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imaris 10 1 0 3d image analysis software  (Oxford Instruments)


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    Structured Review

    Oxford Instruments imaris 10 1 0 3d image analysis software
    Imaris 10 1 0 3d Image Analysis Software, supplied by Oxford Instruments, used in various techniques. Bioz Stars score: 99/100, based on 44266 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/3d+image+analysis+software/Imaris/pm42217685-153-8-8
    Average 99 stars, based on 44266 article reviews
    imaris 10 1 0 3d image analysis software - by Bioz Stars, 2026-09
    99/100 stars

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    Related Articles

    Software:

    Article Title: The microcephaly gene ASPM is required for the timely generation of human outer-radial glia progenitors by controlling mitotic spindle orientation
    Article Snippet: .. For this reason, we did a 3D analysis by reconstructing confocal z-stacks with Imaris 3D Image analysis software (Bitplane) and subsequent computational calculation. ..

    Article Title: Temporal and Spatial Characterization of CUL3 KLHL20 -driven Targeted Degradation of BET family, BRD Proteins by the Macrocycle-based Degrader BTR2004
    Article Snippet: .. We quantified the signal intensity and localization using the Imaris 3D image analysis software ( ). ..

    Article Title: Immunofluorescence analysis of human eosinophils.
    Article Snippet: .. Imaris 3D image analysis software (Version 9.9.1, Bitplane AG, Switzerland) was used to create an object-based colocalization protocol that complemented measures of colocalization using correlation coefficients. ..

    Article Title: Morphological basis of the lung adenocarcinoma subtypes
    Article Snippet: .. We detected each green labeled PC9 cell with Imaris 3D image analysis software and measured the distances to the nearest neighbor cells. ..

    Article Title: Systemic administration of a novel Beclin 1-derived peptide significantly upregulates autophagy in the spinal motor neurons of autophagy reporter mice.
    Article Snippet: Autophagy, an intracellular degradation system, plays a vital role in protecting cells by clearing damaged organelles, pathogens, and protein aggregates.. Autophagy upregulation through pharmacological interventions has gained significant attention as a potential therapeutic avenue for proteinopathies.. Here, we report the development of an autophagy-inducing peptide (BCN4) derived from the Beclin 1 protein, the master regulator of autophagy.

    Article Title: Advancing preclinical drug evaluation through automated 3D imaging for high-throughput screening with kidney organoids.
    Article Snippet: .. The acquired images were analyzed using the IMARIS 3D image analysis software, connected to Image J-Fiji with the LABKIT (machine-learning) plugin [25]. ..

    Article Title: The microcephaly gene ASPM is required for the timely generation of human outer-radial glia progenitors by controlling mitotic spindle orientation
    Article Snippet: .. Therefore, confocal images with z-stacks of 500 nm were taken and three-dimensionally reconstructed using Imaris 3D Image analysis software (Bitplane). ..

    Article Title: Uterine collagen deposition fluctuates throughout the estrous cycle and provides a scaffold for gland visualization via the SHG-casting method
    Article Snippet: .. To further test how the automated SHG-casting method could be used for gland morphology analysis, segmentation maps of the SHG scans ( A–8D and A–S2L) were analyzed using Imaris 3D image analysis software to assess whether it would be possible to isolate individual uterine glands. ..

    Labeling:

    Article Title: Morphological basis of the lung adenocarcinoma subtypes
    Article Snippet: .. We detected each green labeled PC9 cell with Imaris 3D image analysis software and measured the distances to the nearest neighbor cells. ..

    Activity Assay:

    Article Title: Systemic administration of a novel Beclin 1-derived peptide significantly upregulates autophagy in the spinal motor neurons of autophagy reporter mice.
    Article Snippet: Autophagy, an intracellular degradation system, plays a vital role in protecting cells by clearing damaged organelles, pathogens, and protein aggregates.. Autophagy upregulation through pharmacological interventions has gained significant attention as a potential therapeutic avenue for proteinopathies.. Here, we report the development of an autophagy-inducing peptide (BCN4) derived from the Beclin 1 protein, the master regulator of autophagy.



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    <t>SHG</t> intensity measurements in <t>3D</t> scans reflect fluctuations in fibrillar collagen deposition in the mouse uterus across the estrous cycle (A–D) Representative 3D SHG scans of (A) proestrus, (B) estrus, (C) metestrus, and (D) diestrus uteri showing the myometrium and the endometrium. The location of the representative z stack slice (white dashed line) showing gland outlines is depicted later in discussion in (E–F). (E–H) Representative z stack images from 3D reconstruction showing variations in gland outlines in (E) proestrus, (F) estrus, (G) metestrus, and (H) diestrus scans. Arrowheads point to fibrillar collagen-gland cage, green star marks the uterine gland place that appears like a “hole” in SHG scans. (E’–H’) Fibrillar collagen cage enlarged ratio map showing the SHG intensity fold change of gland fibrillar collagen cage in relation to the endometrium in (E’) proestrus, (F’) estrus, (G’) metestrus, and (H’) diestrus scans. The entire image was divided by its mean gray value and is shown, scaled for changes from 1 to 50-fold. (I) Endometrial stroma SHG intensity measurements across the estrous cycle. Green cubes illustrate representative places from where SHG intensity measurements were taken. (J) SHG intensity fold-change measurements of differences in gland fibrillar collagen cages across the estrous cycle. AM, antimesometrial; En, endometrium; M, mesometrial; Myo; myometrium, SHG, second harmonic generation. Statistical analyses were performed with one-way ANOVA followed by the Tukey post hoc test. P values below 0.05 are reported in the graphs. The results are shown as individual data points with mean ± s.d., n = 3 uteri/estrous cycle phase. The data points in I represent the average of five ROI measurements per uterus. The data points in J represent one uterine gland z stack analyzed per uteri. Scale bars for (A–D) are 100 μm and for (E–H’) are 50 μm.
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    Image Search Results


    SHG intensity measurements in 3D scans reflect fluctuations in fibrillar collagen deposition in the mouse uterus across the estrous cycle (A–D) Representative 3D SHG scans of (A) proestrus, (B) estrus, (C) metestrus, and (D) diestrus uteri showing the myometrium and the endometrium. The location of the representative z stack slice (white dashed line) showing gland outlines is depicted later in discussion in (E–F). (E–H) Representative z stack images from 3D reconstruction showing variations in gland outlines in (E) proestrus, (F) estrus, (G) metestrus, and (H) diestrus scans. Arrowheads point to fibrillar collagen-gland cage, green star marks the uterine gland place that appears like a “hole” in SHG scans. (E’–H’) Fibrillar collagen cage enlarged ratio map showing the SHG intensity fold change of gland fibrillar collagen cage in relation to the endometrium in (E’) proestrus, (F’) estrus, (G’) metestrus, and (H’) diestrus scans. The entire image was divided by its mean gray value and is shown, scaled for changes from 1 to 50-fold. (I) Endometrial stroma SHG intensity measurements across the estrous cycle. Green cubes illustrate representative places from where SHG intensity measurements were taken. (J) SHG intensity fold-change measurements of differences in gland fibrillar collagen cages across the estrous cycle. AM, antimesometrial; En, endometrium; M, mesometrial; Myo; myometrium, SHG, second harmonic generation. Statistical analyses were performed with one-way ANOVA followed by the Tukey post hoc test. P values below 0.05 are reported in the graphs. The results are shown as individual data points with mean ± s.d., n = 3 uteri/estrous cycle phase. The data points in I represent the average of five ROI measurements per uterus. The data points in J represent one uterine gland z stack analyzed per uteri. Scale bars for (A–D) are 100 μm and for (E–H’) are 50 μm.

    Journal: iScience

    Article Title: Uterine collagen deposition fluctuates throughout the estrous cycle and provides a scaffold for gland visualization via the SHG-casting method

    doi: 10.1016/j.isci.2025.113989

    Figure Lengend Snippet: SHG intensity measurements in 3D scans reflect fluctuations in fibrillar collagen deposition in the mouse uterus across the estrous cycle (A–D) Representative 3D SHG scans of (A) proestrus, (B) estrus, (C) metestrus, and (D) diestrus uteri showing the myometrium and the endometrium. The location of the representative z stack slice (white dashed line) showing gland outlines is depicted later in discussion in (E–F). (E–H) Representative z stack images from 3D reconstruction showing variations in gland outlines in (E) proestrus, (F) estrus, (G) metestrus, and (H) diestrus scans. Arrowheads point to fibrillar collagen-gland cage, green star marks the uterine gland place that appears like a “hole” in SHG scans. (E’–H’) Fibrillar collagen cage enlarged ratio map showing the SHG intensity fold change of gland fibrillar collagen cage in relation to the endometrium in (E’) proestrus, (F’) estrus, (G’) metestrus, and (H’) diestrus scans. The entire image was divided by its mean gray value and is shown, scaled for changes from 1 to 50-fold. (I) Endometrial stroma SHG intensity measurements across the estrous cycle. Green cubes illustrate representative places from where SHG intensity measurements were taken. (J) SHG intensity fold-change measurements of differences in gland fibrillar collagen cages across the estrous cycle. AM, antimesometrial; En, endometrium; M, mesometrial; Myo; myometrium, SHG, second harmonic generation. Statistical analyses were performed with one-way ANOVA followed by the Tukey post hoc test. P values below 0.05 are reported in the graphs. The results are shown as individual data points with mean ± s.d., n = 3 uteri/estrous cycle phase. The data points in I represent the average of five ROI measurements per uterus. The data points in J represent one uterine gland z stack analyzed per uteri. Scale bars for (A–D) are 100 μm and for (E–H’) are 50 μm.

    Article Snippet: To further test how the automated SHG-casting method could be used for gland morphology analysis, segmentation maps of the SHG scans ( A–8D and A–S2L) were analyzed using Imaris 3D image analysis software to assess whether it would be possible to isolate individual uterine glands.

    Techniques:

    Second harmonic generation and immunostaining reveal endometrial fibrillar collagen cages surrounding uterine glands (A–B’’) Representative images from z stack image show (A) uterine gland-specific FOXA2 staining (magenta), (A’) SHG signal (gold) from fibrillar collagen cages around glands, and (A’’) merged FOXA2 and SHG. 3D reconstructions of whole-mount uterus (B) stained with FOXA2 antibody depicting uterine glands, (B’) SHG signal depicting fibrillar collagens, and (B’’) merged FOXA2 and SHG signals. (C) Fibrillar collagen-rich stromal ECM has a more intense SHG signal at the gland cage. A basement membrane (white) underlies the epithelium in the glands and lumen. Because it is mainly composed of collagen IV, a non-fibrillar collagen, it is SHG-negative. Glandular epithelium is FOXA2 (nuclear stain, magenta) positive but has no fibrillar collagen content. Luminal epithelium (light blue) and lumen (dark gray) do not contain fibrillar collagen or express FOXA2, so they are negative for all of the listed markers. Scale bars (A–B’') are 100 μm. n = 3 independently stained pieces from 1 uterus.

    Journal: iScience

    Article Title: Uterine collagen deposition fluctuates throughout the estrous cycle and provides a scaffold for gland visualization via the SHG-casting method

    doi: 10.1016/j.isci.2025.113989

    Figure Lengend Snippet: Second harmonic generation and immunostaining reveal endometrial fibrillar collagen cages surrounding uterine glands (A–B’’) Representative images from z stack image show (A) uterine gland-specific FOXA2 staining (magenta), (A’) SHG signal (gold) from fibrillar collagen cages around glands, and (A’’) merged FOXA2 and SHG. 3D reconstructions of whole-mount uterus (B) stained with FOXA2 antibody depicting uterine glands, (B’) SHG signal depicting fibrillar collagens, and (B’’) merged FOXA2 and SHG signals. (C) Fibrillar collagen-rich stromal ECM has a more intense SHG signal at the gland cage. A basement membrane (white) underlies the epithelium in the glands and lumen. Because it is mainly composed of collagen IV, a non-fibrillar collagen, it is SHG-negative. Glandular epithelium is FOXA2 (nuclear stain, magenta) positive but has no fibrillar collagen content. Luminal epithelium (light blue) and lumen (dark gray) do not contain fibrillar collagen or express FOXA2, so they are negative for all of the listed markers. Scale bars (A–B’') are 100 μm. n = 3 independently stained pieces from 1 uterus.

    Article Snippet: To further test how the automated SHG-casting method could be used for gland morphology analysis, segmentation maps of the SHG scans ( A–8D and A–S2L) were analyzed using Imaris 3D image analysis software to assess whether it would be possible to isolate individual uterine glands.

    Techniques: Immunostaining, Staining, Membrane

    Schematic diagram illustrating the SHG-casting method (A) Conventional casting method where a mold, containing the hollowed form of the object of interest, is filled. When the mold is removed, the cast of the object of interest is revealed. (B) The SHG-casting method is shown, where the fibrillar collagen-rich extracellular matrix, detected by SHG, serves as a mold. The negative spaces in the extracellular matrix, the result of uterine glands not expressing fibrillar collagen, are digitally filled, resulting in the recreation of the 3D form of a uterine gland. SHG, second harmonic generation.

    Journal: iScience

    Article Title: Uterine collagen deposition fluctuates throughout the estrous cycle and provides a scaffold for gland visualization via the SHG-casting method

    doi: 10.1016/j.isci.2025.113989

    Figure Lengend Snippet: Schematic diagram illustrating the SHG-casting method (A) Conventional casting method where a mold, containing the hollowed form of the object of interest, is filled. When the mold is removed, the cast of the object of interest is revealed. (B) The SHG-casting method is shown, where the fibrillar collagen-rich extracellular matrix, detected by SHG, serves as a mold. The negative spaces in the extracellular matrix, the result of uterine glands not expressing fibrillar collagen, are digitally filled, resulting in the recreation of the 3D form of a uterine gland. SHG, second harmonic generation.

    Article Snippet: To further test how the automated SHG-casting method could be used for gland morphology analysis, segmentation maps of the SHG scans ( A–8D and A–S2L) were analyzed using Imaris 3D image analysis software to assess whether it would be possible to isolate individual uterine glands.

    Techniques: Expressing

    Fibrillar collagen detected by SHG provides a template for 3D gland reconstruction by the SHG-casting method (A–D) Representative 2D digital slice images of (A) fibrillar collagen detected by SHG (gold) forming a cage around the uterine gland and (B) uterine gland, identified by FOXA2 immunostaining (magenta). (C) Tracing of SHG outline (green) (D) aligns with FOXA2 staining (magenta). (E–H) 3D reconstruction of (E) SHG fibrillar collagen (gold), (F) FOXA2 staining of a uterine gland (magenta), (G) 3D reconstruction of gland tracing (green), and (H) merged uterine gland reconstructions of FOXA2 (magenta) and tracing (green). SHG; second harmonic generation. Scale bars are 50 μm. n = 2 manually traced scans.

    Journal: iScience

    Article Title: Uterine collagen deposition fluctuates throughout the estrous cycle and provides a scaffold for gland visualization via the SHG-casting method

    doi: 10.1016/j.isci.2025.113989

    Figure Lengend Snippet: Fibrillar collagen detected by SHG provides a template for 3D gland reconstruction by the SHG-casting method (A–D) Representative 2D digital slice images of (A) fibrillar collagen detected by SHG (gold) forming a cage around the uterine gland and (B) uterine gland, identified by FOXA2 immunostaining (magenta). (C) Tracing of SHG outline (green) (D) aligns with FOXA2 staining (magenta). (E–H) 3D reconstruction of (E) SHG fibrillar collagen (gold), (F) FOXA2 staining of a uterine gland (magenta), (G) 3D reconstruction of gland tracing (green), and (H) merged uterine gland reconstructions of FOXA2 (magenta) and tracing (green). SHG; second harmonic generation. Scale bars are 50 μm. n = 2 manually traced scans.

    Article Snippet: To further test how the automated SHG-casting method could be used for gland morphology analysis, segmentation maps of the SHG scans ( A–8D and A–S2L) were analyzed using Imaris 3D image analysis software to assess whether it would be possible to isolate individual uterine glands.

    Techniques: Immunostaining, Staining

    Deep learning-based segmentation model accurately recognizes and segments the fibrillar collagen cage (A) Schematic diagram shows the training and validation of machine learning trained model, featuring training to recognize the gland and lumen fibrillar collagen cages (SHG path), and to validate these segmentation and subsequent 3D reconstruction against that of FOXA2 uterine gland-specific whole-mount immunostaining (immunostaining path). (B and C) Representative images of 2D slices of (B, B’) SHG scan showing the negative imprints of uterine glands surrounded by fibrillar collagen cages in the x–y (top, B) and z (bottom, B’) planes, and the (C, C’) automatic segmentation of uterine gland imprints in the same regions in the x–y (top, C) and z (bottom, C’) planes. (D) The 3D model of uterine gland morphology resulting from the automatic segmentation of the complete SHG scan. (E) The Dice similarity coefficient (DSC), which compares the overlap of the reference 3D reconstruction to the SHG-casting segmentation model 3D reconstruction, is calculated by adding the overlap between the two methods together (lime green), divided by the total volume of the reference 3D model (yellow) with the volume from the SHG-casting segmentation model (green). The DSC is 93.8%. (F) Intersection over union (IoU) is a segmentation metric that measures the area overlap (intersection, bright green) between the SHG-casting segmentation model (green) and that of the reference (yellow), divided by the total area of both the model and reference (green) combined (union, bright green). The IoU score was 88.4%. (G) Hausdorff distance (HD) is a measure that assesses the worst case difference in distance between two sets of points in the model (green) and the reference (yellow). The HD is 5.5 voxels. Representative images to describe DSC, IoU, and HD were based on images from Pálsson et al. and Huynh.

    Journal: iScience

    Article Title: Uterine collagen deposition fluctuates throughout the estrous cycle and provides a scaffold for gland visualization via the SHG-casting method

    doi: 10.1016/j.isci.2025.113989

    Figure Lengend Snippet: Deep learning-based segmentation model accurately recognizes and segments the fibrillar collagen cage (A) Schematic diagram shows the training and validation of machine learning trained model, featuring training to recognize the gland and lumen fibrillar collagen cages (SHG path), and to validate these segmentation and subsequent 3D reconstruction against that of FOXA2 uterine gland-specific whole-mount immunostaining (immunostaining path). (B and C) Representative images of 2D slices of (B, B’) SHG scan showing the negative imprints of uterine glands surrounded by fibrillar collagen cages in the x–y (top, B) and z (bottom, B’) planes, and the (C, C’) automatic segmentation of uterine gland imprints in the same regions in the x–y (top, C) and z (bottom, C’) planes. (D) The 3D model of uterine gland morphology resulting from the automatic segmentation of the complete SHG scan. (E) The Dice similarity coefficient (DSC), which compares the overlap of the reference 3D reconstruction to the SHG-casting segmentation model 3D reconstruction, is calculated by adding the overlap between the two methods together (lime green), divided by the total volume of the reference 3D model (yellow) with the volume from the SHG-casting segmentation model (green). The DSC is 93.8%. (F) Intersection over union (IoU) is a segmentation metric that measures the area overlap (intersection, bright green) between the SHG-casting segmentation model (green) and that of the reference (yellow), divided by the total area of both the model and reference (green) combined (union, bright green). The IoU score was 88.4%. (G) Hausdorff distance (HD) is a measure that assesses the worst case difference in distance between two sets of points in the model (green) and the reference (yellow). The HD is 5.5 voxels. Representative images to describe DSC, IoU, and HD were based on images from Pálsson et al. and Huynh.

    Article Snippet: To further test how the automated SHG-casting method could be used for gland morphology analysis, segmentation maps of the SHG scans ( A–8D and A–S2L) were analyzed using Imaris 3D image analysis software to assess whether it would be possible to isolate individual uterine glands.

    Techniques: Biomarker Discovery, Immunostaining

    Comparison between uterine gland structure derived from FOXA2 immunostaining and SHG-casting method in combination with deep learning (DL) based (semantic) segmentation model (A) 2D digital slice of FOXA2 uterine gland staining and (B) 3D reconstruction of staining. (C) 2D segmentation map from SHG-casting DL-based segmentation model from the same digital slice shown in (A), followed by 3D reconstruction in (D). Scale bar for (A) is 50 μm and 100 μm in (B).

    Journal: iScience

    Article Title: Uterine collagen deposition fluctuates throughout the estrous cycle and provides a scaffold for gland visualization via the SHG-casting method

    doi: 10.1016/j.isci.2025.113989

    Figure Lengend Snippet: Comparison between uterine gland structure derived from FOXA2 immunostaining and SHG-casting method in combination with deep learning (DL) based (semantic) segmentation model (A) 2D digital slice of FOXA2 uterine gland staining and (B) 3D reconstruction of staining. (C) 2D segmentation map from SHG-casting DL-based segmentation model from the same digital slice shown in (A), followed by 3D reconstruction in (D). Scale bar for (A) is 50 μm and 100 μm in (B).

    Article Snippet: To further test how the automated SHG-casting method could be used for gland morphology analysis, segmentation maps of the SHG scans ( A–8D and A–S2L) were analyzed using Imaris 3D image analysis software to assess whether it would be possible to isolate individual uterine glands.

    Techniques: Comparison, Derivative Assay, Immunostaining, Staining

    Comparison of workflow and time required for uterine gland 3D morphology reconstruction by whole-mount immunostaining and the automated SHG-casting method The estimated time for each step includes both hands-on work and passive waiting gaps. Scanning and analysis times are for one sample. (A) depicts the workflow of uterine gland 3D morphology reconstruction by whole-mount immunostaining, and (B) by the automated SHG-casting method. The initial steps involving specimen collection, fixation, and quenching of background signal are identical in both methods (A and B). The most significant time-related deviation comes at the immunostaining stage, taking up to 10 nights (A). Meanwhile, specimens processed by the SHG-casting method can already be chemically cleared for imaging (B). Critical to note that the SHG signal coming from fibrillar collagens is not sensitive to bleaching, enabling repetitive re-imaging of the specimens (B), whereas imaging a fluorophore associated with an antibody is bleaching the signal permanently (A). SHG; second harmonic generation. Uterus graphic is from BioRender: Savolainen, A. (2025) https://BioRender.com/jie1q29 .

    Journal: iScience

    Article Title: Uterine collagen deposition fluctuates throughout the estrous cycle and provides a scaffold for gland visualization via the SHG-casting method

    doi: 10.1016/j.isci.2025.113989

    Figure Lengend Snippet: Comparison of workflow and time required for uterine gland 3D morphology reconstruction by whole-mount immunostaining and the automated SHG-casting method The estimated time for each step includes both hands-on work and passive waiting gaps. Scanning and analysis times are for one sample. (A) depicts the workflow of uterine gland 3D morphology reconstruction by whole-mount immunostaining, and (B) by the automated SHG-casting method. The initial steps involving specimen collection, fixation, and quenching of background signal are identical in both methods (A and B). The most significant time-related deviation comes at the immunostaining stage, taking up to 10 nights (A). Meanwhile, specimens processed by the SHG-casting method can already be chemically cleared for imaging (B). Critical to note that the SHG signal coming from fibrillar collagens is not sensitive to bleaching, enabling repetitive re-imaging of the specimens (B), whereas imaging a fluorophore associated with an antibody is bleaching the signal permanently (A). SHG; second harmonic generation. Uterus graphic is from BioRender: Savolainen, A. (2025) https://BioRender.com/jie1q29 .

    Article Snippet: To further test how the automated SHG-casting method could be used for gland morphology analysis, segmentation maps of the SHG scans ( A–8D and A–S2L) were analyzed using Imaris 3D image analysis software to assess whether it would be possible to isolate individual uterine glands.

    Techniques: Comparison, Immunostaining, Imaging