Automatic extraction of nuclei centroids of mouse embryonic cells from fluorescence microscopy images.

Accurate identification of cell nuclei and their tracking using three dimensional (3D) microscopic images is a demanding task in many biological studies. Manual identification of nuclei centroids from images is an error-prone task, sometimes impossible to accomplish due to low contrast and the prese...

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Autores principales:	Md Khayrul Bashar, Koji Komatsu, Toshihiko Fujimori, Tetsuya J Kobayashi
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f3bf79d71a5741dd80b450fb379d96de
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spelling	oai:doaj.org-article:f3bf79d71a5741dd80b450fb379d96de2021-11-18T07:19:26ZAutomatic extraction of nuclei centroids of mouse embryonic cells from fluorescence microscopy images.1932-620310.1371/journal.pone.0035550https://doaj.org/article/f3bf79d71a5741dd80b450fb379d96de2012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22590505/?tool=EBIhttps://doaj.org/toc/1932-6203Accurate identification of cell nuclei and their tracking using three dimensional (3D) microscopic images is a demanding task in many biological studies. Manual identification of nuclei centroids from images is an error-prone task, sometimes impossible to accomplish due to low contrast and the presence of noise. Nonetheless, only a few methods are available for 3D bioimaging applications, which sharply contrast with 2D analysis, where many methods already exist. In addition, most methods essentially adopt segmentation for which a reliable solution is still unknown, especially for 3D bio-images having juxtaposed cells. In this work, we propose a new method that can directly extract nuclei centroids from fluorescence microscopy images. This method involves three steps: (i) Pre-processing, (ii) Local enhancement, and (iii) Centroid extraction. The first step includes two variations: first variation (Variant-1) uses the whole 3D pre-processed image, whereas the second one (Variant-2) modifies the preprocessed image to the candidate regions or the candidate hybrid image for further processing. At the second step, a multiscale cube filtering is employed in order to locally enhance the pre-processed image. Centroid extraction in the third step consists of three stages. In Stage-1, we compute a local characteristic ratio at every voxel and extract local maxima regions as candidate centroids using a ratio threshold. Stage-2 processing removes spurious centroids from Stage-1 results by analyzing shapes of intensity profiles from the enhanced image. An iterative procedure based on the nearest neighborhood principle is then proposed to combine if there are fragmented nuclei. Both qualitative and quantitative analyses on a set of 100 images of 3D mouse embryo are performed. Investigations reveal a promising achievement of the technique presented in terms of average sensitivity and precision (i.e., 88.04% and 91.30% for Variant-1; 86.19% and 95.00% for Variant-2), when compared with an existing method (86.06% and 90.11%), originally developed for analyzing C. elegans images.Md Khayrul BasharKoji KomatsuToshihiko FujimoriTetsuya J KobayashiPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 5, p e35550 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Md Khayrul Bashar Koji Komatsu Toshihiko Fujimori Tetsuya J Kobayashi Automatic extraction of nuclei centroids of mouse embryonic cells from fluorescence microscopy images.
description	Accurate identification of cell nuclei and their tracking using three dimensional (3D) microscopic images is a demanding task in many biological studies. Manual identification of nuclei centroids from images is an error-prone task, sometimes impossible to accomplish due to low contrast and the presence of noise. Nonetheless, only a few methods are available for 3D bioimaging applications, which sharply contrast with 2D analysis, where many methods already exist. In addition, most methods essentially adopt segmentation for which a reliable solution is still unknown, especially for 3D bio-images having juxtaposed cells. In this work, we propose a new method that can directly extract nuclei centroids from fluorescence microscopy images. This method involves three steps: (i) Pre-processing, (ii) Local enhancement, and (iii) Centroid extraction. The first step includes two variations: first variation (Variant-1) uses the whole 3D pre-processed image, whereas the second one (Variant-2) modifies the preprocessed image to the candidate regions or the candidate hybrid image for further processing. At the second step, a multiscale cube filtering is employed in order to locally enhance the pre-processed image. Centroid extraction in the third step consists of three stages. In Stage-1, we compute a local characteristic ratio at every voxel and extract local maxima regions as candidate centroids using a ratio threshold. Stage-2 processing removes spurious centroids from Stage-1 results by analyzing shapes of intensity profiles from the enhanced image. An iterative procedure based on the nearest neighborhood principle is then proposed to combine if there are fragmented nuclei. Both qualitative and quantitative analyses on a set of 100 images of 3D mouse embryo are performed. Investigations reveal a promising achievement of the technique presented in terms of average sensitivity and precision (i.e., 88.04% and 91.30% for Variant-1; 86.19% and 95.00% for Variant-2), when compared with an existing method (86.06% and 90.11%), originally developed for analyzing C. elegans images.
format	article
author	Md Khayrul Bashar Koji Komatsu Toshihiko Fujimori Tetsuya J Kobayashi
author_facet	Md Khayrul Bashar Koji Komatsu Toshihiko Fujimori Tetsuya J Kobayashi
author_sort	Md Khayrul Bashar
title	Automatic extraction of nuclei centroids of mouse embryonic cells from fluorescence microscopy images.
title_short	Automatic extraction of nuclei centroids of mouse embryonic cells from fluorescence microscopy images.
title_full	Automatic extraction of nuclei centroids of mouse embryonic cells from fluorescence microscopy images.
title_fullStr	Automatic extraction of nuclei centroids of mouse embryonic cells from fluorescence microscopy images.
title_full_unstemmed	Automatic extraction of nuclei centroids of mouse embryonic cells from fluorescence microscopy images.
title_sort	automatic extraction of nuclei centroids of mouse embryonic cells from fluorescence microscopy images.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/f3bf79d71a5741dd80b450fb379d96de
work_keys_str_mv	AT mdkhayrulbashar automaticextractionofnucleicentroidsofmouseembryoniccellsfromfluorescencemicroscopyimages AT kojikomatsu automaticextractionofnucleicentroidsofmouseembryoniccellsfromfluorescencemicroscopyimages AT toshihikofujimori automaticextractionofnucleicentroidsofmouseembryoniccellsfromfluorescencemicroscopyimages AT tetsuyajkobayashi automaticextractionofnucleicentroidsofmouseembryoniccellsfromfluorescencemicroscopyimages
_version_	1718423638247473152

Automatic extraction of nuclei centroids of mouse embryonic cells from fluorescence microscopy images.

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