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MyelinJ: an ImageJ macro for high throughput analysis of myelinating cultures
Author(s) -
Michael J. Whitehead,
George A. McCanney,
Hugh J. Willison,
Susan C. Barnett
Publication year - 2019
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btz403
Subject(s) - computer science , thresholding , macro , throughput , filter (signal processing) , graphical user interface , software , pattern recognition (psychology) , artificial intelligence , data mining , computer graphics (images) , computer vision , operating system , programming language , image (mathematics) , wireless
MyelinJ is a free user friendly ImageJ macro for high throughput analysis of fluorescent micrographs such as 2D-myelinating cultures and statistical analysis using R. MyelinJ can analyse single images or complex experiments with multiple conditions, where the ggpubr package in R is automatically used for statistical analysis and the production of publication quality graphs. The main outputs are percentage (%) neurite density and % myelination. % neurite density is calculated using the normalize local contrast algorithm, followed by thresholding, to adjust for differences in intensity. For % myelination the myelin sheaths are selected using the Frangi vesselness algorithm, in conjunction with a grey scale morphology filter and the removal of cell bodies using a high intensity mask. MyelinJ uses a simple graphical user interface and user name system for reproducibility and sharing that will be useful to the wider scientific community that study 2D-myelination in vitro.

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