Micro-CT/XRM Academy Newsletter

Advanced Image Processing Workflow for 3D Analysis and Visualization of Complex Multi-Phase Food Structure

The texture aspect of processed foods is a major criterion of sensory attributes that is critical for consumer acceptability and preference. Understanding texture perception requires knowledge of the food structure at the multiscale levels which comprises microstructural elements of varying size and functionality including oil and water droplets, fibers, fat, ice crystals, and gas bubbles.

3D X-ray microscopy (XRM) offers the possibility to visualize and characterize such microscopic features in various food materials. However, some food materials remain challenging to characterize through image processing because of their small or similar attenuation coefficient making them difficult or impossible to be segmented by regular image processing methodology (Fig. 1).

       Raw image - in XY view              Image enhanced with contrast
                                                                    enhancement filtering*

                        (a)                                                         (b)

* New CTAn plugin released in 2017 (MN 113)

Method note 135 presents an automatic image processing workflow through CTAn (version 1.19.11.1) for segmentation and 3D analysis of the various phases in potato crisp. The methodology includes the step by step process to (i) delineate the volume of interest (VOI) for 3D analysis, (ii) segment the crisp medium from air and oil inside the VOI, (iii) improve contrast between air pores and oil droplets, (iv) isolate oil droplets from air pores and (v) analyze in 3D the segmented crisp, air and oil inside the VOI to determine for each phase the volume proportion and thickness distribution.

The results of this phase retrieval applied to the sorghum root scan is also shown in figure 1 (c). The notable feature of phase retrieval imaging is the elimination of the artificial edge brightening and its conversion into enhanced contrast. Thus for example the higher density of a layer of peripheral cells in the root is shown by phase retrieval, but is not visible in the reconstruction of standard absorption based projections.

New Software Updates at BrukerSupport

We have pre-registered our users at BrukerSupport.com for the distribution of documentation and software. Please log into your account and select your SKYSCAN system(s). If you did not receive an email for log-in, please apply for an account with your system serial number.
At BrukerSupport.com you'll find the latest software versions available for download. In addition, the complete library of method notes has been uploaded as well.

Most recent and planned software updates include:

• SKYSCAN 2214 control software V1.6
• SKYSCAN 1275 control software V1.7
• SKYSCAN 1276 control software V1.5
• NRECON V2.0 & FAQ new license protection
• CTAn V1.20.8: 32-bit / 64-bit
• DicomCT V2.6

Bruker is committed to provide complete XRM/Micro-CT solutions, and therefore continues to develop software in-house to complement the Bruker instruments. In order to better protect this substantial investment, a state-of-art license protection is being implemented for Bruker’s proprietary 3D.SUITE software.

NRECON V2.0 will be the first software with this new license protection. Please carefully read the FAQ at Brukersupport in case you would like to upgrade to the latest version.

Enjoy your support membership and let us know if you have any questions!

Image of the Month

In view of the ongoing COVID-19 pandemic, there is an increased interest in research relating to control and prevention through improvement of personal protective equipment against dangerous airborne particulates. For filtering facemasks, the fiber orientation profile of the inner melt-blown layer is an important 3D microstructural feature as it affects various properties including air permeability, water diffusion and bending rigidity.
 
A small piece of an FFP2 facemask was scanned with SKYSCAN 2214 at a pixel size of 1 µm. The images above show the color-coded local orientation distribution of the fiber network inside the inner and outer filter layers, evaluated with 3D.SUITE. On the right, a XY cross-section of the mask illustrates that the inner melt-blown layer (dense fiber network) appears to have a stratified orientation indicated by the altering greenish and reddish color along Y-axis direction.

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