It is quite important to support loading SWC files in VessMorphoVis to be able to support some databases like BraVa.

Install the dependencies required to run VMV using the internal python version that can be obtained from Blender.

Hi Marwan,

Thanks again for adding the 3D directional color-coding feature...

I noticed some choppiness (discontinuities) in the colormap. Did you perhaps encode the angle to each axis or the sines of those angles in the colormap? I believe the sines of those angles (the 3-space components of the direction unit vector) to be the better quantity to encode because it will utilize the color-space more evenly.

Proof: a random variable uniformly distributed on the surface of the unit sphere will be uniformly distributed in three components (sine of angle from axis) independently, but will have an uneven distribution when binned by the angles.

For example, looking at this authentic in vivo anatomy:

Here is the histogram of segment directions binned by Z-component (quite uniform):

And here is the histogram of (area-weighted) section directions binned by angle from Z axis (the histogram is heavily concentrated on 0 (because a random direction is more likely to be aligned to a plane than a line).

Thanks,
Sam

In certain cases, the dataset has samples with very small radii or even with zero-radii. These samples must be fixed before resampling the data to avoid any artifacts in the final reconstruction.

Using the metaball mesh generation algorithm, the tessellation option does not work due to API break in the Blender interface. Please fix this.

It is necessary to add LTS for VMV to ensure some stability for the quick updates of Blender. We need to use Blender 3.3.2 and test all the functionalities and shaders with this version.

Hi,

Thanks for the great work and public-available software. I am particularly interested in the mesh generation. I can see most of the method details are in supplementary materials. However, it seems not able to retrieve the supplementary from the bioinformatics website. https://academic.oup.com/bioinformatics/article/36/Supplement_1/i534/5870503?login=false.

May I ask if there is anywhere else I can find the supplementary materials? Otherwise, would you mind providing a pdf file?

Thanks a lot in advance!

Please include area-weighted quantities (instead of giving each point a weight of one, since this is not robust to arbitrary sampling) in network-wide analyses since, these quantities are more biologically relevant. See figure 4C from the SLAVV methods paper preprint for example area-weighted histograms.

It was required by the cells and circuits team to visualize a time series of the morphology to reveal the differences in several properties like pressure, velocity or diameters, etc ...

• If the connectivity data is not available, simply don't add the mode to the list.
• Add a feature to allow the users to use number of pre- and -post samples to be added from the parent and children respectively.

To complete the analysis, we should integrate a way to visualize the datasets (either morphologies or meshes) with an isometric camera (orthographic camera with a 45 degree alignment) from the 3 views. The bounding box should rendered slightly to give an insight on the depth cues.

Add a flag after loading the dataset to indicate if it has the connectivity information or not. Disable the connected sections builder if this flag is set to false.

Following the VIZTM-1264 ticket, we must add the authors after the Author: statement to match the BBP format.

Please add a color map option that maps vessel direction at each point (by comparing change in position between each point and one or both neighbors) to colors: [ |dx|, |dy|, |dz| ] -> [ R, G, B ] where |dx|, |dy|, |dz| are the absolute-valued difference in position with respect to trace-location along vessel section.

Add a new direction for rendering the datasets from a 3d camera.

Since we have only a single component unlike the neurons, we would like to make a simple button that can be used to update the shading style without re-reconstructing the data.

Currently, every time a new color is requested a new morphology or mesh is re-generated. We need to make the UI updates the structures on the fly without regenerating any objects.

When we visualize simulations, the colors are updated based on the defined color map. When we switch back to visualize the static structure, the colors are still linked to the first element of the color map, which in return results in a wrong color.
This needs to be fixed.

Thank you for considering my feature request for the VessMorphoVis plugin: I would like to encode the directions of the vessels as a color (x-alignment->R,y->G,z->B). I may want to encode other attributes in color, so I would love more control over the coloring of the vessel objects. Ideally, I would love it if the last three fields of the point coordinates comprising the vessel centerline locations in the .vmv file could be interpreted as RGB values for that specific location along the vessel.

Thank you,
Pleased user of VessMorphoVis

Add a flag to allow the user to unify the radii at the branching points for better and smoother visualization.

The UV mapping with the meshes created from the Polyline mesher is not working correctly. The renderings are wrong.

If we change the value of the tube quality from the UI, the morphology is not updated.

As requested by @pbl007, we need to add support to read files in Pajeck format.

Adding a text box to allow the users to change the name of the dataset after loading it.

To focus on the morphology, draw all the bevel objects where the skeleton is going to be drawn.

In the current scene the lights are created at the origin. To make proper illumination, wee must ad the lights where the morphology is located.

Allow the users to draw (and hide) the bounding box of a given network.

Traceback (most recent call last):
File "/Applications/Blender.app/Contents/Resources/2.80/scripts/addons/VessMorphoVis/vmv/interface/ui/io_panel.py", line 281, in execute
vmv.scene.clear_scene()
File "/Applications/Blender.app/Contents/Resources/2.80/scripts/addons/VessMorphoVis/vmv/scene/ops/scene_ops.py", line 59, in clear_scene
vmv.utilities.disable_std_output()
File "/Applications/Blender.app/Contents/Resources/2.80/scripts/addons/VessMorphoVis/vmv/utilities/std_output.py", line 39, in disable_std_output
sys.stdout = open('stdout.output', 'w')
PermissionError: [Errno 13] Permission denied: 'stdout.output'

location: :-1

Artifacts include: overlapping segments, zero-length segments, zero-length-sections, zero-radius samples, zero-radius sections.
A simple report should be generated to reveal the analysis operations applied and the differences between the input morphology and the output one.

To make it easy to install the package for Windows users, add all the dependencies to a text file.

To integrate it in the analysis, render the three views of the morphology and make a collage within the same image.

For calculating the correct statistics, keep the samples list and avoid removing it.

To improve the loading and export performance of the datasets, we should implement a similar a binary like format similar to the ascii one in VMV. We can call it .vmvh5 and simply store the vertices and strands in two different datasets.

We recently received a dataset for the full mouse brain that has more than 5 million samples. Using polylines to visualize such a huge dataset is not applicable without commodity GPUs.
To resolve this issue and visualze the dataset, we can sample the loaded section list and visualize a subset of the morphology.

Note that the analysis will be applied on the entire dataset, while the resampled one is only used for the visual representation.

We should also add a note in the UI that we only visualze a subset of the morphology.

The loaded VMV files are not centered at the origin. This must be fixed.

The current samples builder is indeed limited for large scale visualization. It is better to implement or integrate a point cloud visualizer with OpenGL code and some transparency. This will allow us to visualize extremely large scale datasets.

Trying to export a mesh model with the internal API, it did not work.

Similar to the image below, we would like to add a new feature to allow the users to control the radii of the morphology that will be visualized.

Note that the analysis will still be applied on the entire dataset to avoid any confusion.

Hi Marwan,

Thanks again for completing my other feature request for color-coding 3D direction as XYZ alignment -> RGB color sphere...

Will you please add a similar feature:

I would like again for the colors to represent alignment, but I would like a 2 Dimensional colormap, where one end of the spectrum represents alignment to the viewing angle of the camera, while the other end represents alignment to the plane perpendicular to that axis.

This feature would be nice because it will reduce the number of colors needed to deliver the information, and will still encode the most important directional information (direction in the image plane can be seen without the aid of color-coding).

If it is too hard to change color dynamically to the viewing angle, then we could allow the user to input the (3D spherical) angles, or choose an axis (e.g. Z axis)?

Thank you,
Sam

We are upgrading VMV to read and visualize simulation data using our internal formats, we therefore need to update VMV file structure to account for simulation data.

Use the editing capabilities in Blender to connect the disconnected edges,

Please allow for the color bin limits (for color-coding radius, length, area, etc.) to be logarithmically distributed. (Currently linearly distributed. I believe logarithmic should be the default, but having the option would be helpful too. Thank you.

Add a further analysis components to the analysis panel: network tortuosity.

Add multiple options to resample the skeleton similar to NeuroMorphoVis.

In certain cases during the analysis of the given networks, users want to visualize the compoenents of the networks that have radii below or above a given average. This feature should be implemented in all morphology builders.

To minimize the dependencies, we would like to integrate a function to interpolate colors for a certain range given three colors only.

The current setup script cannot be used to run VMV on Mac computers with M chips.

Further analysis is required to analysis to the total length of the different components in the morphologies along the XYZ coordinates to complement the color-code visual analysis.

Please add a feature to the .vmv file parsing where the user can directly provide the R G B color triplet for each point in the file. Thank you :)

We must add a gallery for some of the images that are created with VessMorphoVis.