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SEMANTIC ANALYSIS OF BIOLOGICAL IMAGING DATA: CHALLENGES AND OPPORTUNITIES
2007
International Journal of Semantic Computing (IJSC)
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In recent years there has been a tremendous growth in the volume of biological imaging data owing to rapid advances in optical instrumentation, high-speed cameras and fluorescent probes. ...
Microscopic imaging is one of the most common techniques for investigating biological systems. ...
Moreover, test data sets and performance measures need to be developed for objective comparison of different segmentation algorithms. ...
doi:10.1142/s1793351x07000032
fatcat:dfh2qe3u3ffhjo7c2deotxh73i
Fast Globally Optimal Segmentation of Cells in Fluorescence Microscopy Images
[chapter]
2011
Lecture Notes in Computer Science
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Accurate and efficient segmentation of cells in fluorescence microscopy images is of central importance for the quantification of protein expression in high-throughput screening applications. ...
The performance of our approach has been evaluated using fluorescence microscopy images of different cell types. We have also performed a quantitative comparison with previous segmentation approaches. ...
We thank Luis Pedro Coelho (CMU) for help with his software. Support of the BMBF project FANCI (SysTec) is gratefully acknowledged. ...
doi:10.1007/978-3-642-23623-5_81
fatcat:p33dryemgrdchfysc224uhmyoq
Fast Segmentation of Stained Nuclei in Terabyte-Scale, Time Resolved 3D Microscopy Image Stacks
2014
PLoS ONE
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In this contribution we present a fast parallelized segmentation method that is especially suited for the extraction of stained nuclei from microscopy images, e.g., of developing zebrafish embryos. ...
Citation: Stegmaier J, Otte JC, Kobitski A, Bartschat A, Garcia A, et al. (2014) Fast Segmentation of Stained Nuclei in Terabyte-Scale, Time Resolved 3D Microscopy Image Stacks. PLoS ONE 9(2): e90036. ...
In this contribution, we present a new segmentation algorithm that is specifically designed to perform a fast, parallelized extraction of stained nuclei from the raw 3D microscopy images on a usual desktop ...
doi:10.1371/journal.pone.0090036
pmid:24587204
pmcid:PMC3937404
fatcat:5hunpa7k6vc5jgbjthn2x5pesm
Fast automatic quantitative cell replication with fluorescent live cell imaging
2012
BMC Bioinformatics
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Conclusion: A robust automated quantification method of live cell imaging is built to measure the cell replication level, providing a robust quantitative analysis system in fluorescent live cell imaging ...
In addition, the presented unsupervised entropy based cell segmentation for live cell images is demonstrated to be also applicable for nuclear segmentation of IHC tissue images. ...
D = n i=1 ⎛ ⎝ j⊂A f j /#A ⎞ ⎠ /n (1) where n is the number of cells, A is the set of cell locations, and f j is the fluorescence level at location j. ...
doi:10.1186/1471-2105-13-21
pmid:22292799
pmcid:PMC3359210
fatcat:7wtnm3pvhndwnjtseac52eam5y
DeLTA: Automated cell segmentation, tracking, and lineage reconstruction using deep learning
[article]
2019
bioRxiv
pre-print
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Further, the algorithm is fast, with complete analysis of a typical frame containing ~150 cells taking <700msec. ...
Microscopy image analysis is a major bottleneck in quantification of single-cell microscopy data, typically requiring human supervision and curation, which limit both accuracy and throughput. ...
Acknowledgements We thank Nadia Sampaio for her help in generating the mother machine datasets, Vincent Chang for assistance with the yeast data training set, and Daniel Eaton for help with data augmentation ...
doi:10.1101/720615
fatcat:ddreol2byrbtpf7jdc4h47l64q
Reconstructing embryonic development
2011
Genesis
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We review state-of-the-art technology for live imaging, focusing on fluorescence light microscopy techniques for system-level investigations of animal development, and discuss computational approaches ...
Novel approaches to bio-imaging and automated computational image processing allow the design of truly quantitative studies in developmental biology. ...
in this review article. ...
doi:10.1002/dvg.20698
pmid:21140407
fatcat:g6aznif7ivec5nwgakw5zflnha
A Guided Tour of Selected Image Processing and Analysis Methods for Fluorescence and Electron Microscopy
2016
IEEE Journal on Selected Topics in Signal Processing
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Microscopy imaging, including fluorescence microscopy and electron microscopy, has taken a prominent role in life science research and medicine due to its ability to investigate the 3D interior of live ...
In this paper, we present recent advances in fluorescence and electron microscopy and we focus on dedicated image processing and analysis methods required to quantify phenotypes for a limited number but ...
ACKNOWLEDGMENT The authors would like to thank the members of the Inria Serpico Project-Team and of the Bioimage Analysis unit (Institut Pasteur) for their inputs and contributions to some of the ideas ...
doi:10.1109/jstsp.2015.2505402
fatcat:fgbrxtuhsfbobluogllqll6q2e
An automatic method for robust and fast cell detection in bright field images from high-throughput microscopy
2013
BMC Bioinformatics
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Another approach could include the development of a robust and fast performing level set evolution method. ...
[19] developed a method that combined out of focus image acquisition and segmentation by level sets to identify outlines of adherent cells. ...
Availability The code of our pipeline is available as Additional file 1.
Additional file Additional file 1: Matlab code of the presented method. ...
doi:10.1186/1471-2105-14-297
pmid:24090363
pmcid:PMC3850979
fatcat:q2jfzbe4l5gpzorawiyb6ysgyu
Localizer: fast, accurate, open-source, and modular software package for superresolution microscopy
2012
Journal of Biomedical Optics
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Acknowledgments Peter Dedecker thanks the Research-Foundation Flanders (FWO-Vlaanderen) for a postdoctoral fellowship and travel grant. ...
settings and outputting a set of localized positions or one or more computed images. ...
Step 1 necessitates the recording of hundreds or thousands of fluorescence images using standard wide-field fluorescence microscopy, for both stochastic optical fluctuation imaging and the superresolution ...
doi:10.1117/1.jbo.17.12.126008
pmid:23208219
pmcid:PMC3512108
fatcat:cvw3viwdvnbk5ivd52jv75as4q
A Two-Phase Segmentation of Cell Nuclei Using Fast Level Set-Like Algorithms
[chapter]
2009
Lecture Notes in Computer Science
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In the first phase, the image foreground is separated from the background using a fast level set-like algorithm by Nilsson and Heyden [1]. ...
In this paper, we present a novel approach to the cell nucleus segmentation in fluorescence microscope images exploiting the level set framework. The proposed method works in two phases. ...
In the first phase, the image foreground is separated from the background using a fast level set-like algorithm by Nilsson and Heyden. ...
doi:10.1007/978-3-642-02230-2_40
fatcat:udg4nyaedvahlnaoxbejxnhv5i
Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review
2016
IEEE Reviews in Biomedical Engineering
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In this review, we provide a comprehensive summary of the recent state-of-the-art nucleus/cell segmentation approaches on different types of microscopy images including bright-field, phase-contrast, differential ...
Digital pathology and microscopy image analysis is widely used for comprehensive studies of cell morphology or tissue structure. ...
[233] have proposed a fast coupled level set method based on the four color theorem to segment cells in phase-contrast microscopy images, and another efficient level set method is reported in [192] ...
doi:10.1109/rbme.2016.2515127
pmid:26742143
pmcid:PMC5233461
fatcat:hx5ldvsppvgzxk6rdiok7siyvi
Bright Field Microscopy as an Alternative to Whole Cell Fluorescence in Automated Analysis of Macrophage Images
2009
PLoS ONE
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Fluorescence microscopy is the standard tool for detection and analysis of cellular phenomena. ...
Using the popular CellProfiler freeware cell image analysis software mainly targeted for fluorescence microscopy, we validate our method by automatically segmenting low contrast and rather complex shaped ...
We are also grateful to Tarmo Ä ijö for implementing the fluorescent spot detection algorithm.
Author Contributions ...
doi:10.1371/journal.pone.0007497
pmid:19847301
pmcid:PMC2760782
fatcat:itvd4bvoljhtzjnbmwnljfhd54
Tissue Intrinsic Fluorescence Spectra-Based Digital Pathology of Liver Fibrosis by Marker-Controlled Segmentation
2018
Frontiers in Medicine
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Because of its unique feature of spectral profiles depending on tissue types, spectroscopic imaging is a promising tool for accurate evaluation of endogenous fluorophores. ...
We formulated a procedure of internal marker selection where markers were chosen to reflect typical biochemical species in the liver, followed by image segmentation and local morphological feature extraction ...
Using these image sets, a feature detection algorithm was applied to detect key points in the images. ...
doi:10.3389/fmed.2018.00350
pmid:30619861
pmcid:PMC6297145
fatcat:ewzqj3tv5nfqlj3e6ck7c4veia
Semi-automatic 3D morphological reconstruction of neurons with densely branching morphology: Application to retinal AII amacrine cells imaged with multi-photon excitation microscopy
2017
Journal of Neuroscience Methods
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Conclusions: We expect our procedure to be generally useful for morphological reconstruction of neurons filled with fluorescent dyes. 7 MPE microscopy and image acquisition ...
We used whole cell recording to fill AII amacrine cells in rat retinal slices with fluorescent dyes and acquired digital image stacks with multiphoton excitation microscopy. ...
Acknowledgement We thank John Georg Riisdal for contributions to an initial stage of the project. This
34 or the decision to submit the work for publication. ...
doi:10.1016/j.jneumeth.2017.01.008
pmid:28115187
fatcat:6xhhocyf7zhdbfq465borexzy4
Particle methods enable fast and simple approximation of Sobolev gradients in image segmentation
[article]
2014
arXiv
pre-print
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Bio-image analysis is challenging due to inhomogeneous intensity distributions and high levels of noise in the images. ...
We show how particle methods as applied to image segmentation allow for a simple and computationally efficient implementation of Sobolev gradients. ...
Acknowledgements We thank all members of the MOSAIC Group for the many fruitful discussions. Particular thanks go to ...
arXiv:1403.0240v1
fatcat:3gzasz3fdvguzfphul4lfjb4nu
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