Segmentation of locally varying numbers of outer retinal layers by a model selection approach

Jelena Novosel, Suzanne Yzer, Koenraad A. Vermeer, Lucas J. Van Vliet

    Research output: Contribution to journalArticleScientificpeer-review

    3 Citations (Scopus)

    Abstract

    Extraction of image-based biomarkers, such as the presence, visibility, or thickness of a certain layer, from 3-D optical coherence tomography data provides relevant clinical information. We present a method to simultaneously determine the number of visible layers in the outer retina and segment them. The method is based on a model selection approach with special attention given to the balance between the quality of a fit and model complexity. This will ensure that a more complex model is selected only if this is sufficiently supported by the data. The performance of the method was evaluated on healthy and retinitis pigmentosa (RP) affected eyes. In addition, the reproducibility of automatic method and manual annotations was evaluated on healthy eyes. Good agreement between the segmentation performed manually by a medical doctor and results obtained from the automatic segmentation was found. The mean unsigned deviation for all outer retinal layers in healthy and RP affected eyes varied between 2.6 and 4.9 μm. The reproducibility of the automatic method was similar to the reproducibility of the manual segmentation. Overall, the method provides a flexible and accurate solution for determining the visibility and location of outer retinal layers and could be used as an aid for the disease diagnosis and monitoring.

    Original languageEnglish
    Article number7847337
    Pages (from-to)1306-1315
    Number of pages10
    JournalIEEE Transactions on Medical Imaging
    Volume36
    Issue number6
    DOIs
    Publication statusPublished - 2017

    Keywords

    • Akaike information criteria
    • Attenuation coefficient
    • Bayesian information criteria
    • Information complexity
    • Maximum likelihood estimation
    • Model selection
    • Retinitis pigmentosa

    Fingerprint Dive into the research topics of 'Segmentation of locally varying numbers of outer retinal layers by a model selection approach'. Together they form a unique fingerprint.

    Cite this