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

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

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 tammikuuta 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 → …

Tiivistelmä

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.

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