Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/29381
Title: Measurement-oriented deep-learning workflow for improved segmentation of myelin and axons in high-resolution images of human cerebral white matter
Authors: Janjic, Predrag
Petrovski, Kristijan
Dolgoski, Blagoja
Smiley, John
Zdravkovski, Panche 
Pavlovski, Goran 
Jakjovski, Zlatko 
Davcheva, Natasha 
Poposka, Verica 
Stankov, Aleksandar 
Rosoklija, Gorazd
Petrushevska, Gordana 
Kocarev, Ljupco
Dwork, Andrew J
Issue Date: Oct-2019
Publisher: Elsevier BV
Journal: Journal of Neuroscience Methods
Abstract: Standard segmentation of high-contrast electron micrographs (EM) identifies myelin accurately but does not translate easily into measurements of individual axons and their myelin, even in cross-sections of parallel fibers. We describe automated segmentation and measurement of each myelinated axon and its sheath in EMs of arbitrarily oriented human white matter from autopsies.
URI: http://hdl.handle.net/20.500.12188/29381
DOI: 10.1016/j.jneumeth.2019.108373
Appears in Collections:Faculty of Medicine: Journal Articles

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