Detecting and tracking the tips of fluorescently labeled mitochondria in U2OS cells

Eero Lihavainen, Jarno Mäkelä, Johannes N. Spelbrink, Andre S. Ribeiro

    Tutkimustuotos: KonferenssiartikkeliScientificvertaisarvioitu

    Abstrakti

    We present a method for automatically detecting the tips of fluorescently labeled mitochondria. The method is based on a Random Forest classifier, which is trained on small patches extracted from confocal microscope images of U2OS human osteosarcoma cells. We then adopt a particle tracking framework for tracking the detected tips, and quantify the tracking accuracy on simulated data. Finally, from images of U2OS cells, we quantify changes in mitochondrial mobility in response to the disassembly of microtubules via treatment with Nocodazole. The results show that our approach provides efficient tracking of the tips of mitochondria, and that it enables the detection of disease-associated changes in mitochondrial motility.

    AlkuperäiskieliEnglanti
    OtsikkoImage Analysis and Processing — ICIAP 2015
    Alaotsikko18th International Conference, Genoa, Italy, September 7-11, 2015, Proceedings, Part II
    KustantajaSpringer Verlag
    Sivut363-372
    Sivumäärä10
    Vuosikerta9280
    ISBN (painettu)9783319232331
    DOI - pysyväislinkit
    TilaJulkaistu - 2015
    OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
    TapahtumaINTERNATIONAL CONFERENCE ON IMAGE ANALYSIS AND PROCESSING -
    Kesto: 1 tammik. 1900 → …

    Julkaisusarja

    NimiLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Vuosikerta9280
    ISSN (painettu)0302-9743
    ISSN (elektroninen)1611-3349

    Conference

    ConferenceINTERNATIONAL CONFERENCE ON IMAGE ANALYSIS AND PROCESSING
    Ajanjakso1/01/00 → …

    Julkaisufoorumi-taso

    • Jufo-taso 1

    !!ASJC Scopus subject areas

    • Computer Science(all)
    • Theoretical Computer Science

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