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Hyperspectral placenta dataset: Hyperspectral image acquisition, annotations, and processing of biological tissues in microsurgical training
The dataset consists of 101 hyperspectral images of four human placentas and six hyperspectral images of contrast dyes (i.e., indocyanine green and red and blue food colorant) that were captured in the range 515–900 nm, step = 5 nm. The hyperspectral images were manually annotated, delineating the k...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10482730/ https://www.ncbi.nlm.nih.gov/pubmed/37691737 http://dx.doi.org/10.1016/j.dib.2023.109526 |
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author | Puustinen, Sami Hyttinen, Joni Elomaa, Antti-Pekka Vrzáková, Hana |
author_facet | Puustinen, Sami Hyttinen, Joni Elomaa, Antti-Pekka Vrzáková, Hana |
author_sort | Puustinen, Sami |
collection | PubMed |
description | The dataset consists of 101 hyperspectral images of four human placentas and six hyperspectral images of contrast dyes (i.e., indocyanine green and red and blue food colorant) that were captured in the range 515–900 nm, step = 5 nm. The hyperspectral images were manually annotated, delineating the key anatomical structures: arteries, veins, stroma, and the umbilical cord. Standard reference materials were used for flat-field correction. The dataset is instrumental for advancing machine-learning algorithms and automated classification of anatomical structures, particularly the classification of superficial and deep vessels and transparent tissue layers. |
format | Online Article Text |
id | pubmed-10482730 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-104827302023-09-08 Hyperspectral placenta dataset: Hyperspectral image acquisition, annotations, and processing of biological tissues in microsurgical training Puustinen, Sami Hyttinen, Joni Elomaa, Antti-Pekka Vrzáková, Hana Data Brief Data Article The dataset consists of 101 hyperspectral images of four human placentas and six hyperspectral images of contrast dyes (i.e., indocyanine green and red and blue food colorant) that were captured in the range 515–900 nm, step = 5 nm. The hyperspectral images were manually annotated, delineating the key anatomical structures: arteries, veins, stroma, and the umbilical cord. Standard reference materials were used for flat-field correction. The dataset is instrumental for advancing machine-learning algorithms and automated classification of anatomical structures, particularly the classification of superficial and deep vessels and transparent tissue layers. Elsevier 2023-08-28 /pmc/articles/PMC10482730/ /pubmed/37691737 http://dx.doi.org/10.1016/j.dib.2023.109526 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Puustinen, Sami Hyttinen, Joni Elomaa, Antti-Pekka Vrzáková, Hana Hyperspectral placenta dataset: Hyperspectral image acquisition, annotations, and processing of biological tissues in microsurgical training |
title | Hyperspectral placenta dataset: Hyperspectral image acquisition, annotations, and processing of biological tissues in microsurgical training |
title_full | Hyperspectral placenta dataset: Hyperspectral image acquisition, annotations, and processing of biological tissues in microsurgical training |
title_fullStr | Hyperspectral placenta dataset: Hyperspectral image acquisition, annotations, and processing of biological tissues in microsurgical training |
title_full_unstemmed | Hyperspectral placenta dataset: Hyperspectral image acquisition, annotations, and processing of biological tissues in microsurgical training |
title_short | Hyperspectral placenta dataset: Hyperspectral image acquisition, annotations, and processing of biological tissues in microsurgical training |
title_sort | hyperspectral placenta dataset: hyperspectral image acquisition, annotations, and processing of biological tissues in microsurgical training |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10482730/ https://www.ncbi.nlm.nih.gov/pubmed/37691737 http://dx.doi.org/10.1016/j.dib.2023.109526 |
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