Messages

Hello,

I had a question regarding pore shape visualization. The identify pores scatter plot identifies 4 pore types, and the help guide shows representative visuals for the 4 types. We were curious if the pore types could be visualized in the dataset itself? Based on what I've seen, none of the pore visualizations represented this. Thank you.

Respectfully,
Jack Davis

Hello,

I had a question regarding the algorithm used to determine the scatter plot for the Krumbein sphericity and the volume distribution.

With the scatter plot, I was curious if there were certain cutoffs used in the algorithm; it seems like maybe not all of our pores were analyzed. If there is a help section in the user guide that explains this could I receive guidance to it?

With regards to the volume distribution, analysis was made on our entire sample was well as 3 single pores. When the entire sample was analyzed, the histogram on the volume distribution matched the PoroDict analysis. However, when we analyzed only 3 (the largest pore and 2 other small ones), it did not match up at all. I was curious if there was a statistical explanation for why the analysis on the entire sample proved accurate but the analysis of just 3 pores was off. Thank you.

Respectfully,
Jack Davis

We have an additional question regarding the fiber find.

We can visually see a full fiber in the segmented dataset (see image below; pink fiber dead center).

The output from the fiber find demonstrates fiber lengths up to approximately 30 mm. We would like to obtain the length of the aforementioned fiber to compare to a typical fiber length; since the data output shows a distribution of fiber length, I was unable to find a way to obtain individual fiber lengths.

If there is a way to do this it would be greatly appreciated.

Good afternoon,

We were curious if GeoDict has a known module that uses the rendered 3D volume to calculate the surface roughness. Thank you.

Respectfully,
Jack Davis

Hello,

We have a segmented dataset with a tube that is straight up and down and a curved tube.

When we crop to only focus on the center tube, we get a tortuosity of approximately 1.004, which is consistent with the definition of tortuosity.

However, when we run the same diffusion simulation on the curved segment, we repeatedly get 1.001. We have tried to crop out part of the top section, clean up the sample, and erode the dataset to get a focused centerline for the path to follow. None of these changed the value from 1.001.

Are there any other methods to get an accurate result for tortuosity? Thank you.

Respectfully,
Jack Davis

Addendum:

We applied the filter, tried the threshold analysis, as well as dilation of fibers. It seemed to do slightly better but still broke up the fibers quite a bit.

Are there any other suggestions to enhance the results? We have exhausted what we currently know with no significant improvement, and our deadline is rather quickly approaching. Thank you.

Respectfully,
Jack Davis

Hello,

After applying the filter, it seemed to make the identification worse, as the number of identified fibers increased.

I tried messing around with the threshold to see if that would get accurate results, but unfortunately it did not work.

Is there anything else that could help in identifying the correct number of fibers and their lengths?

Respectfully,
Jack Davis

Hello,

Thank you for the helpful updates.

I was able to create histograms. However, for both Material ID 1and 2, the histogram outputs were the same (see below image).



The graph output a count of voxels equivalent to the total amount of voxels present in the structure, with an attributed grayvalue of 0.

The code I ran can be seen below.

.

I switched the values between 1 and 2 on line 16 (if Structure [j][k] ==2:).

Is there something I'm missing in regards to specifying the material ID or referencing the grayvalues? Thank you.

Hi Lilli,

Thank you for your response.

We have tried different thresholding values, still with no luck.

We also dilated our structure to ensure that the diameter was at minimum 8 voxels to eliminate any instability there.

Our fibers have relatively high surface roughness, which might be playing a role in the fibers being broken up into multiple identified fibers.

I would be glad to send our structure file to you if that would help any.

Respectfully,
Jack Davis

We are trying to obtain fiber length and count through the FiberFind (AI) module.

The fibers are multidirectional and have fairly high surface roughness.

The module is currently identifying what should be single fibers as multiple fibers, and some fibers are not getting identified at all. The threshold is currently set to 0.9

If we increase the threshold, the issue of multiple fibers attributed to 1 decreases, but so does the identification of fibers. The below image captures what we are currently dealing with.

[attachimg=1]

I am trying to obtain the grayvalues attributed to a specific material ID so I can then create a histogram to visualize the distribution of grayvalues.

I tried running the code found here (https://geodict-userguide.math2market.de/2025/automation_api-results.html?anchor=getvolumefield) in a GeoApp.

[attachimg=2]

However, I received this error.
[attachimg=1]

The logic behind running this code was to get all the statistics attributed to a specific Material ID, and then index out the grayvalues.

Hello,

I had a question regarding the FiberFind mentioned in this thread.

Do the fibers still have to be aligned in the x-y plane for identification with the 2025 software? Thank you.

Respectfully,
Jack Davis

Hello,

I was able to obtain results for the grayvalues on our dataset.

I had a question regarding the plot. On the x-axis, the gray value is given, which is what we want. On the y-axis, however, the probability is given.

We were hoping to be able to show the count of voxels on the y-axis instead of the probability. Is this possible? Thank you.

Respectfully,
Jack Davis

Thank you for the information, and I was able to import and obtain a populated Volume field.

My dataset is a 3-phase material. With that, the analysis assigned only 3 grayscale values: 0 for one material ID, 1 for the second, and 2 for the third.

I was hoping to get the range of grayscale values attributed to the materials, rather than a strict assignment of gray value (such as 0 for material 1, 1 for material 2, and 2 for material 3). Is this possible?

Thank you.

[Gray Values]

Hello Jonas,

In terms of my workflow, I have uploaded our dataset into GeoDict and segmented using AI segmentation, boosted Tree model.

After segmentation, I created a Gray Values volume field. I then selected Compute Metrics on the Gray values volume field.

I also chose to compute the minimum, maximum, mean value, Standard Dev, and variance. I computed the values for one material ID for a test run. The results were as follows [attachimg=1]