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sample1.tiff.tiff (4.3 MB)
sample2.tiff (4.3 MB)
I am analyzing microstructures in biogenic biocomposites (bivalve shells). These are SEM images of a polished surface, where the organic component was removed. I want to assess differences in the microstructure base don these images. By visual inspection I can see that, e.g., the mineral size, elongation, and orientation vary.
Until now, I have failed to quantitatively determine meaningful differences between samples. Measuring the morphology of individual minerals seems nearly impossible, as they are not well separated from one another. It would be highly subjective to define which portions of the image together form one mineral entity.
What properties of the images could reveal quantifiable differences between samples?
I have tried threshold-based and machine-learning based segmentation of the images to measure size, shape etc. of individual minerals. However, it is hard to define a “ground truth” to compare the segmentations with. I have no method on determining if my segmentation results are actually “correct”.
I have tried measuring black and white ratios in thresholded versions of the images, which gives results I would agree with. But using this Method I can only determine the amount of mineral phase compared to the amount of (previously removed) organic phase. I can’t say anything about shape or structure.
I hope my question is not too vague, but I am looking for additional ideas on how to describe what I am seeing in numbers. Would fractal analysis be of use here? Unfortunately I cannot improve the preparation technique much more.