There is a good reason why this article is posted after more than one month. This is because I wanted to get a feeling for how long the scan takes in reality and re-live it… (Or, I may have lied and I was busy with something; we’ll likely never find out.)
Now that the scan is over, the images had to be reconstructed to get a 3D map of the scanned specimen. It uses an algorithm that I can’t seem to name, because I didn’t write it down anywhere. Fortunately, I know exactly what it does. It creates slices of images which show the density within the specimen at specific heights (i.e., find out how much empty space there is and how much filled space there is in each sliced layer the object).
The software NRecon was used to reconstruct the captured images into full-fledged 3D images of high quality. A correction must be made for each image to compensate for any deviations caused by the temperature during scanning, while the images were being captured. There are several options available for this procedure. Fortunately, since the scanner itself was new, the corrections were pretty minor.
Next is to compensate for beam hardening, if any. This is done to keep the densities flat. After this, would be ring artifact corrections, which is done to rectify the formation of rings in the reconstructed images due to miscalibration of the sensor—we’re all humans, so these things can happen during initial setup. Rings are bad. The images with them can be rectified, however. Below is an example of a ring artifact, which, again, is undesirable. This is especially true if your image begins to look like a vinyl record…
There is a tool for reducing noise in the image and smoothening them. The images can then finally be saved in various formats. Saved images can then be visualized and analyzed using other software. I have my images in BMP and TIFF formats.
Fortunately, batch processing of reconstruction is an option and large quantities of obtained images can be corrected and reconstructed with the click of a button, once the settings are ready. Imagine sitting and having to reconstruct each individual image, then save them, and then analyze them… it would take months, especially if the resolution is 4K!
The reconstruction process was done for 4 types of infill levels for colored cones, and both transparent and colored cylinders (a grand total of 12 types of data sets with 3 sub types within them, each) in my project. That genuinely took a lot of time.
With this, we end another part on this extremely interesting process of reconstruction. It looks short when you read it, but it is ridiculously convoluted, especially if you’re doing it for the first time. Next time we will talk about visualizing the images in 2D and 3D, and maybe a bit on how to analyze them.