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wiener filter based deconvolution  (Carl Zeiss)


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    Carl Zeiss wiener filter based deconvolution
    Wiener Filter Based Deconvolution, supplied by Carl Zeiss, used in various techniques. Bioz Stars score: 94/100, based on 67 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/based+deconvolution+filter/pm33181147-93-26-38
    Average 94 stars, based on 67 article reviews
    wiener filter based deconvolution - by Bioz Stars, 2026-09
    94/100 stars

    Images

    Related Articles

    Immunolabeling:

    Article Title: Ventral hippocampal interneurons govern extinction and relapse of contextual associations
    Article Snippet: .. Fluorescent confocal images of immunolabeled tissue were acquired on a Zeiss LSM 780 with a 20x objective and suitable filter sets in tiled z stack images (4 μm steps) that were stitched using the Zen Black software v. 8.1 (Carl Zeiss). ..

    Software:

    Article Title: Ventral hippocampal interneurons govern extinction and relapse of contextual associations
    Article Snippet: .. Fluorescent confocal images of immunolabeled tissue were acquired on a Zeiss LSM 780 with a 20x objective and suitable filter sets in tiled z stack images (4 μm steps) that were stitched using the Zen Black software v. 8.1 (Carl Zeiss). ..

    Article Title: Spatially fractionated minibeam radiation delivered at clinically feasible dose rates induces transient vascular permeability
    Article Snippet: .. For synchrotron irradiations, CAM vasculature was then observed with a Zeiss Axioscope fluorescent microscope (Zeiss AG, Oberkocken, Germany) using a 450–490/515–565 nm emission/excitation filter (Zeiss Filter Set 10) and recorded with a monochromatic industrial camera (Baumer model VCXU-50 M; Baumer International GmbH, Stockach, Germany) controlled by Baumer Camera Explorer v3.3.0 software. .. For orthovoltage irradiations, images were acquired using a Nikon SMZ stereo microscope equipped with a Digital Sight Ri2 camera (Nikon Instruments, New York, USA).

    Control:

    Article Title: Comparison of accumulation and distribution of PEGylated and CD-47-functionalized magnetic nanoporous silica nanoparticles in an in vivo mouse model of implant infection
    Article Snippet: The unstained tissue slices were analyzed using a fluorescence microscope (Axioskop 40, Carl Zeiss AG, Oberkochen, Germany). .. For nanoparticle detection a red filter (filter set 20, Excitatation BP 546/12, Beam Splitter FT 560, Emission BP 575–640, Carl Zeiss AG, Oberkochen, Germany) and for the control of autofluorescence a green filter (filter set 44, Excitation BP 475/40, Beam Splitter FT 500, Emission BP 530/50, Carl Zeiss AG, Oberkochen, Germany) was used. ..

    Staining:

    Article Title: Genotype-specific differences in infertile men due to loss-of-function variants in M1AP or ZZS genes.
    Article Snippet: Immunofluorescence staining of meiotic spreads was complied with a Zeiss Elyra 7 microscope for specialised 3D structured illumination (SIM2) and the Zeiss Zen black software (TEX11 and MLH1 labelled meiotic spreads) or a Leica DM6 B TL microscope and the LASX Software (RAD51 and MSH5 labelled meiotic spreads). .. Suitable filter sets (Zeiss Elyra 7: DAPI/GFP/TXR/Y5 or Leica DM6 B TL: Filtersystem A/D/I3/N2.1) were used to visualise fluorophore-based antibody staining. .. Image processing was achieved with the open-source software Fiji by ImageJ (v2.3.0/1.54 h).

    Fluorescence:

    Article Title: Absence of genotoxic effects of high dietary levels of milk proteins associated or not with free or acylated lutein: an in vivo study using rats
    Article Snippet: Although diets with high dietary content of milk proteins are extensively used in the sports nutrition segment, there is evidence that they could induce damage to colonocyte DNA in rats.. In this study, we have evaluated whether genotoxic effects are induced in the bone marrow or peripheral blood of Wistar rats fed with diets containing high dietary content of milk proteins (casein or whey protein isolate or both), and whether diets with high content of proteins submitted to dry heating (whey protein isolate) impact genotoxicity.. We have also assessed the same diets supplemented with lutein, in its free or acylated form.

    Microscopy:

    Article Title: Absence of genotoxic effects of high dietary levels of milk proteins associated or not with free or acylated lutein: an in vivo study using rats
    Article Snippet: Although diets with high dietary content of milk proteins are extensively used in the sports nutrition segment, there is evidence that they could induce damage to colonocyte DNA in rats.. In this study, we have evaluated whether genotoxic effects are induced in the bone marrow or peripheral blood of Wistar rats fed with diets containing high dietary content of milk proteins (casein or whey protein isolate or both), and whether diets with high content of proteins submitted to dry heating (whey protein isolate) impact genotoxicity.. We have also assessed the same diets supplemented with lutein, in its free or acylated form.

    Article Title: The planktonic freshwater ciliate Balanion planctonicum (Ciliophora, Prostomatea): A cryptic species complex or a “complex species”?
    Article Snippet: .. All CARD‐FISH preparations were evaluated on an Axio Imager.M1 microscope (Zeiss, Germany) at 200X magnification, equipped with an LED illumination and the Zeiss filter set 62 HE and 01 for the detection of hybridized ciliates and the DAPI counterstaining, respectively. ..

    Article Title: Spatially fractionated minibeam radiation delivered at clinically feasible dose rates induces transient vascular permeability
    Article Snippet: .. For synchrotron irradiations, CAM vasculature was then observed with a Zeiss Axioscope fluorescent microscope (Zeiss AG, Oberkocken, Germany) using a 450–490/515–565 nm emission/excitation filter (Zeiss Filter Set 10) and recorded with a monochromatic industrial camera (Baumer model VCXU-50 M; Baumer International GmbH, Stockach, Germany) controlled by Baumer Camera Explorer v3.3.0 software. .. For orthovoltage irradiations, images were acquired using a Nikon SMZ stereo microscope equipped with a Digital Sight Ri2 camera (Nikon Instruments, New York, USA).

    Chick Chorioallantoic Membrane Assay:

    Article Title: Spatially fractionated minibeam radiation delivered at clinically feasible dose rates induces transient vascular permeability
    Article Snippet: .. For synchrotron irradiations, CAM vasculature was then observed with a Zeiss Axioscope fluorescent microscope (Zeiss AG, Oberkocken, Germany) using a 450–490/515–565 nm emission/excitation filter (Zeiss Filter Set 10) and recorded with a monochromatic industrial camera (Baumer model VCXU-50 M; Baumer International GmbH, Stockach, Germany) controlled by Baumer Camera Explorer v3.3.0 software. .. For orthovoltage irradiations, images were acquired using a Nikon SMZ stereo microscope equipped with a Digital Sight Ri2 camera (Nikon Instruments, New York, USA).

    Imaging:

    Article Title: Neuronal p38a knockout protects against neurological consequences following repetitive mild traumatic brain injury
    Article Snippet: On day 2, sections were incubated with Alexa Fluor 555 secondary antibody (1:200; ThermoFisher) diluted in blocking buffer, counterstained with 4′,6-diamidino-2-phenylindole (DAPI;1 μg/mL), and mounted with 10% glycerol in phosphate-buffered saline (PBS). .. Epifluorescence imaging was performed on a Zeiss Axio Observer Z.1 inverted microscope using a 40× objective and halogen illumination, with Zeiss filter set 49 for DAPI and set 20 for Alexa Fluor 555. ..

    Inverted Microscopy:

    Article Title: Neuronal p38a knockout protects against neurological consequences following repetitive mild traumatic brain injury
    Article Snippet: On day 2, sections were incubated with Alexa Fluor 555 secondary antibody (1:200; ThermoFisher) diluted in blocking buffer, counterstained with 4′,6-diamidino-2-phenylindole (DAPI;1 μg/mL), and mounted with 10% glycerol in phosphate-buffered saline (PBS). .. Epifluorescence imaging was performed on a Zeiss Axio Observer Z.1 inverted microscope using a 40× objective and halogen illumination, with Zeiss filter set 49 for DAPI and set 20 for Alexa Fluor 555. ..



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    MathWorks Inc wiener filtering-based deconvolution
    Image <t>deconvolution</t> cannot always resolve individual fluorophore locations. (a) A typical yeast mitotic spindle experimental fluorescence image (kinetochore-associated fluorescence, green; spindle pole body fluorescence, red). (b) Theoretical point-source fluorophores (32 green points, representing individual kinetochores, and 2 red points, representing the spindle pole bodies) along a 1500 nm length. The bright green pixels indicate the presence of multiple fluorophores within the pixel area. For simplicity, it was assumed that there are no fluorophores in out-of-focus focal planes. (c) Point-source fluorophores in (a) are convolved with the microscope PSF and noise is added. (d) The image in (b) has been deconvolved using the identical PSF. The image deconvolution process cannot resolve the individual point-source fluorophores and tends to generate fluorescent “clusters” in the periphery which are artifacts of deconvolving noise
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    Image Search Results


    Image deconvolution cannot always resolve individual fluorophore locations. (a) A typical yeast mitotic spindle experimental fluorescence image (kinetochore-associated fluorescence, green; spindle pole body fluorescence, red). (b) Theoretical point-source fluorophores (32 green points, representing individual kinetochores, and 2 red points, representing the spindle pole bodies) along a 1500 nm length. The bright green pixels indicate the presence of multiple fluorophores within the pixel area. For simplicity, it was assumed that there are no fluorophores in out-of-focus focal planes. (c) Point-source fluorophores in (a) are convolved with the microscope PSF and noise is added. (d) The image in (b) has been deconvolved using the identical PSF. The image deconvolution process cannot resolve the individual point-source fluorophores and tends to generate fluorescent “clusters” in the periphery which are artifacts of deconvolving noise

    Journal: Cellular and Molecular Bioengineering

    Article Title: Model Convolution: A Computational Approach to Digital Image Interpretation

    doi: 10.1007/s12195-010-0101-7

    Figure Lengend Snippet: Image deconvolution cannot always resolve individual fluorophore locations. (a) A typical yeast mitotic spindle experimental fluorescence image (kinetochore-associated fluorescence, green; spindle pole body fluorescence, red). (b) Theoretical point-source fluorophores (32 green points, representing individual kinetochores, and 2 red points, representing the spindle pole bodies) along a 1500 nm length. The bright green pixels indicate the presence of multiple fluorophores within the pixel area. For simplicity, it was assumed that there are no fluorophores in out-of-focus focal planes. (c) Point-source fluorophores in (a) are convolved with the microscope PSF and noise is added. (d) The image in (b) has been deconvolved using the identical PSF. The image deconvolution process cannot resolve the individual point-source fluorophores and tends to generate fluorescent “clusters” in the periphery which are artifacts of deconvolving noise

    Article Snippet: Figure 2 High noise levels limit the utility of the image deconvolution method. (a1) A simulated point-source fluorophore has been convolved with a theoretical PSF (no background noise) to produce a 32 × 32 image having a single signal in the center of the field. (a2) Subsequent image deconvolution (by Wiener filtering-based deconvolution using the Matlab image processing toolbox) precisely resolves the spreading of light due to the PSF, and correctly identifies the fluorophore location to be at the center. (b1) A simulated point-source fluorophore has been convolved with a theoretical PSF, but noise has been added to the image such that the SNR = 8. (b2) In this case, subsequent image deconvolution is able to correctly resolve the fluorophore location. (b3) In another image with SNR = 8, image deconvolution is not able to separate the fluorophore from background noise and misidentifies the location of the point source. (c) The ability of Wiener-filter-based deconvolution to separate fluorophores from background noise decreases substantially with decreasing SNR.

    Techniques: Fluorescence, Microscopy

    High noise levels limit the utility of the image deconvolution method. (a1) A simulated point-source fluorophore has been convolved with a theoretical PSF (no background noise) to produce a 32 × 32 image having a single signal in the center of the field. (a2) Subsequent image deconvolution (by Wiener filtering-based deconvolution using the Matlab image processing toolbox) precisely resolves the spreading of light due to the PSF, and correctly identifies the fluorophore location to be at the center. (b1) A simulated point-source fluorophore has been convolved with a theoretical PSF, but noise has been added to the image such that the SNR = 8. (b2) In this case, subsequent image deconvolution is able to correctly resolve the fluorophore location. (b3) In another image with SNR = 8, image deconvolution is not able to separate the fluorophore from background noise and misidentifies the location of the point source. (c) The ability of Wiener-filter-based deconvolution to separate fluorophores from background noise decreases substantially with decreasing SNR. The quantitative relationship between the failure rate and the SNR depends upon the specifics of the problem, but generally failure rate increases with decreasing SNR

    Journal: Cellular and Molecular Bioengineering

    Article Title: Model Convolution: A Computational Approach to Digital Image Interpretation

    doi: 10.1007/s12195-010-0101-7

    Figure Lengend Snippet: High noise levels limit the utility of the image deconvolution method. (a1) A simulated point-source fluorophore has been convolved with a theoretical PSF (no background noise) to produce a 32 × 32 image having a single signal in the center of the field. (a2) Subsequent image deconvolution (by Wiener filtering-based deconvolution using the Matlab image processing toolbox) precisely resolves the spreading of light due to the PSF, and correctly identifies the fluorophore location to be at the center. (b1) A simulated point-source fluorophore has been convolved with a theoretical PSF, but noise has been added to the image such that the SNR = 8. (b2) In this case, subsequent image deconvolution is able to correctly resolve the fluorophore location. (b3) In another image with SNR = 8, image deconvolution is not able to separate the fluorophore from background noise and misidentifies the location of the point source. (c) The ability of Wiener-filter-based deconvolution to separate fluorophores from background noise decreases substantially with decreasing SNR. The quantitative relationship between the failure rate and the SNR depends upon the specifics of the problem, but generally failure rate increases with decreasing SNR

    Article Snippet: Figure 2 High noise levels limit the utility of the image deconvolution method. (a1) A simulated point-source fluorophore has been convolved with a theoretical PSF (no background noise) to produce a 32 × 32 image having a single signal in the center of the field. (a2) Subsequent image deconvolution (by Wiener filtering-based deconvolution using the Matlab image processing toolbox) precisely resolves the spreading of light due to the PSF, and correctly identifies the fluorophore location to be at the center. (b1) A simulated point-source fluorophore has been convolved with a theoretical PSF, but noise has been added to the image such that the SNR = 8. (b2) In this case, subsequent image deconvolution is able to correctly resolve the fluorophore location. (b3) In another image with SNR = 8, image deconvolution is not able to separate the fluorophore from background noise and misidentifies the location of the point source. (c) The ability of Wiener-filter-based deconvolution to separate fluorophores from background noise decreases substantially with decreasing SNR.

    Techniques:

    The model-convolution method as compared to the image deconvolution process. In the image deconvolution process, an experimental image is “deblurred” using the theoretical microscope PSF. With the model-convolution method, a theoretical fluorophore distribution is convolved with the microscope PSF and noise, and a simulated image is generated. Thus, the model-convolution method is essentially the inverse of the image deconvolution process. (a) The example shown is a computational model of Arp2/3-mediated actin filament branching in three dimensions based on experimental observations by Ichetovkin et al . The model results in a branched actin filament structure stemming from an initial nucleation site (1—blue arrow) and leading to a series of branches off the main filament. The model-convolution method is applied to create a theoretical microscope image at the focal plane of the main filament. Branches that are close to the focal plane of the microscope (2—orange arrow) are clearly visible in the simulated fluorescence image. Branches that project out of the focal plane (3—red arrow, and 4—white arrow) are less visible in the simulated image, indicating that the branching complexity and branch length distribution of the actin filament could be misinterpreted from experimental fluorescence images. Scale bar, 1000 nm. (b) The model-convolution approach to estimating microtubule curvature. A simulated microtubule is constructed with a known analytical function (Sine function on a 2 nm pixel grid), showing the true underlying relation of the curvature to the outer diameter. This simulated microtubule has curvature that would be at the high extreme of observed curvatures in living cells. The model-convolution operation is performed, and the resulting image is binned to the pixel size associated with a high NA lens and ccd detector (50 nm pixel size). The convolved image appears more highly curved than the underlying filament, and the digitization on the camera makes quantitative analysis of curvature prone to errors. Scale bar, 250 nm

    Journal: Cellular and Molecular Bioengineering

    Article Title: Model Convolution: A Computational Approach to Digital Image Interpretation

    doi: 10.1007/s12195-010-0101-7

    Figure Lengend Snippet: The model-convolution method as compared to the image deconvolution process. In the image deconvolution process, an experimental image is “deblurred” using the theoretical microscope PSF. With the model-convolution method, a theoretical fluorophore distribution is convolved with the microscope PSF and noise, and a simulated image is generated. Thus, the model-convolution method is essentially the inverse of the image deconvolution process. (a) The example shown is a computational model of Arp2/3-mediated actin filament branching in three dimensions based on experimental observations by Ichetovkin et al . The model results in a branched actin filament structure stemming from an initial nucleation site (1—blue arrow) and leading to a series of branches off the main filament. The model-convolution method is applied to create a theoretical microscope image at the focal plane of the main filament. Branches that are close to the focal plane of the microscope (2—orange arrow) are clearly visible in the simulated fluorescence image. Branches that project out of the focal plane (3—red arrow, and 4—white arrow) are less visible in the simulated image, indicating that the branching complexity and branch length distribution of the actin filament could be misinterpreted from experimental fluorescence images. Scale bar, 1000 nm. (b) The model-convolution approach to estimating microtubule curvature. A simulated microtubule is constructed with a known analytical function (Sine function on a 2 nm pixel grid), showing the true underlying relation of the curvature to the outer diameter. This simulated microtubule has curvature that would be at the high extreme of observed curvatures in living cells. The model-convolution operation is performed, and the resulting image is binned to the pixel size associated with a high NA lens and ccd detector (50 nm pixel size). The convolved image appears more highly curved than the underlying filament, and the digitization on the camera makes quantitative analysis of curvature prone to errors. Scale bar, 250 nm

    Article Snippet: Figure 2 High noise levels limit the utility of the image deconvolution method. (a1) A simulated point-source fluorophore has been convolved with a theoretical PSF (no background noise) to produce a 32 × 32 image having a single signal in the center of the field. (a2) Subsequent image deconvolution (by Wiener filtering-based deconvolution using the Matlab image processing toolbox) precisely resolves the spreading of light due to the PSF, and correctly identifies the fluorophore location to be at the center. (b1) A simulated point-source fluorophore has been convolved with a theoretical PSF, but noise has been added to the image such that the SNR = 8. (b2) In this case, subsequent image deconvolution is able to correctly resolve the fluorophore location. (b3) In another image with SNR = 8, image deconvolution is not able to separate the fluorophore from background noise and misidentifies the location of the point source. (c) The ability of Wiener-filter-based deconvolution to separate fluorophores from background noise decreases substantially with decreasing SNR.

    Techniques: Microscopy, Generated, Fluorescence, Construct