Automatic Detection and Segmentation of Exosomes in Transmission Electron Microscopy
Abstract
Exosomes are nanosized, cell-derived vesicles that appear in different biological fluids. They attract a growing interest of the researcher community due to their important role in intercellular communication. An easy to use and reliable method for their quantification and characterization at the single-vesicle level is tremendously needed to help evaluating exosomal preparations in research as well as clinical studies. In this paper, we present a morphological method for automatic detection and segmentation of exosomes in transmission electron microscopy images. The exosome segmentation is carried out using morphological seeded watershed on gradient magnitude image, with the seeds established by applying a series of hysteresis thresholdings, followed by morphological filtering and cluster splitting. We tested the method on a diverse image data set, yielding the detection performance of slightly over 80 %.
Cite
Text
Stepka et al. "Automatic Detection and Segmentation of Exosomes in Transmission Electron Microscopy." European Conference on Computer Vision, 2016. doi:10.1007/978-3-319-46604-0_23Markdown
[Stepka et al. "Automatic Detection and Segmentation of Exosomes in Transmission Electron Microscopy." European Conference on Computer Vision, 2016.](https://mlanthology.org/eccv/2016/stepka2016eccv-automatic/) doi:10.1007/978-3-319-46604-0_23BibTeX
@inproceedings{stepka2016eccv-automatic,
title = {{Automatic Detection and Segmentation of Exosomes in Transmission Electron Microscopy}},
author = {Stepka, Karel and Maska, Martin and Pálenik, Jakub Jozef and Pospíchalová, Vendula and Kotrbová, Anna and Ilkovics, Ladislav and Klemová, Dobromila and Hampl, Ales and Bryja, Vítezslav and Matula, Pavel},
booktitle = {European Conference on Computer Vision},
year = {2016},
pages = {318-325},
doi = {10.1007/978-3-319-46604-0_23},
url = {https://mlanthology.org/eccv/2016/stepka2016eccv-automatic/}
}