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HISTOBREAST, a collection of brightfield microscopy images of Haematoxylin and Eosin stained breast tissue

Modern histopathology workflows rely on the digitization of histology slides. The quality of the resulting digital representations, in the form of histology slide image mosaics, depends on various specific acquisition conditions and on the image processing steps that underlie the generation of the f...

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Autores principales: Buga, Roxana M., Totu, Tiberiu, Dumitru, Adrian, Costache, Mariana, Floroiu, Iustin, Sladoje, Nataša, Stanciu, Stefan G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7275059/
https://www.ncbi.nlm.nih.gov/pubmed/32503988
http://dx.doi.org/10.1038/s41597-020-0500-0
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author Buga, Roxana M.
Totu, Tiberiu
Dumitru, Adrian
Costache, Mariana
Floroiu, Iustin
Sladoje, Nataša
Stanciu, Stefan G.
author_facet Buga, Roxana M.
Totu, Tiberiu
Dumitru, Adrian
Costache, Mariana
Floroiu, Iustin
Sladoje, Nataša
Stanciu, Stefan G.
author_sort Buga, Roxana M.
collection PubMed
description Modern histopathology workflows rely on the digitization of histology slides. The quality of the resulting digital representations, in the form of histology slide image mosaics, depends on various specific acquisition conditions and on the image processing steps that underlie the generation of the final mosaic, e.g. registration and blending of the contained image tiles. We introduce HISTOBREAST, an extensive collection of brightfield microscopy images that we collected in a principled manner under different acquisition conditions on Haematoxylin - Eosin (H&E) stained breast tissue. HISTOBREAST is comprised of neighbour image tiles and ensemble of mosaics composed from different combinations of the available image tiles, exhibiting progressively degraded quality levels. HISTOBREAST can be used to benchmark image processing and computer vision techniques with respect to their robustness to image modifications specific to brightfield microscopy of H&E stained tissues. Furthermore, HISTOBREAST can serve in the development of new image processing methods, with the purpose of ensuring robustness to typical image artefacts that raise interpretation problems for expert histopathologists and affect the results of computerized image analysis.
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spelling pubmed-72750592020-06-16 HISTOBREAST, a collection of brightfield microscopy images of Haematoxylin and Eosin stained breast tissue Buga, Roxana M. Totu, Tiberiu Dumitru, Adrian Costache, Mariana Floroiu, Iustin Sladoje, Nataša Stanciu, Stefan G. Sci Data Data Descriptor Modern histopathology workflows rely on the digitization of histology slides. The quality of the resulting digital representations, in the form of histology slide image mosaics, depends on various specific acquisition conditions and on the image processing steps that underlie the generation of the final mosaic, e.g. registration and blending of the contained image tiles. We introduce HISTOBREAST, an extensive collection of brightfield microscopy images that we collected in a principled manner under different acquisition conditions on Haematoxylin - Eosin (H&E) stained breast tissue. HISTOBREAST is comprised of neighbour image tiles and ensemble of mosaics composed from different combinations of the available image tiles, exhibiting progressively degraded quality levels. HISTOBREAST can be used to benchmark image processing and computer vision techniques with respect to their robustness to image modifications specific to brightfield microscopy of H&E stained tissues. Furthermore, HISTOBREAST can serve in the development of new image processing methods, with the purpose of ensuring robustness to typical image artefacts that raise interpretation problems for expert histopathologists and affect the results of computerized image analysis. Nature Publishing Group UK 2020-06-05 /pmc/articles/PMC7275059/ /pubmed/32503988 http://dx.doi.org/10.1038/s41597-020-0500-0 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article.
spellingShingle Data Descriptor
Buga, Roxana M.
Totu, Tiberiu
Dumitru, Adrian
Costache, Mariana
Floroiu, Iustin
Sladoje, Nataša
Stanciu, Stefan G.
HISTOBREAST, a collection of brightfield microscopy images of Haematoxylin and Eosin stained breast tissue
title HISTOBREAST, a collection of brightfield microscopy images of Haematoxylin and Eosin stained breast tissue
title_full HISTOBREAST, a collection of brightfield microscopy images of Haematoxylin and Eosin stained breast tissue
title_fullStr HISTOBREAST, a collection of brightfield microscopy images of Haematoxylin and Eosin stained breast tissue
title_full_unstemmed HISTOBREAST, a collection of brightfield microscopy images of Haematoxylin and Eosin stained breast tissue
title_short HISTOBREAST, a collection of brightfield microscopy images of Haematoxylin and Eosin stained breast tissue
title_sort histobreast, a collection of brightfield microscopy images of haematoxylin and eosin stained breast tissue
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7275059/
https://www.ncbi.nlm.nih.gov/pubmed/32503988
http://dx.doi.org/10.1038/s41597-020-0500-0
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