Testing the accuracy of microstructure reconstruction in three dimensions using phantoms

Abstract

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Topology-faithful nonparametric estimation and tracking of bulk interface networks

“…A schematic and results for the inclination range of 0 • to 90 • is shown in Figure 5. It is seen that while the mean deviation varies with the inclination of the original line, it falls within a few degrees of the actual normal which justifies the use of SM OOT H in calculations of grain boundary character distribution [34,5,6].…”

Three-dimensional digital approximations of grain boundary networks in polycrystals

“…The change in volume of each grain i, V i , between the volume from the originally segmented mesh, V i,mcubes (labeled as 'mcubes') and that from the smoothed mesh, V i,smoothed (labeled as 'smoothed'), is defined as figure 8, the errors of V i created through the smoothing process are plotted against V i,mcubes for all of the grains in (a) Microstructure I, and (b) Microstructure II, respectively. Note that most of the grains experience less than 0.2% volume changes during the smoothing procedure and that smaller grains experience larger volume changes due to the relatively poor resolution of both the original images and segmented triangles when compared to the larger ones, as one might reasonably expect [42].…”

Determination of the Feature Resolution of Processed Image Data via Statistical Analysis

“…Various phantom data have also been used to estimate the feature resolution of different grain characteristics representative of material microstructure (e.g., grain volume, surface area, etc.) (Sintay & Rollett, 2012; Loughnane et al, 2014). However, a disadvantage with the utilization of “phantom data” is the difficulty in representing real microstructural features such as complex crack networks and shape features with simulated structures.…”