Automatic Detection and Segmentation of Exosomes in Transmission Electron Microscopy

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F16%3A00091584" target="_blank" >RIV/00216224:14330/16:00091584 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-46604-0_23" target="_blank" >http://dx.doi.org/10.1007/978-3-319-46604-0_23</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-46604-0_23" target="_blank" >10.1007/978-3-319-46604-0_23</a>

Result language
angličtina
Original language name
Automatic Detection and Segmentation of Exosomes in Transmission Electron Microscopy
Original language description
We presented a morphological method for automatic detection and segmentation of exosomes in transmission electron microscopy images. The exosome segmentation was 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 %.
Czech name
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Czech description
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Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Computer Vision -- ECCV 2016 Workshops: Amsterdam, The Netherlands, October 8-10 and 15-16, 2016, Proceedings, Part I
ISBN
9783319466033
ISSN
0302-9743
e-ISSN
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Number of pages
8
Pages from-to
318-325
Publisher name
Springer International Publishing
Place of publication
Cham, Switzerland
Event location
Amsterdam, The Netherlands
Event date
Jan 1, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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