Literature DB >> 22069299

Three-dimensional segmentation of nuclei and mitotic chromosomes for the study of cell divisions in live Drosophila embryos.

Rambabu Chinta1, Martin Wasser.   

Abstract

Drosophila embryogenesis is an established model to investigate mechanisms and genes related to cell divisions in an intact multicellular organism. Progression through the cell cycle phases can be monitored in vivo using fluorescently labeled fusion proteins and time-lapse microscopy. To measure cellular properties in microscopic images, accurate and fast image segmentation methods are a critical prerequisite. To quantify static and dynamic features of interphase nuclei and mitotic chromosomes, we developed a three-dimensional (3D) segmentation method based on multiple level sets. We tested our method on 3D time-series images of live embryos expressing histone-2Av-green fluorescence protein. Our method is robust to low signal-to-noise ratios inherent to high-speed imaging, fluorescent signals in the cytoplasm, and dynamic changes of shape and texture. Comparisons with manual ground-truth segmentations showed that our method achieves more than 90% accuracy on the object as well as voxel levels and performs consistently throughout all cell cycle phases and developmental stages from syncytial blastoderm to postblastoderm mitotic domains.
Copyright © 2011 International Society for Advancement of Cytometry.

Entities:  

Mesh:

Year:  2011        PMID: 22069299     DOI: 10.1002/cyto.a.21164

Source DB:  PubMed          Journal:  Cytometry A        ISSN: 1552-4922            Impact factor:   4.355


  14 in total

1.  Rapid 3-D delineation of cell nuclei for high-content screening platforms.

Authors:  Arkadiusz Gertych; Zhaoxuan Ma; Jian Tajbakhsh; Adriana Velásquez-Vacca; Beatrice S Knudsen
Journal:  Comput Biol Med       Date:  2015-04-25       Impact factor: 4.589

Review 2.  Basic quantitative morphological methods applied to the central nervous system.

Authors:  Lutz Slomianka
Journal:  J Comp Neurol       Date:  2020-08-01       Impact factor: 3.215

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

Authors:  Tzu-Ching Wu; Xu Wang; Linlin Li; Ye Bu; David M Umulis
Journal:  Sci Rep       Date:  2021-05-10       Impact factor: 4.379

4.  NeuroGPS: automated localization of neurons for brain circuits using L1 minimization model.

Authors:  Tingwei Quan; Ting Zheng; Zhongqing Yang; Wenxiang Ding; Shiwei Li; Jing Li; Hang Zhou; Qingming Luo; Hui Gong; Shaoqun Zeng
Journal:  Sci Rep       Date:  2013       Impact factor: 4.379

5.  Current automated 3D cell detection methods are not a suitable replacement for manual stereologic cell counting.

Authors:  Christoph Schmitz; Brian S Eastwood; Susan J Tappan; Jack R Glaser; Daniel A Peterson; Patrick R Hof
Journal:  Front Neuroanat       Date:  2014-05-07       Impact factor: 3.856

6.  Survey statistics of automated segmentations applied to optical imaging of mammalian cells.

Authors:  Peter Bajcsy; Antonio Cardone; Joe Chalfoun; Michael Halter; Derek Juba; Marcin Kociolek; Michael Majurski; Adele Peskin; Carl Simon; Mylene Simon; Antoine Vandecreme; Mary Brady
Journal:  BMC Bioinformatics       Date:  2015-10-15       Impact factor: 3.169

7.  A novel toolbox to investigate tissue spatial organization applied to the study of the islets of Langerhans.

Authors:  Hoa Tran Thi Nhu; Rafael Arrojo E Drigo; Per-Olof Berggren; Thomas Boudier
Journal:  Sci Rep       Date:  2017-03-17       Impact factor: 4.379

8.  The study of muscle remodeling in Drosophila metamorphosis using in vivo microscopy and bioimage informatics.

Authors:  Rambabu Chinta; Joo Huang Tan; Martin Wasser
Journal:  BMC Bioinformatics       Date:  2012-12-13       Impact factor: 3.169

9.  A generic classification-based method for segmentation of nuclei in 3D images of early embryos.

Authors:  Jaza Gul-Mohammed; Ignacio Arganda-Carreras; Philippe Andrey; Vincent Galy; Thomas Boudier
Journal:  BMC Bioinformatics       Date:  2014-01-14       Impact factor: 3.169

10.  Large-scale localization of touching somas from 3D images using density-peak clustering.

Authors:  Shenghua Cheng; Tingwei Quan; Xiaomao Liu; Shaoqun Zeng
Journal:  BMC Bioinformatics       Date:  2016-09-15       Impact factor: 3.169

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