Basic  3D  reconstruction  in  Imaris  7.6.1  

 

 

 

 

 

Task  The aim of this tutorial is to understand basic Imaris functionality by performing surface reconstruction of glia cells in culture, in order to visualize enclosed structures and perform 3D measurements. Ultimately, we will create a 3D visualization animation of our dataset.

Key  contents  of  tutorial  -­‐ Visualize dataset -­‐ Setting the scale -­‐ Mixed Model Rendering -­‐ 3D measurements -­‐ Generating movies

Load  stack  to  Imaris  In this example, we will be using a sample 3-channel z-stack obtained on a Zeiss LSM 510 confocal microscope. The stack is included in one .lsm file. Imaris can read most file formats created by various microscopes, as well as single TIFF files and many more. To import a stack of single tiff files, go to “File”, “Open…”, click on the first one image and click Settings. The images should be exported and saved in a way that Imaris can recognize channels, z position and time point for the stack to be loaded properly. See Figure 1 and 2.

Figure 1. Imaris main window and dialogue for opening image sequence. Select always the first of the images from the particular stack, and make sure the file name is formatted in a way where each image is a specific channel of the multi-dimensional data (blue arrow). To assign specific dimensions to images, click ‘Settings’ (red arrow).

Figure 2. Using the ‘Settings’ dialogue (see Figure 1) the multidimensional dataset can be loaded properly, by assigning different attributes to images depending on their filename (spatial and/or temporal position on stack, and channel). This step is of pivotal importance for appropriate multidimensional analysis.

Set  the  scale  The image dimensions or pixel to µm scaling have to be set according to the acquisition settings. Typically, this information is contained within the image metadata, or is reported by the software when the acquisition is performed. In certain occasions, with files directly produced by most microscope manufacturers, Imaris can read the metadata automatically and set the image scale. But it is always a good practice to confirm that these are correct. To set these, go to ‘Edit’, ‘Image Properties…’. In the ‘Geometry’ dialogue (Figure 3), use the Voxel size (typically reported with the

Time point

Stack position

Channel Always check whether the entire stack is recognized

same name in the image metadata) to set the µm corresponding to one pixel. In z, typically the optical slice thickness is reported.

Figure 3. The scale of the stack is set by entering the corresponding µm to 1 three-dimensional pixel (volume element - voxel) of the stack. Z typically corresponds to the value of the optical slice thickness. Additionaly, when there is a time-lapse stack, one can set the time point interval.

Verify  stack  

After loading has been completed, use the ‘Slice’ button to verify that the stack has been loaded correctly. Use the arrow next to the button to select the ‘Gallery’ option in order to visualize the

stack, merging the individual channels (Figure 3). This gives an overview of the stack slices, as well as the optical thickness and imaging depth, given that the scale is set correctly. The stack can also be examined as XZ and YZ slices, by selecting ‘Section’ using the arrow of the ‘Slice’ button. In our case, this visualization can give a first impression as to whether there are structures enclosed in the cells we are examining, before we proceed to 3D rendering. See Figure 4. At this point, the ‘Display Adjustment’ dialogue can be used (if it is not active, enable from ‘Edit’, ‘Show Display Adjustment’) to adjust the channel contrast for best visualization.

Figure 4. Section view of the stack, where XZ and YZ slices can be examined, additionally to the XY view. Planes can be changed in any view by dragging the position of the white crosshair lines (e.g. blue arrow). Using this view, we can preliminary determine whether there are potentially intracellular inclusions. The contrast of the various channels can be adjusted using the sliders in the ‘Display adjustment’ (boxed). This is a histogram based enhancement; it will not affect your data, and should only be used to improve 3D reconstruction and visualization, not to draw conclusions regarding the expression or presence of any ligands.

Examine  3D  morphology  

Use the ‘Surpass’ button to examine the 3D morphology of your stack. This is a primary intensity-based rendering of the 3D volume of the stack, and the basis of the 3D reconstruction area. The workspace is divided in 4 main parts (see Figure 5), namely the view area, the object area and the object property area and the visualization area. The ‘Display Adjustment’ window is also useful in this case to adjust for best visual contrast.

Figure 5: The main areas of the ‘Surpass’ view. This view facilitates the image navigation, selection and interaction with the 3D volume. The ‘Object’ window allows the selection of a combination of various visualisation techniques; by default, the ‘Volume’ object presents an intensity rendering of the inserted stack. The object properties can be adjusted from the respective window. The intensity rendering contrast can be adjusted for appropriate visualisation using the ‘Display Adjustment’, which is essentially a histogram-based adjustment control pane.

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Surface  Reconstruction  Reconstructing the surface of a structure is a useful visualization tool that can provide insight on the morphology of the structure, its 3D architecture as well as its interaction with nearby structures. In our example, we will use it to unveil intersections and inclusions between the microglia body (blue), the amyloid (a protein which they are supposed to phagocytize - red) and the microglia nucleus (green). The reconstruction will be analytically explained for the blue channel, and the reader may perform the reconstructions of the other channels as an exercise.

To start, we want to create a new surface, by clicking on the surfaces icon ( ) in the Objects toolbar:

A new object has been added into the Objects list (see figure 5). For the creation of the surface we will be working at the ‘Object Properties’ workspace (see figure 5); it is advisable to use the Display Adjustment to enhance the contrast of the channel we are reconstructing, in order to evaluate the precision of the reconstruction. Once this is done, go to the ‘Object Properties’ workspace (shown on the left of figure 6). We want to segment the whole image, but there is the option of only reconstructing a part of the image. This option can also be used to speed up the algorithm, by applying it to a part of the image in order to fine-tune the parameters, and then apply the final reconstruction to the whole image. Click the blue button with the arrow on the bottom right of the dialogue to continue.

Figure 6: The first steps of the surface reconstruction wizard.

In the next dialogue (2nd image in figure 6) we have to select the appropriate channel to be reconstructed (that would be channel 3 in our example). Then, the level of detail can be chosen. This of course depends on the resolution (both axial and lateral) of the dataset, and is automatically set

according to the Nyquist theorem to 2x the pixel size, thus 0.140µm in our case. However, depending on the noise level of the dataset, and other imaging parameters such as oversampling, this can be set to coarser values, resulting in smoother surfaces. Here, we will set it to 0.21µm, as this provides with enough detail and does not result in too noisy of a surface.

The volumes to be reconstructed can be segmented using either an absolute intensity threshold (distinction between foreground and background based on the intensity value) or a more advanced local contrast method. The local contrast method is recommended for use when there are structures with uniform illumination and smooth surfaces, of ovoid, ellipsoid or spherical shapes that are touching each other and have to be segmented and split. The local contrast operates on the volume by fitting a sphere into the object, of diameter set by the user. In our case, due to the morphology of the structures, this would result into over-segmentation. It would be more appropriate for use to reconstruct e.g. the nucleus (green channel). Therefore, we make use of the Absolute Intensity (see figure 6, 2nd image), and proceed to the next step using the blue forward arrow.

In the next dialogue, the surface coverage is calculated based on the aforementioned threshold, which can be manually set using the slider (figure 7). At this point, it is advisable to check the accuracy of the surface coverage (gray surface overlay) by adjusting the contrast of the reconstructing channel, using the ‘Display Adjustment’ (see figure 5 and 7).

Figure 7: surface coverage adjustment using the absolute intensity measure (threshold). This can be adjusted manually by dragging the edge of the yellow slider (red arrow), showing the gray values that will be considered for the reconstruction. The thresholds can also be numerically entered into the fields above (blue arrow). In some cases, it may be necessary to exclude high intensity structures; the threshold can also be adjusted to exclude high values by

dragging the other end of the yellow slider. Using the Display Adjustment (orange arrow), the contrast can be tuned to check the reliability of the surface coverage.

Once the threshold has been adjusted, there is the option of segmenting the volume using a region growing method, which enables touching objects to be split. This is applicable in cases where there are adjacent structures that are segmented as one by the threshold. In this case, using the threshold Imaris calculates certain seed points inside each surface (a dialogue appears in the next step, allowing the user to fine tune this) and applies a region growing algorithm, resulting in distinct split objects. Again, caution must be exercised as using it with the wrong parameters can result in over-segmentation. In our dataset, there is no need for such a function, so the box is left unchecked.

Proceeding to the next step, Imaris will then calculate for the selected settings the surfaces and will render the resulting isosurfaces. This step may take some time, depending on the processing power of the workstation. Once finished, the user has the possibility of selecting which surfaces to keep, based on a variety of filters, according to the relevance of the structure to the data that need to be visualized. Figure 8 illustrates this dialogue.

Figure 8: The final surface reconstruction step. The user can exclude or include the rendered isosurfaces to the final image, using a variety of filters (orange arrow), which can be tuned to the required precision. There is an extensive comprehensive list of filters which can be used depending on the threshold result of the previous step, and on the desired data visualisation; here, we make use of the ‘Number of Voxels’ filter, to exclude the extremely small structures. The number was set 300 (smallest allowed structure would have 300voxels).

After choosing the appropriate volumes to be reconstructed, based on the filters selected, the final surface will be constructed by pressing the green forward button. The rendering of the surfaces can be further manipulated using the ‘Object Properties’ dialogue (see figure 5); statistics about the

volumes can also be obtained here. In figure 9 the final rendered volume is presented, with a different color, refrelctivity and opacity (all modified using the colour type button ); the initial intensity volume renderings have been removed using the button.

Figure 9: Final isosurface rendering of the microglia volume. Image on the left depicts only the isosurface; image on the right includes the rendered volumes of the other channels. Changing the isosurface transparency shows that these structures are included in the surface.

Volume  Statistics  Each isosurface created has distinct spatial properties, which upon reconstruction are readily available in Imaris, and can be exported to Excel. Figure 10 illustrates these for the central microglia cell (selection shown in yellow).

Figure 10: Each isosurface object has certain spatial properties and can include components from all channels (e.g. shown by the blue arrows). These statistics can be easily exported for processing.

Using  XTenstions  

Imaris has the possibility of incorporating MATLAB and ImageJ code to the analysis. There are

already some MATLAB extensions implemented, which can be found under the ( ) button. Using these requires a MATLAB license as well. For every type of reconstruction (surface, filament or spots) there is a variety of readily available XTensions, which can be added to the volume statistics. User-written MATLAB and ImageJ plugins can also be included in Imaris (see Quick Start Tutorial 7.6.1 included in Material folder).

Short  description  of  Mixed  Model  Rendering  Isosurfaces is but one of the many possibilities for modeling a volume in Imaris. Depending on the

structures that need to be visualized, Imaris can produce also fitted spheres ( ), neuronal

filaments including spine reconstruction ( ), or even create a customized intensity volume

rendering ( ). These can all be included in the same image to produce a mixed model of the data stack. For illustrating the mixed model, in our example (figure 11), a sphere had been fitted to the nucleus (channel 2) and the red structures had been intensity rendered, using the ‘Blend’ function in the Volume object pane.

Figure 11: Image on the left illustrates an intensity rendering of the original stack; image on the left shows a mixed model rendering of the dataset, including isosurfaces (blue channel), fitted ellipsoid (green channel) and blend mode intensity render (red channel).

Animation  A short description will be presented here illustrating the potential of Imaris when it comes to creating animated presentations of the dataset. For this, we will use the reconstructed volumes shown in figure 11, changing transparencies, cutting through the volume and adding structures as the animation proceeds. The final movie can be obtained from within the material of the website.

Switch to the Animation tab( ), go to the lower right part of the menu, and click ‘Settings’. On

the ‘Surpass’ pane, all object creation buttons must be enabled (apart from those marked as Custom Object at the bottom), and the Frame Rate must be set to 24 fps, or higher to ensure smooth animation. Figure 12 shows the interface of the ‘Animation’ tab, and includes a description of the basic functions when creating an animation.

Figure 12: The ‘Animation’ tab. The animation effects are based on the addition of Key Frames (red arrow). Each key frame locks the current properties of the objects (set for each object using the Object Properties – orange frame, corresponding to the object pointed by green arrow), as well as the rotation of stack. The stack can be manually rotated using the Navigate cursor, but for increased precision and smoothness of move, rotations of specific angles can be added (blue arrow). The number of Animation frames (purple arrow) can be increased to make animation smoother and slower, according to the number of key frames too. At 24fps, it is advisable to select more than 240 frames for illustrating the volume better. In our example, 1000 frames have been selected.

We will create a full rotation in the Y axis, modifying the transparency of the glia body, and subsequently sectioning it, making the nucleus visible. Additionally, the red channel can be either used as an intensity volume rendering, or can be reconstructed as an isosurface, which will make the animation smoother. The colours will also be changed for better contrast. Start by setting the colour of Surfaces 5 to green, transparency to 0%, colour of Spots 1 to Blue, and click add a key frame.

Rotate the camera by 900, using Custom Rotations (blue arrow, figure 12), around Y axis. This automatically adds a key frame. To look at the key frame, place cursor on the animation slider, and click on the line created. Create another rotation like this; select created key frame, change the transparency of Surfaces 5 to 75% and press ‘Modify’. Create another two 900 rotations. Click the last created frame, and restore transparency to 0% and press ‘Modify’.

Now, to create a slicing plane: Create a new rotation of 60% along the X axis. Select the newly

created key frame. Add a new Clipping pane, using the respective Objects button ( ). Place the new Object above the Surfaces 5, and below Volume; move spots above it too, so that it will clip only the glia surface. Figure 13 depicts the clipping plane.

Figure 13: The Clipping Plane object, within the Animation tab. The position of the object in the list (red arrow) determines which objects are going to be sectioned. The object can be manipulated using the cursor (change from the Navigate to Select - green arrow) in all directions, or precise clippings can be performed using the Object Properties tab (orange frame).

Move the plane using the Select cursor, so that there is no clipping. Click Modify Key frame. Then move the manipulator almost to the end, clipping all glia isosurface. Click Add Key frame. Bring the clipping plane back to the top, without cutting any surface, and add another Key frame. Finally, select the very last key frame, make sure everything is back to original position, and if necessary click Modify.

Set the animation to 480 frames, and click the ‘Play’ button to preview the animation. If no modifications are necessary, press the ‘Rec’ button ( to create a movie with the animation). A variety of options is available for the user to select, depending on the desired quality and file size. In our example, mp4 format was selected, with low compression, of size same as the window size.

Postscript  As with every piece of software designed for advanced applications and offering great versatility, only the tip of the iceberg has been described, from the multitude of features that Imaris includes. We urge the reader to try out different options when following this tutorial; explore the menus and the great variety of Image processing and analysis tools offered by Imaris.

Further  reading  Website: http://www.bitplane.com/

Imaris tutorials: Youtube Channel https://www.youtube.com/playlist?list=PLB6C0D473A06E9AB4

List of XTensions: http://open.bitplane.com/Default.aspx?tabid=237

A selection of documents explaining the basic principles is also included in the Material folder.

Acknowledgement  We would like to acknowledge Dr Jonas Neher of the Hertie Institute for Clinical Brain Research, Tübingen, Germany, for providing the dataset for this tutorial.