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Threshold-based segmentation of fluorescent and chromogenic images of microglia, astrocytes and oligodendrocytes in FIJI by Sinead Healy; Jill McMahon; Peter Owens; Peter Dockery; Una FitzGerald is a Neuroscience article available to read on EtoBox.

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## Background: Image segmentation is often imperfect, particularly in complex image sets such z-stack micrographs of slice cultures and there is a need for sufficient details of parameters used in quantitative image analysis to allow independent repeatability and appraisal. ## New method: For the first time, we have critically evaluated, quantified and validated the performance of different segmentation methodologies using z-stack images of ex vivo glial cells. the biovoxxel toolbox plugin, available in fiji, was used to measure the relative quality, accuracy, specificity and sensitivity of 16 global and 9 local threshold automatic thresholding algorithms. ## Results: Automatic thresholding yields improved binary representation of glial cells compared with the conventional user-chosen single threshold approach for confocal z-stacks acquired from ex vivo slice cultures. the performance of threshold algorithms varies considerably in quality, specificity, accuracy and sensitivity with entropy-based thresholds scoring highest for fluorescent staining. ## Comparison with existing methods: We have used the biovoxxel toolbox to correctly and consistently select the best automated threshol

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Author

Sinead Healy; Jill McMahon; Peter Owens; Peter Dockery; Una FitzGerald

Publisher

Elsevier BV

Published

2017

Language

EN

Field

Neuroscience (Life Sciences)