X-ray Microscopic Examination of a Chocolate and Peanut Butter Covered Animal Cracker

Figure 1: Maverick 3D rendering of clipped volumetric data of peanut butter and chocolate covered cookie imaged with the SkyScan 1275

In many quality control and quality analysis procedures, non-destructive testing is preferred due to the ability to preserve the sample for additional downstream testing. Micro-CT 3D imaging can play a role in these processes in instances where the throughput of the technique matches or exceeds the sampling rate required for the quality inspection program.

Other imaging techniques generally produce 2D images of the surface or a cross-section of a sample, and labor-intensive methods, such as sectioning or chemical fixation, are often used to prepare these samples. These techniques are usually destructive and the 2D results are often insufficient for drawing conclusions about the 3D structure. Micro-CT analysis is useful in several ways, from studying the internal structure to inspecting finished packaging, non-destructively.

The SkyScan 1275 is Bruker’s answer to high quality imaging of many different sample types at exceptional speeds.

X-Ray Microscopic Imaging of Cookies and Crackers

For this month’s imaging article, we examined an animal cracker, enrobed with both a peanut butter layer and a chocolate layer, using our high-speed SkyScan 1275 desktop micro-CT at an isotropic voxel size of 25µm. The SkyScan 1275 is a great match for this project due to its simple operation and high-speed acquisition modes to keep throughput high.

To maximize resolution within the dataset, the sample was mounted with the longest dimension in the Z plane to minimize our horizontal width allowing for higher magnification. Using two sequential image acquisitions along the length of the cookie, the full sample is acquired at high resolution while the individual scans are digitally combined into one dataset within NRecon for downstream analysis and visualization.

Figure 2: Planar 2D views of the coated animal cracker dataset

As shown in Figure 2, DataViewer provides us a linked, 3D planar view through the dataset. The ability to load datasets into a linked 3D viewing mode provides great control over the final orientation and cropping of the dataset to keep file size down and allows you to save any of the three view planes as your default view for the image stack through the dataset. If you look carefully at the base of the cookie as shown in the bottom two views, you can subtly see the delineation between the chocolate coating and the peanut butter coating. It’s also interesting to note the difference in the location of the salt granules (bright white spots) as we see a distinct salt distribution within the peanut butter coating while nearly no salt granules are visible in the chocolate coating.

While our eyes are skilled at perceiving the boundary between the chocolate and peanut butter coatings, a true segmentation of the coatings as distinct layers would be challenging due to the amount of overlap in signal intensity between the two layers. It is possible however that an advanced segmentation method utilizing machine learning may be able to be trained to automatically separate the chocolate and peanut butter coatings from one another based on minor differences in pixel intensity and the presence of the salt granules within the peanut butter coating but not within the chocolate coating.


Figure 3: Clipped 3D CTVox volumetric rendering of the coated animal cracker showing the porous structure of the cookie along with the salt filled peanut butter coating layer

As shown in Figure 3, CTVox provides us with an interactive volumetric model of the dataset rendered in real time and often helps provide a clearer view of the location of features within the sample in 3D space compared to the planar views possible in DataViewer.

 

Figure 4: Clipped view through the animal cracker dataset, highlighting the location and size of pores within the animal cracker itself while excluding pores in the two coating layers

Using a clipping box within CTVox, we digitally altered the view of the dataset as shown in Figure 4. In this view, we selectively subtracted half the representation of the cookie thickness while not impacting our visualization of the overlaid pore thickness data to create this compound image. Smaller pores are represented in green while larger pores are represented in blue or purple shading.

Figure 5: Animal cracker segmentation masks showing multiple masks overlapping (left) and the dataset after a Boolean subtraction of masks to separate the peanut butter coating from the animal cracker (right)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Within our laboratory, we also often utilize Simpleware ScanIP software (Version U-2022.12-SP1; Synopsys, Inc., Mountain View, USA) to import our Bruker SkyScan micro-CT data and then produce optimized 3D models or specialized analysis. Within CTAnalyzer, we generally work only through one view of the dataset whereas Simpleware ScanIP software allows us to switch between any of the three available view planes through the sample with ease. Simpleware ScanIP software also allows us to create as many individual masks as we would like while CTAn restricts us to working with one to two selections at a time, using a combination of the image view and the clipboard view. For the coated animal cracker sample, we decided to segment the dataset into four individual masks to isolate the salt granules, peanut butter coating, chocolate coating, and animal cracker from one another.

As discussed earlier, a true separation of the chocolate and peanut butter coatings would be challenging from standard thresholding procedures alone. To achieve layer separation for this process, we utilized multiple masks in Simpleware ScanIP software and built each mask through a combination of thresholding, selective manual painting by threshold values, Boolean subtractions, morphological opening and closing functions, and the use of the island removal tool (Figure 5).

Figure 6: Cookie thickness analysis from Simpleware Scan IP software (left) and CTAnalyzer (right)

 

 

 

 

 

 

 

While the methods used to create the masks or isolate components may differ between CTAnalyzer and Simpleware ScanIP software, some functions overlap, such as the ability to use a sphere-fitting model to calculate thickness of features of interest (Figure 6). Using either program, we can create a color-mapped dataset to help us visualize the relative thickness of different regions of the animal cracker. Ultimately, for this dataset there’s good agreement between the two programs with Simpleware Scan IP software reporting an average thickness of 182 micrometers and CTAnalyzer reporting an average thickness of 187 micrometers. Since each program utilized a different method to isolate and define the boundaries of the animal cracker from the coating layers, minor differences in this process would explain the ~3% difference in thickness reported between the two programs.

Figure 7: Maverick 3D rendering from a top view of the bottom edge of the dataset

After isolating the individual components of our coated animal cracker dataset into their respective volumetric meshes, we’re free to move into any downstream 3D software suite to complete further work. In our case, we imported our mesh into Maverick Render Indie to create high resolution photo realistic renderings and videos of our scan data as shown in Figures 1 and 7, highlighting different views of the coated animal cracker product.

Conclusion

Among the SkyScan product line, the SkyScan 1275 stands apart from the field based on its simple user controls and high imaging speeds in the stop and shoot imaging mode. This speed and straightforward operation, along with the ability to equip the instrument with a 16-position sample exchanger, make the SkyScan 1275 a great choice for laboratories where throughput is important as part of a routine quality control or quality assurance program.

We hope you found this Image of the Month informative and encourage you to subscribe to our newsletter and social media channels in preparation for the continuation of our Image of the Month series next month.

Scan Specifications

Sample Coated Animal Cracker
Voltage (kV) 50
Current (µA) 200
Filter None
Voxel Size (µm) 25
Rotation Step 0.4
Exposure Time (ms) 100
Rotation Extent (deg.) 360
Scan Time (HH:MM:SS) 00:34:08

This scan was completed on our SkyScan 1275 micro-CT system at the Micro Photonics Imaging Laboratory in Allentown, PA using an oversize imaging mode. Reconstructions were completed using NRecon 2.0 while visualization and volumetric inspection of the 2D and 3D results were completed using DataViewer and CTVox. The individual components of the coated animal cracker were converted to volumetric models using Synopsys’ Simpleware ScanIP software with the CAD add-on module (Synopsys, Inc., Mountain View, USA) before 3D rendering using Maverick Render Indie (Random Control, Madrid, Spain).

Would you like your work to be featured in our monthly newsletter? If so, please contact us by calling Seth Hogg at 610-366-7103 or e-mailing seth.hogg@microphotonics.com.

References

https://www.synopsys.com/simpleware.html

*Simpleware software (Synopsys, Inc., Mountain View, USA) enables you to comprehensively process 3D image data (MRI, CT, micro-CT, FIB-SEM…) and export models suitable for CAD, CAE and 3D printing. Use Simpleware software’s capabilities to visualize, analyze, and quantify your data, and to export models for design and simulation workflows. Simpleware™ is a trademark of Synopsys, Inc. in the U.S. and/or other countries.

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