Review of free software tools for image analysis of fluorescence cell micrographs (original) (raw)
Related papers
BMC Bioinformatics
Background: Manual assessment and evaluation of fluorescent micrograph cell experiments is time-consuming and tedious. Automated segmentation pipelines can ensure efficient and reproducible evaluation and analysis with constant high quality for all images of an experiment. Such cell segmentation approaches are usually validated and rated in comparison to manually annotated micrographs. Nevertheless, manual annotations are prone to errors and display inter-and intra-observer variability which influence the validation results of automated cell segmentation pipelines. Results: We present a new approach to simulate fluorescent cell micrographs that provides an objective ground truth for the validation of cell segmentation methods. The cell simulation was evaluated twofold: (1) An expert observer study shows that the proposed approach generates realistic fluorescent cell micrograph simulations. (2) An automated segmentation pipeline on the simulated fluorescent cell micrographs reproduces segmentation performances of that pipeline on real fluorescent cell micrographs. Conclusion: The proposed simulation approach produces realistic fluorescent cell micrographs with corresponding ground truth. The simulated data is suited to evaluate image segmentation pipelines more efficiently and reproducibly than it is possible on manually annotated real micrographs.
Bioinformatics, 2010
Complete, accurate and reproducible analysis of intracellular foci from fluorescence microscopy image sequences of live cells requires full automation of all processing steps involved: cell segmentation and tracking followed by foci segmentation and pattern analysis. Integrated systems for this purpose are lacking. Results: Extending our previous work in cell segmentation and tracking, we developed a new system for performing fully automated analysis of fluorescent foci in single cells. The system was validated by applying it to two common tasks: intracellular foci counting (in DNA damage repair experiments) and cell-phase identification based on foci pattern analysis (in DNA replication experiments). Experimental results show that the system performs comparably to expert human observers. Thus, it may replace tedious manual analyses for the considered tasks, and enables high-content screening. Availability and implementation: The described system was implemented in MATLAB (The MathWorks, Inc., USA) and compiled to run within the MATLAB environment. The routines together with four sample datasets are available at http://celmia.bigr.nl/. The software is planned for public release, free of charge for noncommercial use, after publication of this article.
2013
Detection and quantification of fluorescently labeled molecules in sub-cellular compartments is a key step in analyzing many cell-biological processes. Pixel-wise colocalization analyses, however, are not always suitable because they do not provide object-specific information and are vulnerable to noise and background fluorescence. Here we present a versatile method for detecting, delineating, and quantifying sub-cellular structures in fluorescence microscopy images. The method is implemented as a freely available, user-friendly plugin for ImageJ and Fiji. It works on both 2D and 3D images, accounts for the microscope optics, computes cell masks, provides sub-pixel accuracy, and can be used on parallel computer clusters. The present method allows both colocalization and shape analyses. We compare it with other colocalization techniques and apply it to studying sub-cellular localization of RAB GTPases and to mitochondria morphology analysis.
Fluorescence Microscopic Image Cell Segmentation
International Journal of Future Computer and Communication, 2012
Apoptosis is a process of Programmed Cell Death (PCD) that is a naturally occurring process in the body. The defective apoptosis process will causes extensive variety of diseases, such as cancer, ischemic damage, and etc. Hence, apoptosis is widely applied in disease analysis and disease treatments. How to segment the cells from a Fluorescence Microscope (FM) image is essential in developing an automatic computer-aided system for Apoptosis detection. In this paper, a Fluorescence Microscopic Image Cell Segmenting (FMICS) system is proposed to cut cells off from an image under fluorescence microscope. The experimental results indicate that the FMICS system provides an impressive performance than the compared methods.
CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation
Source code for biology and medicine, 2013
The application of fluorescence microscopy in cell biology often generates a huge amount of imaging data. Automated whole cell segmentation of such data enables the detection and analysis of individual cells, where a manual delineation is often time consuming, or practically not feasible. Furthermore, compared to manual analysis, automation normally has a higher degree of reproducibility. CELLSEGM, the software presented in this work, is a MATLAB based command line software toolbox providing an automated whole cell segmentation of images showing surface stained cells, acquired by fluorescence microscopy. It has options for both fully automated and semi-automated cell segmentation. Major algorithmic steps are: (i) smoothing, (ii) Hessian-based ridge enhancement, (iii) marker-controlled watershed segmentation, and (iv) feature-based classfication of cell candidates. Using a wide selection of image recordings and code snippets, we demonstrate that CELLSEGM has the ability to detect various types of surface stained cells in 3D. After detection and outlining of individual cells, the cell candidates can be subject to software based analysis, specified and programmed by the end-user, or they can be analyzed by other software tools. A segmentation of tissue samples with appropriate characteristics is also shown to be resolvable in CELLSEGM. The command-line interface of CELLSEGM facilitates scripting of the separate tools, all implemented in MATLAB, offering a high degree of flexibility and tailored workflows for the end-user. The modularity and scripting capabilities of CELLSEGM enable automated workflows and quantitative analysis of microscopic data, suited for high-throughput image based screening.
2009
In the rapidly expanding fields of cellular and molecular biology, fluorescence illumination and observation is becoming one of the techniques of choice to study the localization and dynamics of proteins, organelles, and other cellular compartments, as well as a tracer of intracellular protein trafficking. The automatic analysis of these images and signals in medicine, biotechnology, and chemistry is a challenging and demanding field. Signal-producing procedures by microscopes, spectrometers and other sensors have found their way into wide fields of medicine, biotechnology, economy and environmental analysis. With this arises the problem of the automatic mass analysis of signal information. Signal-interpreting systems which automatically generate the desired target statements from the signals are therefore of compelling necessity. The continuation of mass analysis on the basis of the classical procedures leads to investments of proportions that are not feasible. New procedures and system architectures are therefore required. We will present, based on our flexible image analysis and interpretation system Cell Interpret, new intelligent and automatic image analysis and interpretation procedures. We will demonstrate it in the application of the HEp-2 cell pattern analysis.
PLOS ONE, 2015
We introduce here MATtrack, an open source MATLAB-based computational platform developed to process multi-Tiff files produced by a photo-conversion time lapse protocol for live cell fluorescent microscopy. MATtrack automatically performs a series of steps required for image processing, including extraction and import of numerical values from Multi-Tiff files, red/green image classification using gating parameters, noise filtering, background extraction, contrast stretching and temporal smoothing. MATtrack also integrates a series of algorithms for quantitative image analysis enabling the construction of mean and standard deviation images, clustering and classification of subcellular regions and injection point approximation. In addition, MATtrack features a simple user interface, which enables monitoring of Fluorescent Signal Intensity in multiple Regions of Interest, over time. The latter encapsulates a region growing method to automatically delineate the contours of Regions of Interest selected by the user, and performs background and regional Average Fluorescence Tracking, and automatic plotting. Finally, MATtrack computes convenient visualization and exploration tools including a migration map, which provides an overview of the protein intracellular trajectories and accumulation areas. In conclusion, MATtrack is an open source MATLAB-based software package tailored to facilitate the analysis and visualization of large data files derived from real-time live cell fluorescent microscopy using photoconvertible proteins. It is flexible, user friendly, compatible with Windows, Mac, and Linux, and a wide range of data acquisition software. MATtrack is freely available for download at eleceng.dit.ie/courtney/MATtrack.zip.
Nature Protocols, 2014
Detection and quantification of fluorescently labeled molecules in subcellular compartments is a key step in the analysis of many cell biological processes. pixel-wise colocalization analyses, however, are not always suitable, because they do not provide object-specific information, and they are vulnerable to noise and background fluorescence. Here we present a versatile protocol for a method named 'squassh' (segmentation and quantification of subcellular shapes), which is used for detecting, delineating and quantifying subcellular structures in fluorescence microscopy images. the workflow is implemented in freely available, user-friendly software. It works on both 2D and 3D images, accounts for the microscope optics and for uneven image background, computes cell masks and provides subpixel accuracy. the squassh software enables both colocalization and shape analyses. the protocol can be applied in batch, on desktop computers or computer clusters, and it usually requires <1 min and <5 min for 2D and 3D images, respectively. Basic computer-user skills and some experience with fluorescence microscopy are recommended to successfully use the protocol.
Validation of image processing tools for 3-D fluorescence microscopy
Comptes Rendus Biologies, 2002
We propose a comprehensive treatment of theta microscopy based on dipole emission, which better describes fluorescence emission than the isotropic emission model, as fluorescence emission is often polarized. Formulas describing the point spread function for polarized confocal fluorescence theta microscopy are given. Examples are given and some advantages of polarized theta fluorescence microscopy are presented. To cite this article: O. Haeberlé et al., C. R. Physique 3 (2002) 1445-1450. 2002 Académie des sciences/Éditions scientifiques et médicales Elsevier SAS fluorescence microscopy / reflection microscopy / theta microscopy Microscopie confocale theta polarisée Résumé Nous présentons un modèle pour la microscopie de fluorescence theta basé sur le rayonnement dipolaire, qui décrit mieux le phénomène de fluorescence que le modèle isotropique, car l'émission de fluorescence est souvent polarisée. Les formules décrivant la tache de diffraction pour la microscopie de fluorescence polarisée en montage theta sont données. Des exemples sont donnés, et certains avantages à utiliser la polarisation en microscopie de fluorescence theta sont présentés. Pour citer cet article : O. Haeberlé et al., C. R. Physique 3 (2002) 1445-1450. 2002 Académie des sciences/Éditions scientifiques et médicales Elsevier SAS microscopie de fluorescence / microscopie en réflexion / microscopie theta Version française abrégée En microscopie classique et confocale [1,2], un compromis entre résolution et distance de travail doit être accepté, les objectifs à grande distance de travail ayant une faible ouverture numérique, et donc une faible résolution. Le microscope theta a été proposé pour pallier à cet inconvénient. Il consiste à utiliser deux objectifs de microscope pour l'excitation et la détection, dont les axes optiques sont perpendiculaires [3]. La Fig. 1 en décrit le principe. L'objectif 1 est utilisé pour illuminer le specimen, et la détection se fait au travers de l'objectif 2.