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ImageSURF: An ImageJ plugin for batch pixel-based image segmentation using random forests


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O'Mara, A, King, AE ORCID: 0000-0003-1792-0965, Vickers, JC ORCID: 0000-0001-5671-4879 and Kirkcaldie, MTK ORCID: 0000-0003-3285-0168 2017 , 'ImageSURF: An ImageJ plugin for batch pixel-based image segmentation using random forests' , Journal of Open Research Software, vol. 5 , pp. 1-7 , doi: 10.5334/jors.172.

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Image segmentation is a necessary step in automated quantitative imaging. ImageSURF is a macro-compatible ImageJ2/FIJI plugin for pixel-based image segmentation that considers a range of image derivatives to train pixel classifiers which are then applied to image sets of any size to produce segmentations without bias in a consistent, transparent and reproducible manner. The plugin is available from ImageJ update site and source code from

Item Type: Article
Authors/Creators:O'Mara, A and King, AE and Vickers, JC and Kirkcaldie, MTK
Keywords: machine learning, image processing, pathology, ImageJ, segmentation, trainable segmentation, binary segmentation, random forests
Journal or Publication Title: Journal of Open Research Software
Publisher: Ubiquity Press Ltd.
ISSN: 2049-9647
DOI / ID Number: 10.5334/jors.172
Copyright Information:

© 2017 The Authors. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0)

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