An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset

An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset

Measurement(s) regional part of brain • T2 (Observed)-Weighted Imaging Technology Type(s) Image Segmentation Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.14039327

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Autores principales: Kelly Payette, Priscille de Dumast, Hamza Kebiri, Ivan Ezhov, Johannes C. Paetzold, Suprosanna Shit, Asim Iqbal, Romesa Khan, Raimund Kottke, Patrice Grehten, Hui Ji, Levente Lanczi, Marianna Nagy, Monika Beresova, Thi Dao Nguyen, Giancarlo Natalucci, Theofanis Karayannis, Bjoern Menze, Meritxell Bach Cuadra, Andras Jakab
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/955b4c4a372743dc811da7c038c1a140
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spelling oai:doaj.org-article:955b4c4a372743dc811da7c038c1a1402021-12-02T18:33:59ZAn automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset10.1038/s41597-021-00946-32052-4463https://doaj.org/article/955b4c4a372743dc811da7c038c1a1402021-07-01T00:00:00Zhttps://doi.org/10.1038/s41597-021-00946-3https://doaj.org/toc/2052-4463Measurement(s) regional part of brain • T2 (Observed)-Weighted Imaging Technology Type(s) Image Segmentation Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.14039327Kelly PayettePriscille de DumastHamza KebiriIvan EzhovJohannes C. PaetzoldSuprosanna ShitAsim IqbalRomesa KhanRaimund KottkePatrice GrehtenHui JiLevente LancziMarianna NagyMonika BeresovaThi Dao NguyenGiancarlo NatalucciTheofanis KarayannisBjoern MenzeMeritxell Bach CuadraAndras JakabNature PortfolioarticleScienceQENScientific Data, Vol 8, Iss 1, Pp 1-14 (2021)
institution DOAJ
collection DOAJ
language EN
topic Science
Q
spellingShingle Science
Q
Kelly Payette
Priscille de Dumast
Hamza Kebiri
Ivan Ezhov
Johannes C. Paetzold
Suprosanna Shit
Asim Iqbal
Romesa Khan
Raimund Kottke
Patrice Grehten
Hui Ji
Levente Lanczi
Marianna Nagy
Monika Beresova
Thi Dao Nguyen
Giancarlo Natalucci
Theofanis Karayannis
Bjoern Menze
Meritxell Bach Cuadra
Andras Jakab
An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset
description Measurement(s) regional part of brain • T2 (Observed)-Weighted Imaging Technology Type(s) Image Segmentation Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.14039327
format article
author Kelly Payette
Priscille de Dumast
Hamza Kebiri
Ivan Ezhov
Johannes C. Paetzold
Suprosanna Shit
Asim Iqbal
Romesa Khan
Raimund Kottke
Patrice Grehten
Hui Ji
Levente Lanczi
Marianna Nagy
Monika Beresova
Thi Dao Nguyen
Giancarlo Natalucci
Theofanis Karayannis
Bjoern Menze
Meritxell Bach Cuadra
Andras Jakab
author_facet Kelly Payette
Priscille de Dumast
Hamza Kebiri
Ivan Ezhov
Johannes C. Paetzold
Suprosanna Shit
Asim Iqbal
Romesa Khan
Raimund Kottke
Patrice Grehten
Hui Ji
Levente Lanczi
Marianna Nagy
Monika Beresova
Thi Dao Nguyen
Giancarlo Natalucci
Theofanis Karayannis
Bjoern Menze
Meritxell Bach Cuadra
Andras Jakab
author_sort Kelly Payette
title An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset
title_short An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset
title_full An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset
title_fullStr An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset
title_full_unstemmed An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset
title_sort automatic multi-tissue human fetal brain segmentation benchmark using the fetal tissue annotation dataset
publisher Nature Portfolio
publishDate 2021
url https://doaj.org/article/955b4c4a372743dc811da7c038c1a140
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