Improved and robust detection of cell nuclei from four dimensional fluorescence images.

Segmentation-free direct methods are quite efficient for automated nuclei extraction from high dimensional images. A few such methods do exist but most of them do not ensure algorithmic robustness to parameter and noise variations. In this research, we propose a method based on multiscale adaptive f...

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Autores principales:	Md Khayrul Bashar, Kazuo Yamagata, Tetsuya J Kobayashi
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f785155cbe8e420b8c57636567bbb752
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spelling	oai:doaj.org-article:f785155cbe8e420b8c57636567bbb7522021-11-25T06:08:35ZImproved and robust detection of cell nuclei from four dimensional fluorescence images.1932-620310.1371/journal.pone.0101891https://doaj.org/article/f785155cbe8e420b8c57636567bbb7522014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/25020042/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Segmentation-free direct methods are quite efficient for automated nuclei extraction from high dimensional images. A few such methods do exist but most of them do not ensure algorithmic robustness to parameter and noise variations. In this research, we propose a method based on multiscale adaptive filtering for efficient and robust detection of nuclei centroids from four dimensional (4D) fluorescence images. A temporal feedback mechanism is employed between the enhancement and the initial detection steps of a typical direct method. We estimate the minimum and maximum nuclei diameters from the previous frame and feed back them as filter lengths for multiscale enhancement of the current frame. A radial intensity-gradient function is optimized at positions of initial centroids to estimate all nuclei diameters. This procedure continues for processing subsequent images in the sequence. Above mechanism thus ensures proper enhancement by automated estimation of major parameters. This brings robustness and safeguards the system against additive noises and effects from wrong parameters. Later, the method and its single-scale variant are simplified for further reduction of parameters. The proposed method is then extended for nuclei volume segmentation. The same optimization technique is applied to final centroid positions of the enhanced image and the estimated diameters are projected onto the binary candidate regions to segment nuclei volumes.Our method is finally integrated with a simple sequential tracking approach to establish nuclear trajectories in the 4D space. Experimental evaluations with five image-sequences (each having 271 3D sequential images) corresponding to five different mouse embryos show promising performances of our methods in terms of nuclear detection, segmentation, and tracking. A detail analysis with a sub-sequence of 101 3D images from an embryo reveals that the proposed method can improve the nuclei detection accuracy by 9% over the previous methods, which used inappropriate large valued parameters. Results also confirm that the proposed method and its variants achieve high detection accuracies (> 98% mean F-measure) irrespective of the large variations of filter parameters and noise levels.Md Khayrul BasharKazuo YamagataTetsuya J KobayashiPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 7, p e101891 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Md Khayrul Bashar Kazuo Yamagata Tetsuya J Kobayashi Improved and robust detection of cell nuclei from four dimensional fluorescence images.
description	Segmentation-free direct methods are quite efficient for automated nuclei extraction from high dimensional images. A few such methods do exist but most of them do not ensure algorithmic robustness to parameter and noise variations. In this research, we propose a method based on multiscale adaptive filtering for efficient and robust detection of nuclei centroids from four dimensional (4D) fluorescence images. A temporal feedback mechanism is employed between the enhancement and the initial detection steps of a typical direct method. We estimate the minimum and maximum nuclei diameters from the previous frame and feed back them as filter lengths for multiscale enhancement of the current frame. A radial intensity-gradient function is optimized at positions of initial centroids to estimate all nuclei diameters. This procedure continues for processing subsequent images in the sequence. Above mechanism thus ensures proper enhancement by automated estimation of major parameters. This brings robustness and safeguards the system against additive noises and effects from wrong parameters. Later, the method and its single-scale variant are simplified for further reduction of parameters. The proposed method is then extended for nuclei volume segmentation. The same optimization technique is applied to final centroid positions of the enhanced image and the estimated diameters are projected onto the binary candidate regions to segment nuclei volumes.Our method is finally integrated with a simple sequential tracking approach to establish nuclear trajectories in the 4D space. Experimental evaluations with five image-sequences (each having 271 3D sequential images) corresponding to five different mouse embryos show promising performances of our methods in terms of nuclear detection, segmentation, and tracking. A detail analysis with a sub-sequence of 101 3D images from an embryo reveals that the proposed method can improve the nuclei detection accuracy by 9% over the previous methods, which used inappropriate large valued parameters. Results also confirm that the proposed method and its variants achieve high detection accuracies (> 98% mean F-measure) irrespective of the large variations of filter parameters and noise levels.
format	article
author	Md Khayrul Bashar Kazuo Yamagata Tetsuya J Kobayashi
author_facet	Md Khayrul Bashar Kazuo Yamagata Tetsuya J Kobayashi
author_sort	Md Khayrul Bashar
title	Improved and robust detection of cell nuclei from four dimensional fluorescence images.
title_short	Improved and robust detection of cell nuclei from four dimensional fluorescence images.
title_full	Improved and robust detection of cell nuclei from four dimensional fluorescence images.
title_fullStr	Improved and robust detection of cell nuclei from four dimensional fluorescence images.
title_full_unstemmed	Improved and robust detection of cell nuclei from four dimensional fluorescence images.
title_sort	improved and robust detection of cell nuclei from four dimensional fluorescence images.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/f785155cbe8e420b8c57636567bbb752
work_keys_str_mv	AT mdkhayrulbashar improvedandrobustdetectionofcellnucleifromfourdimensionalfluorescenceimages AT kazuoyamagata improvedandrobustdetectionofcellnucleifromfourdimensionalfluorescenceimages AT tetsuyajkobayashi improvedandrobustdetectionofcellnucleifromfourdimensionalfluorescenceimages
_version_	1718414139794128896

Improved and robust detection of cell nuclei from four dimensional fluorescence images.

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