EXACT: a collaboration toolset for algorithm-aided annotation of images with annotation version control

Abstract In many research areas, scientific progress is accelerated by multidisciplinary access to image data and their interdisciplinary annotation. However, keeping track of these annotations to ensure a high-quality multi-purpose data set is a challenging and labour intensive task. We developed t...

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Autores principales:	Christian Marzahl, Marc Aubreville, Christof A. Bertram, Jennifer Maier, Christian Bergler, Christine Kröger, Jörn Voigt, Katharina Breininger, Robert Klopfleisch, Andreas Maier
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/dae5d790f0594699940a3224be15d42e
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spelling	oai:doaj.org-article:dae5d790f0594699940a3224be15d42e2021-12-02T16:23:14ZEXACT: a collaboration toolset for algorithm-aided annotation of images with annotation version control10.1038/s41598-021-83827-42045-2322https://doaj.org/article/dae5d790f0594699940a3224be15d42e2021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-83827-4https://doaj.org/toc/2045-2322Abstract In many research areas, scientific progress is accelerated by multidisciplinary access to image data and their interdisciplinary annotation. However, keeping track of these annotations to ensure a high-quality multi-purpose data set is a challenging and labour intensive task. We developed the open-source online platform EXACT (EXpert Algorithm Collaboration Tool) that enables the collaborative interdisciplinary analysis of images from different domains online and offline. EXACT supports multi-gigapixel medical whole slide images as well as image series with thousands of images. The software utilises a flexible plugin system that can be adapted to diverse applications such as counting mitotic figures with a screening mode, finding false annotations on a novel validation view, or using the latest deep learning image analysis technologies. This is combined with a version control system which makes it possible to keep track of changes in the data sets and, for example, to link the results of deep learning experiments to specific data set versions. EXACT is freely available and has already been successfully applied to a broad range of annotation tasks, including highly diverse applications like deep learning supported cytology scoring, interdisciplinary multi-centre whole slide image tumour annotation, and highly specialised whale sound spectroscopy clustering.Christian MarzahlMarc AubrevilleChristof A. BertramJennifer MaierChristian BerglerChristine KrögerJörn VoigtKatharina BreiningerRobert KlopfleischAndreas MaierNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Christian Marzahl Marc Aubreville Christof A. Bertram Jennifer Maier Christian Bergler Christine Kröger Jörn Voigt Katharina Breininger Robert Klopfleisch Andreas Maier EXACT: a collaboration toolset for algorithm-aided annotation of images with annotation version control
description	Abstract In many research areas, scientific progress is accelerated by multidisciplinary access to image data and their interdisciplinary annotation. However, keeping track of these annotations to ensure a high-quality multi-purpose data set is a challenging and labour intensive task. We developed the open-source online platform EXACT (EXpert Algorithm Collaboration Tool) that enables the collaborative interdisciplinary analysis of images from different domains online and offline. EXACT supports multi-gigapixel medical whole slide images as well as image series with thousands of images. The software utilises a flexible plugin system that can be adapted to diverse applications such as counting mitotic figures with a screening mode, finding false annotations on a novel validation view, or using the latest deep learning image analysis technologies. This is combined with a version control system which makes it possible to keep track of changes in the data sets and, for example, to link the results of deep learning experiments to specific data set versions. EXACT is freely available and has already been successfully applied to a broad range of annotation tasks, including highly diverse applications like deep learning supported cytology scoring, interdisciplinary multi-centre whole slide image tumour annotation, and highly specialised whale sound spectroscopy clustering.
format	article
author	Christian Marzahl Marc Aubreville Christof A. Bertram Jennifer Maier Christian Bergler Christine Kröger Jörn Voigt Katharina Breininger Robert Klopfleisch Andreas Maier
author_facet	Christian Marzahl Marc Aubreville Christof A. Bertram Jennifer Maier Christian Bergler Christine Kröger Jörn Voigt Katharina Breininger Robert Klopfleisch Andreas Maier
author_sort	Christian Marzahl
title	EXACT: a collaboration toolset for algorithm-aided annotation of images with annotation version control
title_short	EXACT: a collaboration toolset for algorithm-aided annotation of images with annotation version control
title_full	EXACT: a collaboration toolset for algorithm-aided annotation of images with annotation version control
title_fullStr	EXACT: a collaboration toolset for algorithm-aided annotation of images with annotation version control
title_full_unstemmed	EXACT: a collaboration toolset for algorithm-aided annotation of images with annotation version control
title_sort	exact: a collaboration toolset for algorithm-aided annotation of images with annotation version control
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/dae5d790f0594699940a3224be15d42e
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EXACT: a collaboration toolset for algorithm-aided annotation of images with annotation version control

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