd International Workshop on Functional Imaging and Modeling of the Heart, FIMH 2005
    Abbreviated titleFIMH 2005
    Country/TerritorySpain
    CityBarcelona
    Period2/06/054/06/05

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