Automatic wavelet-based 3D nuclei segmentation and analysis for multicellular embryo quantification

Abstract Identification of individual cells in tissues, organs, and in various developing systems is a well-studied problem because it is an essential part of objectively analyzing quantitative images in numerous biological contexts. We developed a size-dependent wavelet-based segmentation method th...

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Autores principales:	Tzu-Ching Wu, Xu Wang, Linlin Li, Ye Bu, David M. Umulis
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/1a5d46dc3e34476fa9ec4dc23c97c925
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spelling	oai:doaj.org-article:1a5d46dc3e34476fa9ec4dc23c97c9252021-12-02T17:01:57ZAutomatic wavelet-based 3D nuclei segmentation and analysis for multicellular embryo quantification10.1038/s41598-021-88966-22045-2322https://doaj.org/article/1a5d46dc3e34476fa9ec4dc23c97c9252021-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-88966-2https://doaj.org/toc/2045-2322Abstract Identification of individual cells in tissues, organs, and in various developing systems is a well-studied problem because it is an essential part of objectively analyzing quantitative images in numerous biological contexts. We developed a size-dependent wavelet-based segmentation method that provides robust segmentation without any preprocessing, filtering or fine-tuning steps, and is robust to the signal-to-noise ratio. The wavelet-based method achieves robust segmentation results with respect to True Positive rate, Precision, and segmentation accuracy compared with other commonly used methods. We applied the segmentation program to zebrafish embryonic development IN TOTO for nuclei segmentation, image registration, and nuclei shape analysis. These new approaches to segmentation provide a means to carry out quantitative patterning analysis with single-cell precision throughout three dimensional tissues and embryos and they have a high tolerance for non-uniform and noisy image data sets.Tzu-Ching WuXu WangLinlin LiYe BuDavid M. UmulisNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Tzu-Ching Wu Xu Wang Linlin Li Ye Bu David M. Umulis Automatic wavelet-based 3D nuclei segmentation and analysis for multicellular embryo quantification
description	Abstract Identification of individual cells in tissues, organs, and in various developing systems is a well-studied problem because it is an essential part of objectively analyzing quantitative images in numerous biological contexts. We developed a size-dependent wavelet-based segmentation method that provides robust segmentation without any preprocessing, filtering or fine-tuning steps, and is robust to the signal-to-noise ratio. The wavelet-based method achieves robust segmentation results with respect to True Positive rate, Precision, and segmentation accuracy compared with other commonly used methods. We applied the segmentation program to zebrafish embryonic development IN TOTO for nuclei segmentation, image registration, and nuclei shape analysis. These new approaches to segmentation provide a means to carry out quantitative patterning analysis with single-cell precision throughout three dimensional tissues and embryos and they have a high tolerance for non-uniform and noisy image data sets.
format	article
author	Tzu-Ching Wu Xu Wang Linlin Li Ye Bu David M. Umulis
author_facet	Tzu-Ching Wu Xu Wang Linlin Li Ye Bu David M. Umulis
author_sort	Tzu-Ching Wu
title	Automatic wavelet-based 3D nuclei segmentation and analysis for multicellular embryo quantification
title_short	Automatic wavelet-based 3D nuclei segmentation and analysis for multicellular embryo quantification
title_full	Automatic wavelet-based 3D nuclei segmentation and analysis for multicellular embryo quantification
title_fullStr	Automatic wavelet-based 3D nuclei segmentation and analysis for multicellular embryo quantification
title_full_unstemmed	Automatic wavelet-based 3D nuclei segmentation and analysis for multicellular embryo quantification
title_sort	automatic wavelet-based 3d nuclei segmentation and analysis for multicellular embryo quantification
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/1a5d46dc3e34476fa9ec4dc23c97c925
work_keys_str_mv	AT tzuchingwu automaticwaveletbased3dnucleisegmentationandanalysisformulticellularembryoquantification AT xuwang automaticwaveletbased3dnucleisegmentationandanalysisformulticellularembryoquantification AT linlinli automaticwaveletbased3dnucleisegmentationandanalysisformulticellularembryoquantification AT yebu automaticwaveletbased3dnucleisegmentationandanalysisformulticellularembryoquantification AT davidmumulis automaticwaveletbased3dnucleisegmentationandanalysisformulticellularembryoquantification
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Automatic wavelet-based 3D nuclei segmentation and analysis for multicellular embryo quantification

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