Introduction
Bitplane Imaris is a commercial software package for the visualization, segmentation and analysis of multidimensional microscopy datasets.
Besides open source tools such as Fiji, Imaris is the most used software at the ZMB to explore and analyze light microscopy data. The main reasons are the simplicity and the ease of use for visualization of microscopy data, segmentation and quantification in 3D and 4D. Especially for 3D visualization there are as of now no open source tools with a similar performance.
This guide will introduce you to the visualization and segmentation of 3D and 4D microscopy datasets with Bitplane Imaris.
Please also check out the other guides of the Imaris series, especially the guide Imaris Part 1: File Import Using Arena.
This guide was written using Bitplane Imaris 9.3.0.
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Reserve and open a ZMB image processing virtual machine.
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Open the most recent version of Imaris x64 (9.3.0).
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Double click to open your *.ims file.
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To make an intensity based 3D segmentation in the “3D View” go to the “Scene – Properties” pane and click the blue Icon “Add new Surface”.
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The surface creation wizard starts.
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Select “Segment only a Region of Interest” and “Process entire Image finally”.
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Click "Next"
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Define your region of interest by changing the dimensions and positions of the transparent box.
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Use “Select” to adjust the size and position of the “Region of Interest” box.
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Use “Navigate” to adjust the view.
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Visualize your channel of interest and uncheck the ones you don't need.
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If your image is very heterogeneous you can also place multiple “Regions of Interest” for a better parametrization by pressing “Add”.
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Press next.
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Select the channel you want to segment.
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Choose if you want to apply a feature smoothing and/or an adaptive thresholding with a local background subtraction.
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Since version 9.9 Imaris has the option of using machine leaning pixel classification to create surfaces! For more info check the corresponding guide or https://imaris.oxinst.com/learning/view/...
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Adjust the intensity threshold for segmentation.
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In this step you can classify/filter your surfaces using a combination of filters.
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E.g. In the second image only dimmer objects were segmented.
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Add additional filters if necessary.
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In the drop-down menu you can choose from a selection of filters.
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Once you have adjusted all parameters, you can apply the segmentation of your ROI to the whole dataset.
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When your segmentation is done, you can adjust the visualization of your surfaces, manually delete objects which are not of interest and explore and export (e.g. to excel or matlab) the statistics for each individual object or globally.
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Here you can access the statistics for your surface.
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You can also select and highlight individual components and show their corresponding statistics.
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Something very helpful to see patterns and trends in your data is the statistical coding of surface objects.
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Here you can assign a color according of one of the objects variables such as size or roundness.
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