| 1. |
- Arnold, Hannah, et al.
(författare)
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mafba and mafbb differentially regulate lymphatic endothelial cell migration in topographically distinct manners
- 2022
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Ingår i: Cell Reports. - : Elsevier. - 2211-1247. ; 39:12
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Tidskriftsartikel (refereegranskat)abstract
- Lymphangiogenesis, formation of lymphatic vessels from pre-existing vessels, is a dynamic process that requires cell migration. Regardless of location, migrating lymphatic endothelial cell (LEC) progenitors probe their surroundings to form the lymphatic network. Lymphatic-development regulation requires the transcription factor MAFB in different species. Zebrafish Mafba, expressed in LEC progenitors, is essential for their migration in the trunk. However, the transcriptional mechanism that orchestrates LEC migration in different lymphatic endothelial beds remains elusive. Here, we uncover topographically different requirements of the two paralogs, Mafba and Mafbb, for LEC migration. Both mafba and mafbb are necessary for facial lymphatic development, but mafbb is dispensable for trunk lymphatic development. On the molecular level, we demonstrate a regulatory network where Vegfc-Vegfd-SoxF-Mafba-Mafbb is essential in facial lymphangiogenesis. We identify that mafba and mafbb tune the directionality of LEC migration and vessel morphogenesis that is ultimately necessary for lymphatic function.
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| 2. |
- Arnold, Hannah, et al.
(författare)
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Mafba and Mafbb Differentially Regulate Lymphatic Endothelial Cell Migration in Topographically Distinct Manners
- 2021
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Ingår i: SSRN Electronic Journal. - : Elsevier. - 1556-5068.
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Tidskriftsartikel (refereegranskat)abstract
- Lymphangiogenesis is the formation of lymphatic vessels from pre-existing vessels, a dynamic process that requires cell migration. Regardless of location, lymphatic endothelial cell (LEC) progenitors probe their surroundings while migrating to form the lymphatic network. Lymphatic development regulation depends on the transcription factor MAFB in different species. Zebrafish Mafba, expressed in LEC progenitors, is essential for their migration in the trunk. However, the transcriptional mechanism that orchestrate LEC migration in different lymphatic endothelial beds remains elusive. Here, we uncover topographically different requirements of the two paralogues, Mafba and Mafbb, for lymphatic cell migration. Both mafba and mafbb are necessary for facial lymphatic development, but mafbb is dispensable for trunk lymphatic development. On the molecular level, we demonstrate a regulatory network where Vegfc-Vegfd-SoxF-Mafba-Mafbb are essential in the facial lymphangiogenesis. We identify that mafba and mafbb fine-tune the directionality of LEC migration and vessel morphogenesis that is ultimately necessary for lymphatic function.
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| 3. |
- Bandaru, Manoj Kumar, et al.
(författare)
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Zebrafish larvae as a model system for systematic characterization of drugs and genes in dyslipidemia and atherosclerosis
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Tidskriftsartikel (refereegranskat)abstract
- Background: Hundreds of loci have been robustly associated with circulating lipids, atherosclerosis and coronary artery disease; but for most loci the causal genes and mechanisms remain uncharacterized.Methods: We developed a semi-automated experimental pipeline for systematic, quantitative, large-scale characterization of mechanisms, drugs and genes associated with dyslipidemia and atherosclerosis in a zebrafish model system. We validated our pipeline using a dietary (n>2000), drug treatment (n>1000), and genetic intervention (n=384).Results: Our results show that five days of overfeeding and cholesterol supplementation had independent pro-atherogenic effects, which could be diminished by concomitant treatment with atorvastatin and ezetimibe. CRISPR-Cas9-induced mutations in orthologues of proof-of-concept genes resulted in higher LDL cholesterol levels (apoea), and more early stage atherosclerosis (apobb.1).Conclusions: In summary, our pipeline facilitates systematic, in vivo characterization of drugs and candidate genes to increase our understanding of disease etiology, and can likely help identify novel targets for therapeutic intervention.
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| 4. |
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| 5. |
- Bombrun, Maxime, et al.
(författare)
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A web application to analyse and visualize digital images at multiple resolutions
- 2017
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Computerised image processing and automated quantification of cell and tissue morphology are becoming important tools for complementing visual assessment when investigating disease and/or drug response. The distribution and organisation of cells in intact tissue samples provides a rich visual-cognitive combination of information at multiple resolutions. The lowest magnification describes specific architectural patterns in the global tissue organization. At the same time, new methods for in situ sequencing of RNA allows profiling of gene expression at cellular resolution. Analysis at multiple resolutions thus opens up for large-scale comparison of genotype and phenotype. Expressed genes are locally amplified by molecular probes and rolling circle amplification, and decoded by repeating the sequencing cycle for the four letters of the genetic code. Using image processing methodologies on these giga-pixel images (40000 x 48000 pixels), we have identified more than 40 genes in parallel in the same tissue sample. Here, we present an open-source tool which combines the quantification of cell and tissue morphology with the analysis of gene expression. Our framework builds on CellProfiler, a free and open-source software developed for image based screening, and our viewing platform allow experts to visualize both gene expression patterns and quantitative measurements of tissue morphology with different overlays, such as the commonly used H&E staining. Furthermore, the user can draw regions of interest and extract local statistics on gene expression and tissue morphology over large slide scanner images at different resolutions. The TissueMaps platform provides a flexible solution to support the future development of histopathology, both as a diagnostic tool and as a research field.
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| 6. |
- Bombrun, Maxime, et al.
(författare)
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Decoding gene expression in 2D and 3D
- 2017
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Ingår i: Image Analysis. - Cham : Springer. - 9783319591285 ; , s. 257-268
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Konferensbidrag (refereegranskat)abstract
- Image-based sequencing of RNA molecules directly in tissue samples provides a unique way of relating spatially varying gene expression to tissue morphology. Despite the fact that tissue samples are typically cut in micrometer thin sections, modern molecular detection methods result in signals so densely packed that optical “slicing” by imaging at multiple focal planes becomes necessary to image all signals. Chromatic aberration, signal crosstalk and low signal to noise ratio further complicates the analysis of multiple sequences in parallel. Here a previous 2D analysis approach for image-based gene decoding was used to show how signal count as well as signal precision is increased when analyzing the data in 3D instead. We corrected the extracted signal measurements for signal crosstalk, and improved the results of both 2D and 3D analysis. We applied our methodologies on a tissue sample imaged in six fluorescent channels during five cycles and seven focal planes, resulting in 210 images. Our methods are able to detect more than 5000 signals representing 140 different expressed genes analyzed and decoded in parallel.
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| 7. |
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| 8. |
- Bombrun, Maxime, et al.
(författare)
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TissueMaps : A large multi-scale data analysis platform for digital image application built on open-source software
- 2016
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Automated analysis of microscopy data and quantification of cell and tissue morphology has become an important tool for investigating disease and/or drug response. New methods of in situ sequencing of RNA allows profiling of gene expression at cellular resolution in intact tissue samples, and thus opens up for large-scale comparison of genotype and phenotype. Expressed genes are locally amplified by molecular probes and rolling circle amplification, and decoded by analysis of repeated imaging and sequencing cycles. Using image processing methodologies on these giga-pixel images (40000 x 48000 pixels), we have identified more than 40 genes in parallel in the same tissue sample. On the other hand, the distribution and organisation of cells in the tissue contain rich information at multiple resolutions. The lowest resolution describes the global tissue arrangement, while the cellular resolution allows us to quantify gene expression and morphology of individual cells.Here, we present an open-source tool which combine the analysis of gene expression with quantification of cell and tissue morphology. Our framework builds on CellProfiler, a free and open-source software developed for image based screening, and our viewing platform allow experts to visualize analysis results with different overlays, such as the commonly used H&E staining. Furthermore, the user can draw regions of interest and extract local statistics on gene expression and tissue morphology over large slide scanner images at different resolutions (Fig.1). The TissueMaps platform provides a flexible solution to support the future development of histopathology, both as a diagnostic tool and as a research field.
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| 9. |
- Clausson, Carl-Magnus, 1985-, et al.
(författare)
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Compaction of rolling circle amplification products increases signal integrity and signal–to–noise ratio
- 2015
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 5, s. 12317:1-10
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Tidskriftsartikel (refereegranskat)abstract
- Rolling circle amplification (RCA) for generation of distinct fluorescent signals in situ relies upon the self-collapsing properties of single-stranded DNA in commonly used RCA-based methods. By introducing a cross-hybridizing DNA oligonucleotide during rolling circle amplification, we demonstrate that the fluorophore-labeled RCA products (RCPs) become smaller. The reduced size of RCPs increases the local concentration of fluorophores and as a result, the signal intensity increases together with the signal-to-noise ratio. Furthermore, we have found that RCPs sometimes tend to disintegrate and may be recorded as several RCPs, a trait that is prevented with our cross-hybridizing DNA oligonucleotide. These effects generated by compaction of RCPs improve accuracy of visual as well as automated in situ analysis for RCA based methods, such as proximity ligation assays (PLA) and padlock probes.
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| 10. |
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| 11. |
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| 12. |
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| 13. |
- Hallberg, Ida, et al.
(författare)
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Bovine oocyte exposure to perfluorohexane sulfonate (PFHxS) induces phenotypic, transcriptomic, and DNA methylation changes in resulting embryos in vitro
- 2022
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Ingår i: Reproductive Toxicology. - : Elsevier. - 0890-6238 .- 1873-1708. ; 109, s. 19-30
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Tidskriftsartikel (refereegranskat)abstract
- Knowledge on the effects of perfluorohexane sulfonate (PFHxS) on ovarian function is limited. In the current study, we investigated the sensitivity of oocytes to PFHxS during in vitro maturation (IVM), including conse-quences on embryo development at the morphological, transcriptomic, and epigenomic levels. Bovine cumulus-oocyte complexes (COCs) were exposed to PFHxS during 22 h IVM. Following fertilisation, developmental competence was recorded until day 8 of culture. Two experiments were conducted: 1) exposure of COCs to 0.01 mu g mL(-1) -100 mu g mL(-1) PFHxS followed by confocal imaging to detect neutral lipids and nuclei, and 2) exposure of COCs to 0.1 mu g mL(-1) PFHxS followed by analysis of transcriptomic and DNA methylation changes in blastocysts. Decreased oocyte developmental competence was observed upon exposure to & nbsp;>= 40 mu g mL(-1) PFHxS and altered lipid distribution was observed in the blastocysts upon exposure to 1-10 mu g mL(-1) PFHxS (not observed at lower or higher concentrations). Transcriptomic data showed that genes affected by 0.1 mu g mL(-1) PFHxS were enriched for pathways related to increased synthesis and production of reactive oxygen species. Enrichment for peroxisome proliferator-activated receptor-gamma and oestrogen pathways was also observed. Genes linked to DNA methylation changes were enriched for similar pathways. In conclusion, exposure of the bovine oocyte to PFHxS during the narrow window of IVM affected subsequent embryonic development, as reflected by morphological and mo- lecular changes. This suggests that PFHxS interferes with the final nuclear and cytoplasmic maturation of the oocyte leading to decreased developmental competence to blastocyst stage.
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| 14. |
- Hallström, Erik, et al.
(författare)
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Label-free deep learning-based species classification of bacteria imaged by phase-contrast microscopy
- 2023
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Ingår i: PloS Computational Biology. - : Public Library of Science (PLoS). - 1553-734X .- 1553-7358. ; 19:11
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Tidskriftsartikel (refereegranskat)abstract
- Reliable detection and classification of bacteria and other pathogens in the human body, animals, food, and water is crucial for improving and safeguarding public health. For instance, identifying the species and its antibiotic susceptibility is vital for effective bacterial infection treatment. Here we show that phase contrast time-lapse microscopy combined with deep learning is sufficient to classify four species of bacteria relevant to human health. The classification is performed on living bacteria and does not require fixation or staining, meaning that the bacterial species can be determined as the bacteria reproduce in a microfluidic device, enabling parallel determination of susceptibility to antibiotics. We assess the performance of convolutional neural networks and vision transformers, where the best model attained a class-average accuracy exceeding 98%. Our successful proof-of-principle results suggest that the methods should be challenged with data covering more species and clinically relevant isolates for future clinical use. Bacterial infections are a leading cause of premature death worldwide, and growing antibiotic resistance is making treatment increasingly challenging. To effectively treat a patient with a bacterial infection, it is essential to quickly detect and identify the bacterial species and determine its susceptibility to different antibiotics. Prompt and effective treatment is crucial for the patient's survival. A microfluidic device functions as a miniature "lab-on-chip" for manipulating and analyzing tiny amounts of fluids, such as blood or urine samples from patients. Microfluidic chips with chambers and channels have been designed for quickly testing bacterial susceptibility to different antibiotics by analyzing bacterial growth. Identifying bacterial species has previously relied on killing the bacteria and applying species-specific fluorescent probes. The purpose of the herein proposed species identification is to speed up decisions on treatment options by already in the first few imaging frames getting an idea of the bacterial species, without interfering with the ongoing antibiotics susceptibility testing. We introduce deep learning models as a fast and cost-effective method for identifying bacteria species. We envision this method being employed concurrently with antibiotic susceptibility tests in future applications, significantly enhancing bacterial infection treatments.
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| 15. |
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| 16. |
- Kecheril Sadanandan, Sajith, et al.
(författare)
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Automated training of deep convolutional neural networks for cell segmentation
- 2017
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- Deep Convolutional Neural Networks (DCNN) have recently emerged as superior for many image segmentation tasks. The DCNN performance is however heavily dependent on the availability of large amounts of problem-specific training samples. Here we show that DCNNs trained on ground truth created automatically using fluorescently labeled cells, perform similar to manual annotations.
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| 17. |
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| 18. |
- Leclercq, Anna, et al.
(författare)
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Occurrence of late-apoptotic symptoms in porcine preimplantation embryos upon exposure of oocytes to perfluoroalkyl substances (PFASs) under in vitro meiotic maturation
- 2022
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 17
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Tidskriftsartikel (refereegranskat)abstract
- The objectives of this study were to evaluate the effect of perfluoroalkyl substances on early embryonic development and apoptosis in blastocysts using a porcine in vitro model. Porcine oocytes (N = 855) collected from abattoir ovaries were subjected to perfluorooctane sulfonic acid (PFOS) (0.1 μg/ml) and perfluorohexane sulfonic acid (PFHxS) (40 μg/ml) during in vitro maturation (IVM) for 45 h. The gametes were then fertilized and cultured in vitro, and developmental parameters were recorded. After 6 days of culture, resulting blastocysts (N = 146) were stained using a terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay and imaged as stacks using confocal laser scanning microscopy. Proportion of apoptotic cells as well as total numbers of nuclei in each blastocyst were analyzed using objective image analysis. The experiment was run in 9 replicates, always with a control present. Effects on developmental parameters were analyzed using logistic regression, and effects on apoptosis and total numbers of nuclei were analyzed using linear regression. Higher cell count was associated with lower proportion of apoptotic cells, i.e., larger blastocysts contained less apoptotic cells. Upon PFAS exposure during IVM, PFHxS tended to result in higher blastocyst rates on day 5 post fertilization (p = 0.07) and on day 6 post fertilization (p = 0.05) as well as in higher apoptosis rates in blastocysts (p = 0.06). PFHxS resulted in higher total cell counts in blastocysts (p = 0.002). No effects attributable to the concentration of PFOS used here was seen. These findings add to the evidence that some perfluoroalkyl substances may affect female reproduction. More studies are needed to better understand potential implications for continued development as well as for human health.
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| 19. |
- Matuszewski, Damian J., et al.
(författare)
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Learning Cell Nuclei Segmentation Using Labels Generated with Classical Image Analysis Methods
- 2021
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Ingår i: Proceedings of the WSCG 2021. - : University of West Bohemia. ; , s. 335-338
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Konferensbidrag (refereegranskat)abstract
- Creating manual annotations in a large number of images is a tedious bottleneck that limits deep learning use inmany applications. Here, we present a study in which we used the output of a classical image analysis pipeline aslabels when training a convolutional neural network (CNN). This may not only reduce the time experts spendannotating images but it may also lead to an improvement of results when compared to the output from the classicalpipeline used in training. In our application, i.e., cell nuclei segmentation, we generated the annotations usingCellProfiler (a tool for developing classical image analysis pipelines for biomedical applications) and trained onthem a U-Net-based CNN model. The best model achieved a 0.96 dice-coefficient of the segmented Nuclei and a0.84 object-wise Jaccard index which was better than the classical method used for generating the annotations by0.02 and 0.34, respectively. Our experimental results show that in this application, not only such training is feasiblebut also that the deep learning segmentations are a clear improvement compared to the output from the classicalpipeline used for generating the annotations.
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| 20. |
- Ossinger, Alexander, et al.
(författare)
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A rapid and accurate method to quantify neurite outgrowth from cell and tissue cultures : Two image analytic approaches using adaptive thresholds or machine learning
- 2020
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Ingår i: Journal of Neuroscience Methods. - : Elsevier BV. - 0165-0270 .- 1872-678X. ; 331
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Assessments of axonal outgrowth and dendritic development are essential readouts in many in vitro models in the field of neuroscience. Available analysis software is based on the assessment of fixed immunolabelled tissue samples, making it impossible to follow the dynamic development of neurite outgrowth. Thus, automated algorithms that efficiently analyse brightfield images, such as those obtained during time-lapse microscopy, are needed.NEW METHOD: We developed and validated algorithms to quantitatively assess neurite outgrowth from living and unstained spinal cord slice cultures (SCSCs) and dorsal root ganglion cultures (DRGCs) based on an adaptive thresholding approach called NeuriteSegmantation. We used a machine learning approach to evaluate dendritic development from dissociate neuron cultures.RESULTS: NeuriteSegmentation successfully recognized axons in brightfield images of SCSCs and DRGCs. The temporal pattern of axonal growth was successfully assessed. In dissociate neuron cultures the total number of cells and their outgrowth of dendrites were successfully assessed using machine learning.COMPARISON WITH EXISTING METHODS: The methods were positively correlated and were more time-saving than manual counts, having performing times varying from 0.5-2 minutes. In addition, NeuriteSegmentation was compared to NeuriteJ®, that uses global thresholding, being more reliable in recognizing axons in areas of intense background.CONCLUSION: The developed image analysis methods were more time-saving and user-independent than established approaches. Moreover, by using adaptive thresholding, we could assess images with large variations in background intensity. These tools may prove valuable in the quantitative analysis of axonal and dendritic outgrowth from numerous in vitro models used in neuroscience.
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| 21. |
- ovrebo, Oystein, et al.
(författare)
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RegiSTORM : channel registration for multi-color stochastic optical reconstruction microscopy
- 2023
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Ingår i: BMC Bioinformatics. - : BMC. - 1471-2105. ; 24:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Stochastic optical reconstruction microscopy (STORM), a super-resolution microscopy technique based on single-molecule localizations, has become popular to characterize sub-diffraction limit targets. However, due to lengthy image acquisition, STORM recordings are prone to sample drift. Existing cross-correlation or fiducial marker-based algorithms allow correcting the drift within each channel, but misalignment between channels remains due to interchannel drift accumulating during sequential channel acquisition. This is a major drawback in multi-color STORM, a technique of utmost importance for the characterization of various biological interactions.Results: We developed RegiSTORM, a software for reducing channel misalignment by accurately registering STORM channels utilizing fiducial markers in the sample. RegiSTORM identifies fiducials from the STORM localization data based on their non-blinking nature and uses them as landmarks for channel registration. We first demonstrated accurate registration on recordings of fiducials only, as evidenced by significantly reduced target registration error with all the tested channel combinations. Next, we validated the performance in a more practically relevant setup on cells multi-stained for tubulin. Finally, we showed that RegiSTORM successfully registers two-color STORM recordings of cargo-loaded lipid nanoparticles without fiducials, demonstrating the broader applicability of this software.Conclusions: The developed RegiSTORM software was demonstrated to be able to accurately register multiple STORM channels and is freely available as open-source (MIT license) at https://github.com/oystein676/RegiSTORM.git and https://doi.org/10.5281/ zenodo.5509861 (archived), and runs as a standalone executable (Windows) or via Python (Mac OS, Linux).
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| 22. |
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| 23. |
- Ranefall, Petter, et al.
(författare)
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A new method for segmentation of colour images applied to immunohistochemically stained cell nuclei
- 1997
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Ingår i: Analytical Cellular Pathology. - : IOS PRESS. - 0921-8912 .- 1878-3651. ; 15:3, s. 145-156
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Tidskriftsartikel (refereegranskat)abstract
- A new method for segmenting images of immunohistochemically stained cell nuclei is presented. The aim is to distinguish between cell nuclei with a positive staining reaction and other cell nuclei, and to make it possible to quantify the reaction. First, a
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| 24. |
- Ranefall, Petter, 1968-, et al.
(författare)
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Automatic grading of breast cancer from whole slide images of Ki67 stained tissue sections
- 2016
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- AimThis work describes a proof-of-principle study within the Exchange of Diagnostic Images in Networks (ExDIN) project, for automatic grading of breast cancer from whole slide images of Ki67 stained tissue sections. The idea was to mimic the manual grading process: “The assessment is carried out on invasive cancer within the area with the highest number of Ki67-positive cancer cell nuclei/area (hot spot), containing at least 200 cells.”MethodColor deconvolution to separate the image into brown and blue channels.Extract the 10 subsampled tiles (size corresponding to ~200 cells) with the highest values for pre-defined texture and color features.Analyze these tiles in full resolution and compute the maximum positivity (defined as area of positive cells in relation to total cell area, rather than number of cells, since that will speed up the computations and avoid introducing errors due to over- or under segmentation of connected objects). Figure 1. Illustration of the procedure. Hot spot candidates are extracted from low resolution tiles. Then the final hot spot is selected among the corresponding full resolution versions.The results show good correlation to manual estimates and the procedure takes ~4 minutes/slide.Future improvementsRules and features defined using machine learning based on training samples given by pathologists.User interface where suggested regions can be deselected manually.
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| 25. |
- Ranefall, Petter, et al.
(författare)
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Automatic quantification of immunohistochemically stained cell nuclei based on standard reference cells
- 1998
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Ingår i: Analytical Cellular Pathology. - 0921-8912 .- 1878-3651. ; 17:2, s. 111-23
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Tidskriftsartikel (refereegranskat)abstract
- A fully automatic method for quantification of images of immunohistochemically stained cell nuclei by computing area proportions, is presented. Agarose embedded cultured fibroblasts were fixed, paraffin embedded and sectioned at 4 microm. They were then stained together with 4 microm sections of the test specimen obtained from bladder cancer material. A colour based classifier is automatically computed from the control cells. The method was tested on formalin fixed paraffin embedded tissue section material, stained with monoclonal antibodies against the Ki67 antigen and cyclin A protein. Ki67 staining results in a detailed nuclear texture with pronounced nucleoli and cyclin A staining is obtained in a more homogeneously distributed pattern. However, different staining patterns did not seem to influence labelling index quantification, and the sensitivity to variations in light conditions and choice of areas within the control population was low. Thus, the technique represents a robust and reproducible quantification method. In tests measuring proportions of stained area an average standard deviation of about 1.5% for the same field was achieved when classified with classifiers created from different control samples.
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| 26. |
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| 27. |
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| 28. |
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| 29. |
- Ranefall, Petter, et al.
(författare)
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Automatic quantification of microvessels using unsupervised image analysis
- 1998
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Ingår i: Analytical Cellular Pathology. - : IOS PRESS. - 0921-8912 .- 1878-3651. ; 17:2, s. 83-92
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Tidskriftsartikel (refereegranskat)abstract
- An automatic method for quantification of images of microvessels by computing area proportions and number of objects is presented. The objects are segmented from the background using dynamic thresholding of the average component size histogram. To be able
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| 30. |
- Ranefall, Petter, 1968-, et al.
(författare)
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Fast Adaptive Local Thresholding Based on Ellipse fit
- 2016
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Konferensbidrag (refereegranskat)abstract
- In this paper we propose an adaptive thresholding method where each object is thresholded optimizing its shape. The method is based on a component tree representation, which can be computed in quasi-linear time. We test and evaluate the method on images of bacteria from three different live-cell analysis experiments and show that the proposed method produces segmentation results comparable to state-of-the-art but at least an order of magnitude faster. The method can be extended to compute any feature measurements that can be calculated in a cumulative way, and holds great potential for applications where a priori information on expected object size and shape is available.
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| 31. |
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| 32. |
- Ranefall, Petter, 1968-, et al.
(författare)
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Global And Local Adaptive Gray-level Thresholding Based on Object Features
- 2016
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Ingår i: Swedish Symposium on Image Analysis 2016.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- In this paper we propose a) a fast and robustglobal gray-level thresholding method based on object size,where the selection of threshold level is based on recall andmaximum precision with regard to objects within a givensize interval, and b) an adaptive thresholding method whereeach object is thresholded optimizing its shape. The methodsare based on on the component tree representation, whichcan be computed in quasi-linear time. We show that forreal images of cell nuclei and synthetic data sets mimickingfluorescent spots the proposed methods are more robust thanall standard global thresholding methods in ImageJ andCellProfiler. The methods can be extended to compute anyfeature measurements that can be calculated in a cumulativeway, and hold great potential for applications where a prioriinformation on expected object size and shape is available.
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| 33. |
- Ranefall, Petter, 1968-, et al.
(författare)
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Global Gray-level Thresholding Based on Object Size
- 2016
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Ingår i: Cytometry Part A. - : John Wiley & Sons. - 1552-4922 .- 1552-4930. ; 89A:4, s. 385-390
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Tidskriftsartikel (refereegranskat)abstract
- In this article, we propose a fast and robust global gray-level thresholding method based on object size, where the selection of threshold level is based on recall and maximum precision with regard to objects within a given size interval. The method relies on the component tree representation, which can be computed in quasi-linear time. Feature-based segmentation is especially suitable for biomedical microscopy applications where objects often vary in number, but have limited variation in size. We show that for real images of cell nuclei and synthetic data sets mimicking fluorescent spots the proposed method is more robust than all standard global thresholding methods available for microscopy applications in ImageJ and CellProfiler. The proposed method, provided as ImageJ and CellProfiler plugins, is simple to use and the only required input is an interval of the expected object sizes.
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| 34. |
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| 35. |
- Ranefall, Petter, 1968-, et al.
(författare)
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The Giga-pixel Challenge: Full Resolution Image Analysis – Without Losing the Big Picture : An open-source approach for multi-scale analysis and visualization of slide-scanner data
- 2014
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The amount of image data in a slide scanner image is usually in the giga-pixel range, inducing challenges for image analysis and visualization. At the same time, in order to maximize the information gained in these experi-ments and integrate expert knowledge with quantitative measurements, it is crucial to maintain the connection be-tween high-resolution per-cell and per-region metrics with lower resolution relational metrics. We present a free and open-source framework for full resolution image analysis of large images, e.g. slide scanner data, with the possibility of visual examination and interaction at multiple resolutions. The interface enables seamless zooming and panning, with the option to toggle multiple layers, such as segmentation masks and classification results, on or off. We make use of the strength and flexibility of existing state-of-the-art open-source software for visualization, creating resolution pyra-mids, image registration and image analysis.
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| 36. |
- Ranefall, Petter, 1968-
(författare)
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Towards Automatic Quantification of Immunohistochemistry Using Colour Image Analysis
- 1998
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Quantification of the proportions of specifically stained regions in images is of significant interest in a growing number of biomedical applications. These applications includes histology and cytology where quantification of various stainings performed on histological tissue sections, smears, imprints etc. is of utmost importance. Through the use of special stains biological components of interest can be given a specific colour. Qualitatively this can be evaluated visually as the presence of a specific colour. But to perform a quantitative evaluation the number of stained cell nuclei and/or the proportion of specimen area that has been stained needs to be measured. Pure visual estimates of this provide very crude results with poor inter- and intraobserver reproducibility. For this purpose computerised image analysis based methods are needed. The methods presented in this thesis aim to make the quantification objective and reproducible.A new supervised method for computing a pixelwise box classifier has been developed. The resulting classifier can be applied to images of the same type as the training image as long as the lighting conditions have not been changed. The main advantage of this method is that time will be saved if there are many similar images to classify, since box/classification is a fast method.In order to reduce user interaction, automatic methods for classification, based on more specific knowledge about the images, were developed. These methods include automatic classification of two types of roundish objects, e.g. cell nuclei, on a lighter background, first without, and then with the help of reference images of external cultured cells stained together with the specimen. A method for automatic segmentation of dark thin structures, e.g. microvessels, has been developed as well.A characteristic of all these methods is that they are implemented as a sequence of single colour band operations, instead of multiband operations. The purpose of this is to make the operations simple and efficient.
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| 37. |
- Ranefall, Petter, 1968-, et al.
(författare)
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Viewing and analyzing slide scanner data using CellProfiler (work in progress)
- 2013
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Ingår i: European BioImage Analysis Symposium 2013. ; , s. 58-
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Viewing and analyzing slide scanner data using CellProfiler (work in progress)Petter Ranefall1, Alexandra Pacureanu1, and Carolina Wählby1,21Centre for Image Analysis, Department of Information Technology, Uppsala University, and Science for Life Laboratory, Sweden2Imaging Platform, Broad Institute of Harvard and MIT, Cambridge, MA, USA The amount of image data in a slide scanner image is usually very large, inducing challenges for image analysis and visualization. We would like to use the strengths and flexibility of CellProfiler for the image analysis, but performing high-resolution image analysis on large slide scanner images is unfortunately not possible due to memory limitations. At the same time, we would like to visualize the results of the analysis in the context of the full tissue slide so that for example phenotypic variations at the sub-cellular level can be related to lower-resolution structures such as vessels, ducts, or tumors in the tissue. To approach this problem we split the image into smaller tiles that are more suitable for CellProfiler to handle. By keeping track of the coordinates of the tiles we can display the results on the original, full-size image. Our aim is to enable visual examination at multiple resolutions and with the option to toggle results such as segmentation masks and classification results on or off using a “Google Maps” type of view. In particular, we work with tissue profiling by in situ sequencing of RNA molecules. The tissue samples have to be removed from the microscope for each new sequencing cycle. In this case, and in other applications dealing with repeated staining, there are often differences in the alignment between the imaging rounds. We assume that these misalignments are rigid (only translation and rotation), and we have added an image registration step in order to align the different channels before partitioning the images into tiles suitable for analysis in CellProfiler.
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| 38. |
- Ranefall, Petter, 1968-, et al.
(författare)
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Your New Default Thresholding Method? : A robust global gray-level thresholding method based on object features
- 2015
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Ingår i: BioImage Informatics Conference 2015.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- We present a new robust method for global gray-level thresholding. The method is based on object features and the input is an interval of the expected object sizes. It is especially suitable for biomedical microscopy applications where objects often vary in number, but have limited variation in size. Our vision is that this method should be the first thresholding method you try when designing a pipeline for object segmentation, and thus your new default method.
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| 39. |
- Sadanandan, Sajith Kecheril, 1983-
(författare)
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Deep Neural Networks and Image Analysis for Quantitative Microscopy
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Understanding biology paves the way for discovering drugs targeting deadly diseases like cancer, and microscopy imaging is one of the most informative ways to study biology. However, analysis of large numbers of samples is often required to draw statistically verifiable conclusions. Automated approaches for analysis of microscopy image data makes it possible to handle large data sets, and at the same time reduce the risk of bias. Quantitative microscopy refers to computational methods for extracting measurements from microscopy images, enabling detection and comparison of subtle changes in morphology or behavior induced by varying experimental conditions. This thesis covers computational methods for segmentation and classification of biological samples imaged by microscopy.Recent increase in computational power has enabled the development of deep neural networks (DNNs) that perform well in solving real world problems. This thesis compares classical image analysis algorithms for segmentation of bacteria cells and introduces a novel method that combines classical image analysis and DNNs for improved cell segmentation and detection of rare phenotypes. This thesis also demonstrates a novel DNN for segmentation of clusters of cells (spheroid), with varying sizes, shapes and textures imaged by phase contrast microscopy. DNNs typically require large amounts of training data. This problem is addressed by proposing an automated approach for creating ground truths by utilizing multiple imaging modalities and classical image analysis. The resulting DNNs are applied to segment unstained cells from bright field microscopy images. In DNNs, it is often difficult to understand what image features have the largest influence on the final classification results. This is addressed in an experiment where DNNs are applied to classify zebrafish embryos based on phenotypic changes induced by drug treatment. The response of the trained DNN is tested by ablation studies, which revealed that the networks do not necessarily learn the features most obvious at visual examination. Finally, DNNs are explored for classification of cervical and oral cell samples collected for cancer screening. Initial results show that the DNNs can respond to very subtle malignancy associated changes. All the presented methods are developed using open-source tools and validated on real microscopy images.
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| 40. |
- Sadanandan, Sajith Kecheril, et al.
(författare)
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Segmentation and Track-Analysis in Time-Lapse Imaging of Bacteria
- 2016
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Ingår i: IEEE Journal on Selected Topics in Signal Processing. - : IEEE Communications Society. - 1932-4553 .- 1941-0484. ; 10:1, s. 174-184
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we have developed tools to analyze prokaryotic cells growing in monolayers in a microfluidic device. Individual bacterial cells are identified using a novel curvature based approach and tracked over time for several generations. The resulting tracks are thereafter assessed and filtered based on track quality for subsequent analysis of bacterial growth rates. The proposed method performs comparable to the state-of-the-art methods for segmenting phase contrast and fluorescent images, and we show a 10-fold increase in analysis speed.
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| 41. |
- Smirnova, Anna, et al.
(författare)
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Increased apoptosis, reduced Wnt/beta-catenin signaling, and altered tail development in zebrafish embryos exposed to a human-relevant chemical mixture
- 2021
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Ingår i: Chemosphere. - : Elsevier. - 0045-6535 .- 1879-1298. ; 264:1
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Tidskriftsartikel (refereegranskat)abstract
- A wide variety of anthropogenic chemicals is detected in humans and wildlife and the health effects of various chemical exposures are not well understood. Early life stages are generally the most susceptible to chemical disruption and developmental exposure can cause disease in adulthood, but the mechanistic understanding of such effects is poor. Within the EU project EDC-MixRisk, a chemical mixture (Mixture G) was identified in the Swedish pregnancy cohort SELMA by the inverse association between levels in women at around gestational week ten with birth weight of their children. This mixture was composed of mono-ethyl phthalate, mono-butyl phthalate, mono-benzyl phthalate, mono-ethylhexyl phthalate, mono-isononyl phthalate, triclosan, perfluorohexane sulfonate, perfluorooctanoic acid, and perfluorooctane sulfonate. In a series of experimental studies, we characterized effects of Mixture G on early development in zebrafish models. Here, we studied apoptosis and Wnt/beta-catenin signaling which are two evolutionarily conserved signaling pathways of crucial importance during development. We determined effects on apoptosis by measuring TUNEL staining, caspase-3 activity, and acridine orange staining in wildtype zebrafish embryos, while Wnt/beta-catenin signaling was assayed using a transgenic line expressing an EGFP reporter at beta-catenin-regulated promoters. We found that Mixture G increased apoptosis, suppressed Wnt/beta-catenin signaling in the caudal fin, and altered the shape of the caudal fin at water concentrations only 20-100 times higher than the geometric mean serum concentration in the human cohort. These findings call for awareness that pollutant mixtures like mixture G may interfere with a variety of developmental processes, possibly resulting in adverse health effects.
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| 42. |
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| 43. |
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| 44. |
- Wang, Yizhi, et al.
(författare)
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SynQuant : an automatic tool to quantify synapses from microscopy images
- 2020
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811 .- 1460-2059. ; 36:5, s. 1599-1606
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: Synapses are essential to neural signal transmission. Therefore, quantification of synapses and related neurites from images is vital to gain insights into the underlying pathways of brain functionality and diseases. Despite the wide availability of synaptic punctum imaging data, several issues are impeding satisfactory quantification of these structures by current tools. First, the antibodies used for labeling synapses are not perfectly specific to synapses. These antibodies may exist in neurites or other cell compartments. Second, the brightness of different neurites and synaptic puncta is heterogeneous due to the variation of antibody concentration and synapse-intrinsic differences. Third, images often have low signal to noise ratio due to constraints of experiment facilities and availability of sensitive antibodies. These issues make the detection of synapses challenging and necessitates developing a new tool to easily and accurately quantify synapses.Results: We present an automatic probability-principled synapse detection algorithm and integrate it into our synapse quantification tool SynQuant. Derived from the theory of order statistics, our method controls the false discovery rate and improves the power of detecting synapses. SynQuant is unsupervised, works for both 2D and 3D data, and can handle multiple staining channels. Through extensive experiments on one synthetic and three real datasets with ground truth annotation or manually labeling, SynQuant was demonstrated to outperform peer specialized unsupervised synapse detection tools as well as generic spot detection methods.
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| 45. |
- Wester, Kenneth, et al.
(författare)
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Automatic quantification of microvessel density in urinary bladder carcinoma
- 1999
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Ingår i: British Journal of Cancer. - : CHURCHILL LIVINGSTONE. - 0007-0920 .- 1532-1827. ; 81:8, s. 1363-1370
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Tidskriftsartikel (refereegranskat)abstract
- Seventy-three TUR-T biopsies from bladder carcinoma were evaluated regarding microvessel density, defined as microvessel number (nMVD) and cross-section endothelial cell area (aMVD). A semi-automatic and a newly developed, automatic image analysis techniq
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| 46. |
- Wester, Kenneth, et al.
(författare)
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Cultured human fibroblasts in agarose gel as a multi-functional control for immunohistochemistry : Standardization Of Ki67 (MIB1) assessment in routinely processed urinary bladder carcinoma tissue
- 2000
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Ingår i: Journal of Pathology. - 0022-3417 .- 1096-9896. ; 190:4, s. 503-11
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Tidskriftsartikel (refereegranskat)abstract
- Immunohistochemistry (IHC) in clinical practice is hampered by lack of standardization and by subjectivity in interpretation and quantitation. This study aimed to develop a control system for IHC in routinely fixed and histoprocessed tissues. Such a system should be easy to handle in clinical practice and should reflect variations in fixation time, section thickness, section storage conditions, and staining protocols. In addition, in image analysis quantitation of immunostained tissues, when using classifiers computed on IHC-control images, the control system should be very stable. Cultured human fibroblasts were suspended in agarose, transferred into a length of tubing and stored at 4 degrees C. Three pieces of the cellgel control were separately fixed, histoprocessed, and paraffin-embedded as external controls. One piece was prepared together with each of 18 bladder carcinoma biopsies as internal controls. Slides with sections from the biopsy and all types of cellgel controls were stored at different temperatures and then stained using three different IHC protocols. The fibroblasts were homogeneously distributed in the agarose gel. Variation in section thickness did not influence immunostaining as evaluated by the MIB1 labelling index (MIB1 LI). The external controls decreased notably in MIB1 LI with increased fixation time. This was not seen in the 18 internal controls that were each fixed with a fresh biopsy. However, section storage and immunostaining conditions influenced the MIB1 expression equally in all control types and to a similar degree to the biopsies. Furthermore, colour-based image analysis quantitation of MIB1 LI in biopsies proved stable and independent of the control type used to compute the classifier.
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| 47. |
- Wu, Chi-Chih, et al.
(författare)
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In situ quantification of individual mRNA transcripts in melanocytes discloses gene regulation of relevance to speciation
- 2019
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Ingår i: Journal of Experimental Biology. - : COMPANY BIOLOGISTS LTD. - 0022-0949 .- 1477-9145. ; 222:5
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Tidskriftsartikel (refereegranskat)abstract
- Functional validation of candidate genes involved in adaptation and speciation remains challenging. Here, we exemplify the utility of a method quantifying individual mRNA transcripts in revealing the molecular basis of divergence in feather pigment synthesis during early-stage speciation in crows. Using a padlock probe assay combined with rolling circle amplification, we quantified cell-typespecific gene expression in the histological context of growing feather follicles. Expression of Tyrosinase Related Protein 1 (TYRP1), Solute Carrier Family 45 member 2 (SLC45A2) and Hematopoietic Prostaglandin D Synthase (HPGDS) was melanocyte-limited and significantly reduced in follicles from hooded crow, explaining the substantially lower eumelanin content in grey versus black feathers. The central upstream Melanocyte Inducing Transcription Factor (MITF) only showed differential expression specific to melanocytes - a feature not captured by bulk RNA-seq. Overall, this study provides insight into the molecular basis of an evolutionary young transition in pigment synthesis, and demonstrates the power of histologically explicit, statistically substantiated single-cell gene expression quantification for functional genetic inference in natural populations.
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