| 1. |
- Allalou, Amin, 1981-, et al.
(author)
-
BlobFinder, a tool for fluorescence microscopy image cytometry
- 2009
-
In: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607 .- 1872-7565. ; 94:1, s. 58-65
-
Journal article (peer-reviewed)abstract
- Images can be acquired at high rates with modern fluorescence microscopy hardware, giving rise to a demand for high-speed analysis of image data. Digital image cytometry, i.e., automated measurements and extraction of quantitative data from images of cells, provides valuable information for many types of biomedical analysis. There exists a number of different image analysis software packages that can be programmed to perform a wide array of useful measurements. However, the multi-application capability often compromises the simplicity of the tool. Also, the gain in speed of analysis is often compromised by time spent learning complicated software. We provide a free software called BlobFinder that is intended for a limited type of application, making it easy to use, easy to learn and optimized for its particular task. BlobFinder can perform batch processing of image data and quantify as well as localize cells and point like source signals in fluorescence microscopy images, e.g., from FISH, in situ PLA and padlock probing, in a fast and easy way.
|
|
| 2. |
- Allalou, Amin, et al.
(author)
-
Image Based Measurements of Single Cell mtDNA Mutation Load
- 2007
-
In: Image Analysis, Proceedings. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 9783540730392 ; , s. 631-640
-
Conference paper (peer-reviewed)abstract
- Cell cultures as well as cells in tissue always display a certain degree of variability, and measurements based on cell averages will miss important information contained in a heterogeneous population. This paper presents automated methods for image based measurements of mitochondiral DNA (mtDNA) mutations in individual cells. The mitochondria are present in the cell’s cytoplasm, and each cytoplasm has to be delineated. Three different methods for segmentation of cytoplasms are compared and it is shown that automated cytoplasmic delineation can be performed 30 times faster than manual delineation, with an accuracy as high as 87%. The final image based measurements of mitochondrial mutation load are also compared to, and show high agreement with, measurements made using biochemical techniques.
|
|
| 3. |
- Allalou, Amin, et al.
(author)
-
Image based measurements of single cell mtDNA mutation load MTD 2007
- 2007
-
In: Medicinteknikdagarna 2007.
-
Conference paper (pop. science, debate, etc.)abstract
- Cell cultures as well as cells in tissue always display a certain degree of variability,and measurements based on cell averages will miss important information contained in a heterogeneous population. These differences among cells in a population may be essential to quantify when looking at, e.g., protein expression and mutations in tumor cells which often show high degree of heterogeneity.Single nucleotide mutations in the mithochondrial DNA (mtDNA) can accumulate and later be present in large proportions of the mithocondria causing devastating diseases. To study mtDNA accumulation and segregation one needs to measure the amount of mtDNA mutations in each cell in multiple serial cell culture passages. The different degrees of mutation in a cell culture can be quantified by making measurements on individual cells as an alternative to looking at an average of a population. Fluorescence microscopy in combination with automated digital image analysis provides an efficient approach to this type of single cell analysis.Image analysis software for these types of applications are often complicated and not easy to use for persons lacking extensive knowledge in image analysis, e.g., laboratory personnel. This paper presents a user friendly implementation of an automated method for image based measurements of mtDNA mutations in individual cells detected with padlock probes and rolling-circle amplification (RCA). The mitochondria are present in the cell’s cytoplasm, and here each cytoplasm has to be delineated without the presence of a cytoplasmic stain. Three different methods for segmentation of cytoplasms are compared and it is shown that automated cytoplasmic delineation can be performed 30 times faster than manual delineation, with an accuracy as high as 87%. The final image based measurements of mitochondrial mutation load are also compared to, and show high agreement with, measurements made using biochemical techniques.
|
|
| 4. |
- Allalou, Amin, et al.
(author)
-
Segmentation of Cytoplasms of Cultured Cells
- 2007
-
In: In Proceedings SSBA 2007, Symposium on image analysis, Linköping.
-
Conference paper (other academic/artistic)abstract
- Cell cultures as well as cells in tissue always display a certain degree of variability, and measurements based on cell averages will miss important information contained in a heterogeneous population. This paper presents automated methods for segmentation of cells and cytoplasms. The segmentation results are applied to image based measurements of mitochondiral DNA (mtDNA) mutations in individual cells. Three different methods for segmentation of cytoplasms are compared and it is shown that automated cytoplasmic delineation can be performed 30 times faster than manual delineation, with an accuracy as high as 87%, compared to an inter observer variability of 79% at manual delineation.
|
|
| 5. |
- Allalou, Amin, 1981-, et al.
(author)
-
Signal Detection in 3D by Stable Wave Signal Verification
- 2009
-
In: Proceedings of SSBA 2009.
-
Conference paper (other academic/artistic)abstract
- Detection and localization of point-source signals is an important task in many image analysis applications. These types of signals can commonly be seen in fluorescent microscopy when studying functions of biomolecules. Visual detection and localization of point-source signals in 3D is limited and time consuming, making automated methods an important task. The 3D Stable Wave Detector (3DSWD) is a new method that combines signal enhancement with a verifier/separator. The verifier/separator examines the intensity gradient around a signal, making the detection less sensitive to noise and better at separating spatially close signals. Conventional methods such as; TopHat, Difference of Gaussian, and Multiscale Product consist only of signal enhancement. In this paper we compare the 3DSWD to these conventional methods with and without the addition of a verifier/separator. We can see that the 3DSWD has the highest robustness to noise among all the methods and that the other methods are improved when a verifier/separator is added.
|
|
| 6. |
|
|
| 7. |
- Gavrilovic, Milan, 1981-, et al.
(author)
-
Dimensionality Reduction for Colour Based Pixel Classification
- 2009
-
In: Proceedings SSBA 2009. - Halmstad : Halmstad University. - 9789163339240 ; , s. 65-68
-
Conference paper (other academic/artistic)abstract
- In digital images, providing classification based on colour, hue or spectral angle is a problem usually solved by combining a variety of pre-processing steps, as well as object wise classifiers. We have developed a method for transforming colour or multispectral image data to a 1D colour histogram with respect to the digital characteristics of intensity measurements. Classification is then reduced to 1D histogram segmentation which is a simpler problem. The proposed method, based on ideas of spectral decomposition, was previously applied in dual-colour fluorescence microscopy for quantification and detection of colocalization insensitive to cross-talk. In this paper the principle is expanded to unsupervised colour based pixel classification algorithms in hue-saturation-lightness or luminance-chrominance colour spaces.
|
|
| 8. |
- Gavrilovic, Milan, 1981-, et al.
(author)
-
Quantification and Localization of Colocalization
- 2007
-
In: Proceedings SSBA 2007. - Linköping : Linköping University. ; , s. 93-96
-
Conference paper (other academic/artistic)abstract
- This paper presents a comparison of two well known and commonly used methods for quantification of color colocalization in fluorescence microscopy image data. We also propose a new method based on a modified spectral decomposition borrowed from the field of remote sensing. Quantification and localization of colocalized pixels using modified spectral decomposition proved to be more robust than previous method when tested on a data set of artificial images with increasing levels of noise. The proposed method was also tested on a data set consisting of 16 color channels, showing that it is easily extendable to colocalization problems in more than two color dimensions.
|
|
| 9. |
- Gavrilovic, Milan, 1981-, et al.
(author)
-
Quantification of colocalization and cross-talk based on spectral angles
- 2009
-
In: Journal of Microscopy. - Oxford, UK : Blackwell Publishing. - 0022-2720 .- 1365-2818. ; 234:3, s. 311-324
-
Journal article (peer-reviewed)abstract
- Common methods for quantification of colocalization in fluorescence microscopy typically require cross-talk free images or images where cross-talk has been eliminated by image processing, as they are based on intensity thresholding. Quantification of colocalization includes not only calculating a global measure of the degree of colocalization within an image, but also a classification of each image pixel as showing colocalized signals or not. In this paper, we present a novel, automated method for quantification of colocalization and classification of image pixels. The method, referred to as SpecDec, is based on an algorithm for spectral decomposition of multispectral data borrowed from the field of remote sensing. Pixels are classified based on hue rather than intensity. The hue distribution is presented as a histogram created by a series of steps that compensate for the quantization noise always present in digital image data, and classification rules are thereafter based on the shape of the angle histogram. Detection of colocalized signals is thus only dependent on the hue, making it possible to classify also low-intensity objects, and decoupling image segmentation from detection of colocalization. Cross-talk will show up as shifts of the peaks of the histogram, and thus a shift of the classification rules, making the method essentially insensitive to cross-talk. The method can also be used to quantify and compensate for cross-talk, independent of the microscope hardware.
|
|
| 10. |
- Gavrilovic, Milan, 1981-, et al.
(author)
-
Spectral Angle Histogram : a Novel Image Analysis Tool for Quantification of Colocalization and Cross-talk
- 2009
-
In: 9th International ELMI Meeting on Advanced Light Microscopy. - Glasgow, UK. ; , s. 66-67
-
Conference paper (other academic/artistic)abstract
- In fluorescence microscopy, when analyzing spectral components, it is common to record two (or more) greyscale images. Each greyscale image, referred to as a channel, corresponds to intensities in different wavelength intervals. If each pixel of a two-channel image is plotted in a space spanned by the two intensity channels a conventional scatter-plot is obtained. Single-coloured pixels are distributed along the axes, while colocalized pixels are distributed closer to the diagonal of the scatter-plot, and cross-talk (as well as noise) is observed as deviations of the single-coloured vectors from the axes. Detection of colocalized pixels is often based on a division of this 2D space into different regions by intensity thresholding. We have developed a method for reducing the scatter-plot to a 1D spectral angle histogram through a series of steps that compensate for the quantization noise which is always present in digital image data.Using the spectral angle histogram, we can quantify colocalization in a fully automated and robust manner. As compared to previous methods for quantification of colocalization, this approach is insensitive to cross-talk. In fact, it can also be employed to quantify and compensate for cross-talk, using either linear unmixing or fuzzy classification by spectral angle, ensuring complete suppression of cross-talk with minimal loss of information. Recently we started investigating how the method can deal with autofluorescence. Initial tests on real image data show that the method may be useful for improved background suppression and amplification of the true signals.The article “Quantification of colocalization and cross-talk based on spectral angles”, describing the method, is about to be published in the Journal of Microscopy. Authors have also filed a patent application “Pixel classification in image analysis” in 2008.
|
|
| 11. |
- Gavrilovic, Milan, 1981-, et al.
(author)
-
Suppression of Autofluorescence based on Fuzzy Classification by Spectral Angles
- 2009
-
In: Optical Tissue Image analysis in Microscopy, Histopathology and Endoscopy (OPTIMHisE). - London. - 9780956377609 ; , s. 135-146
-
Conference paper (peer-reviewed)abstract
- Background fluorescence, also known as autofluorescence, and cross-talk are two problems in fluorescence microscopy that stem from similar phenomena. When biological specimens are imaged, the detected signal often contains contributions from fluorescence originating from sources other than the imaged fluorophore. This fluorescence could either come from the specimen itself (autofluorescence), or from fluorophores with partly overlapping emission spectra (cross-talk). In order to resolve spectral components at least two distinct wavelength intervals have to be imaged. This paper shows how autofluorescence can be presented statistically using a spectral angle histogram. Pixel classification by spectral angles was previously developed for detection and quantification of colocalization. Here we show how the spectral angle histogram can be employed to suppress autofluorescence. First, classical background subtraction (also referred to as linear unmixing) is presented in the form of a fuzzy classification by spectral angles. A modification of the fuzzy classification rules is also presented and we show that sigmoid membership functions lead to better suppression of background and amplification of true signals.
|
|
| 12. |
- Göransson, Jenny, 1978-, et al.
(author)
-
A single molecule array for digital targeted molecular analyses
- 2009
-
In: Nucleic Acids Research. - England : Oxford University Press. - 0305-1048 .- 1362-4962. ; 37:1, s. e7-
-
Journal article (peer-reviewed)abstract
- We present a new random array format together with a decoding scheme for targeted multiplex digital molecular analyses. DNA samples are analyzed using multiplex sets of padlock or selector probes that create circular DNA molecules upon target recognition. The circularized DNA molecules are amplified through rolling-circle amplification (RCA) to generate amplified single molecules (ASMs). A random array is generated by immobilizing all ASMs on a microscopy glass slide. The ASMs are identified and counted through serial hybridizations of small sets of tag probes, according to a combinatorial decoding scheme. We show that random array format permits at least 10 iterations of hybridization, imaging and dehybridization, a process required for the combinatorial decoding scheme. We further investigated the quantitative dynamic range and precision of the random array format. Finally, as a demonstration, the decoding scheme was applied for multiplex quantitative analysis of genomic loci in samples having verified copy-number variations. Of 31 analyzed loci, all but one were correctly identified and responded according to the known copy-number variations. The decoding strategy is generic in that the target can be any biomolecule which has been encoded into a DNA circle via a molecular probing reaction.
|
|
| 13. |
- Holting, Per, et al.
(author)
-
Easy-to-use object selection by color space projections and watershed segmentation
- 2005
-
In: Image Analysis and Processing. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 9783540288695 ; , s. 269-276
-
Conference paper (peer-reviewed)abstract
- Digital cameras are gaining in popularity, and not only experts in image analysis, but also the average users, show a growing interest in image processing. Many different kinds of software for image processing offer tools for object selection, or segmentation, but most of them require expertise knowledge, or leave too little freedom in expressing the desired segmentation. This paper presents an easy to use tool for object segmentation in color images. The amount of user interaction is minimized, and no tuning parameters are needed. The method is based on the watershed segmentation algorithm, combined with seeding information given by the user, and color space projections for optimized object edge detection. The presented method can successfully segment objects in most types of color images.
|
|
| 14. |
- Jahangir Tafrechi, Roshan S., et al.
(author)
-
Single-cell A3243G mitochondrial DNA mutation load assays for segregation analysis
- 2007
-
In: Journal of Histochemistry and Cytochemistry. - 0022-1554 .- 1551-5044. ; 55:11, s. 1159-1166
-
Journal article (peer-reviewed)abstract
- Segregation of mitochondrial DNA (mtDNA) is an important underlying pathogenic factor in mtDNA mutation accumulation in mitochondrial diseases and aging, but the molecular mechanisms of mtDNA segregation are elusive. Lack of high-throughput single-cell mutation load assays lies at the root of the paucity of studies in which, at the single-cell level, mitotic mtDNA segregation patterns have been analyzed. Here we describe development of a novel fluorescence-based, non-gel PCR restriction fragment length polymorphism method for single-cell A3243G mtDNA mutation load measurement. Results correlated very well with a quantitative in situ Padlock/rolling circle amplification–based genotyping method. In view of the throughput and accuracy of both methods for single-cell A3243G mtDNA mutation load determination, we conclude that they are well suited for segregation analysis.
|
|
| 15. |
- Jarvius, Malin, et al.
(author)
-
In situ detection of phosphorylated platelet-derived growth factor receptor beta using a generalized proximity ligation method
- 2007
-
In: Molecular & Cellular Proteomics. - 1535-9476 .- 1535-9484. ; 6:9, s. 1500-1509
-
Journal article (peer-reviewed)abstract
- Improved methods are needed for in situ characterization of post-translational modifications in cell lines and tissues. For example, it is desirable to monitor the phosphorylation status of individual receptor tyrosine kinases in samples from human tumors treated with inhibitors to evaluate therapeutic responses. Unfortunately the leading methods for observing the dynamics of tissue post-translational modifications in situ, immunohistochemistry and immunofluorescence, exhibit limited sensitivity and selectivity. Proximity ligation assay is a novel method that offers improved selectivity through the requirement of dual recognition and increased sensitivity by including DNA amplification as a component of detection of the target molecule. Here we therefore established a generalized in situ proximity ligation assay to investigate phosphorylation of platelet-derived growth factor receptor β (PDGFRβ) in cells stimulated with platelet-derived growth factor BB. Antibodies specific for immunoglobulins from different species, modified by attachment of DNA strands, were used as secondary proximity probes together with a pair of primary antibodies from the corresponding species. Dual recognition of receptors and phosphorylated sites by the primary antibodies in combination with the secondary proximity probes was used to generate circular DNA strands; this was followed by signal amplification by replicating the DNA circles via rolling circle amplification. We detected tyrosine phosphorylated PDGFRβ in human embryonic kidney cells stably overexpressing human influenza hemagglutinin-tagged human PDGFRβ in porcine aortic endothelial cells transfected with the β-receptor, but not in cells transfected with the α-receptor, and also in immortalized human foreskin fibroblasts, BJ hTert, endogenously expressing the PDGFRβ. We furthermore visualized tyrosine phosphorylated PDGFRβ in tissue sections from fresh frozen human scar tissue undergoing wound healing. The method should be of great value to study signal transduction, screen for effects of pharmacological agents, and enhance the diagnostic potential in histopathology.
|
|
| 16. |
- Karlsson Edlund, Patrick, 1975-
(author)
-
Methods and models for 2D and 3D image analysis in microscopy, in particular for the study of muscle cells
- 2008
-
Doctoral thesis (other academic/artistic)abstract
- Many research questions in biological research lead to numerous microscope images that need to be evaluated. Here digital image cytometry, i.e., quantitative, automated or semi-automated analysis of the images is an important rapidly growing discipline. This thesis presents contributions to that field. The work has been carried out in close cooperation with biomedical research partners, successfully solving real world problems.The world is 3D and modern imaging methods such as confocal microscopy provide 3D images. Hence, a large part of the work has dealt with the development of new and improved methods for quantitative analysis of 3D images, in particular fluorescently labeled skeletal muscle cells.A geometrical model for robust segmentation of skeletal muscle fibers was developed. Images of the multinucleated muscle cells were pre-processed using a novel spatially modulated transform, producing images with reduced complexity and facilitating easy nuclei segmentation. Fibers from several mammalian species were modeled and features were computed based on cell nuclei positions. Features such as myonuclear domain size and nearest neighbor distance, were shown to correlate with body mass, and femur length. Human muscle fibers from young and old males, and females, were related to fiber type and extracted features, where myonuclear domain size variations were shown to increase with age irrespectively of fiber type and gender.A segmentation method for severely clustered point-like signals was developed and applied to images of fluorescent probes, quantifying the amount and location of mitochondrial DNA within cells. A synthetic cell model was developed, to provide a controllable golden standard for performance evaluation of both expert manual and fully automated segmentations. The proposed method matches the correctness achieved by manual quantification.An interactive segmentation procedure was successfully applied to treated testicle sections of boar, showing how a common industrial plastic softener significantly affects testosterone concentrations.
|
|
| 17. |
- Pinidiyaarachchi, Amalka, et al.
(author)
-
A detailed analysis of 3D subcellular signal localization
- 2009
-
In: Cytometry Part A. - : Wiley. - 1552-4922 .- 1552-4930. ; 75A:4, s. 319-328
-
Journal article (peer-reviewed)abstract
- Detection and localization of fluorescent signals in relation to other subcellular structures is an important task in various biological studies. Many methods for analysis of fluorescence microscopy image data are limited to 2D. As cells are in fact 3D structures, there is a growing need for robust methods for analysis of 3D data. This article presents an approach for detecting point-like fluorescent signals and analyzing their subnuclear position. Cell nuclei are delineated using marker-controlled (seeded) 3D watershed segmentation. User-defined object and background seeds are given as input, and gradient information defines merging and splitting criteria. Point-like signals are detected using a modified stable wave detector and localized in relation to the nuclear membrane using distance shells. The method was applied to a set of biological data studying the localization of Smad2-Smad4 protein complexes in relation to the nuclear membrane. Smad complexes appear as early as 1 min after stimulation while the highest signal concentration is observed 45 min after stimulation, followed by a concentration decrease. The robust 3D signal detection and concentration measures obtained using the proposed method agree with previous observations while also revealing new information regarding the complex formation.
|
|
| 18. |
- Pinidiyaarachchi, Amalka, 1975-
(author)
-
Digital Image Analysis of Cells : Applications in 2D, 3D and Time
- 2009
-
Doctoral thesis (other academic/artistic)abstract
- Light microscopes are essential research tools in biology and medicine. Cell and tissue staining methods have improved immensely over the years and microscopes are now equipped with digital image acquisition capabilities. The image data produced require development of specialized analysis methods. This thesis presents digital image analysis methods for cell image data in 2D, 3D and time sequences.Stem cells have the capability to differentiate into specific cell types. The mechanism behind differentiation can be studied by tracking cells over time. This thesis presents a combined segmentation and tracking algorithm for time sequence images of neural stem cells.The method handles splitting and merging of cells and the results are similar to those achieved by manual tracking.Methods for detecting and localizing signals from fluorescence stained biomolecules are essential when studying how they function and interact. A study of Smad proteins, that serve as transcription factors by forming complexes and enter the cell nucleus, is included in the thesis. Confocal microscopy images of cell nuclei are delineated using gradient information, and Smad complexes are localized using a novel method for 3D signal detection. Thus, the localization of Smad complexes in relation to the nuclear membrane can be analyzed. A detailed comparison between the proposed and previous methods for detection of point-source signals is presented, showing that the proposed method has better resolving power and is more robust to noise.In this thesis, it is also shown how cell confluence can be measured by classification of wavelet based texture features. Monitoring cell confluence is valuable for optimization of cell culture parameters and cell harvest. The results obtained agree with visual observations and provide an efficient approach to monitor cell confluence and detect necrosis.Quantitative measurements on cells are important in both cytology and histology. The color provided by Pap (Papanicolaou) staining increases the available image information. The thesis explores different color spaces of Pap smear images from thyroid nodules, with the aim of finding the representation that maximizes detection of malignancies using color information in addition to quantitative morphological parameters.The presented methods provide useful tools for cell image analysis, but they can of course also be used for other image analysis applications.
|
|
| 19. |
- Pinidiyaarachchi, Amalka, et al.
(author)
-
Digital image processing for multiplexing of single molecule detection
- 2005
-
In: Medicinteknikdagarna.
-
Conference paper (other academic/artistic)abstract
- Using padlock and proximity probing techniques, individual molecular identification events are converted to long DNA molecules, carrying repeated sequence motifs used for identification of the detected molecules. We show that identification events can be amplified using rolling circle replication, and randomly attached to a surface for repeated access by identification probes. Repeated hybridization with detection probes carrying fluorescing nano-crystals (quantum dots) of varying spectral properties opens the possibility to search for large numbers of different identification events simultaneously. Methods for digital image processing of the resulting multi-spectral data include spatial as well as spectral data clustering. Spatial data processing includes registration of images from repeated hybridization events as well as delineation of clustered reporter events. Spectral data processing and analysis includes classification of spectral data into groups of either pre-defined or unknown patterns representing different molecular identification events.
|
|
| 20. |
- Pinidiyaarachchi, Amalka, et al.
(author)
-
On color spaces for cytology
- 2007
-
In: SSBA 2007, Symposium i bildanalys i Linköping 14-15 mars 2007.
-
Conference paper (peer-reviewed)
|
|
| 21. |
- Pinidiyaarachchi, Amalka, et al.
(author)
-
Seeded watersheds for combined segmentation and tracking
- 2005
-
In: Image Analysis and Processing – ICIAP 2005. - Berlin, Heidelberg : Springer Berlin / Heidelberg. - 9783540288695 ; , s. 336-343
-
Book chapter (other academic/artistic)abstract
- Watersheds are very powerful for image segmentation, and seeded watersheds have shown to be useful for object detection in images of cells in vitro. This paper shows that if cells are imaged over time, segmentation results from a previous time frame can be used as seeds for watershed segmentation of the current time frame. The seeds from the previous frame are combined with morphological seeds from the current frame, and over-segmentation is reduced by rule-based merging, propagating labels from one time-frame to the next. Thus, watershed segmentation is used for segmentation as well as tracking of cells over time. The described algorithm was tested on neural stem/progenitor cells imaged using time-lapse microscopy. Tracking results agreed to 71% to manual tracking results. The results were also compared to tracking based on solving the assignment problem using a modified version of the auction algorithm.
|
|
| 22. |
- Wählby, Carolina, 1974-, et al.
(author)
-
Finding cells, finding molecules, finding patterns
- 2006
-
In: Advances in Data Mining. ; , s. 15-24
-
Conference paper (peer-reviewed)abstract
- Many modern molecular labeling techniques result in bright point signals. Signals from molecules that are detected directly inside a cell can be captured by fluorescence microscopy. Signals representing different types of molecules may be randomly distributed in the cells or show systematic patterns indicating that the corresponding molecules have specific, non-random localizations and functions in the cell. Assessing this information requires high speed robust image segmentation followed by signal detection, and finally pattern analysis. We present and discuss this type of methods and show an example of how the distribution of different variants of mitochondrial DNA can be analyzed.
|
|
| 23. |
- Wählby, Carolina, et al.
(author)
-
Finding cells, finding molecules, finding patterns
- 2008
-
In: International Journal of Signal and Imaging Systems Engineering. - 1748-0698. ; 1:1, s. 11-17
-
Journal article (peer-reviewed)abstract
- Many modern molecular labelling techniques result in bright point signals. Signals from molecules that are detected directly inside a cell can be captured by fluorescence microscopy. Signals representing different types of molecules may be randomly distributed in the cells or show systematic patterns, indicating that the corresponding molecules have specific, non-random localisations and functions in the cell. Assessing this information requires high speed robust image segmentation followed by signal detection, and finally, pattern analysis. We present and discuss these types of methods and show an example of how the distribution of different variants of mitochondrial DNA can be analysed.
|
|
| 24. |
|
|
