En masse scanning and automated surfacing of small objects using Micro-CT

TL;DR

This work introduces a novel protocol for en-masse micro-CT scanning of small objects with a mostly-automated processing workflow that functions in memory-limited settings and set the standard for future mass-scale, high resolution scanning studies.

Abstract

Modern archaeological methods increasingly utilize 3D virtual representations of objects, computationally intensive analyses, high resolution scanning, large datasets, and machine learning. With higher resolution scans, challenges surrounding computational power, memory, and file storage quickly arise. Processing and analyzing high resolution scans often requires memory-intensive workflows, which are infeasible for most computers and increasingly necessitate the use of super-computers or innovative methods for processing on standard computers. Here we introduce a novel protocol for en-masse micro-CT scanning of small objects with a {\em mostly-automated} processing workflow that functions in memory-limited settings. We scanned 1,112 animal bone fragments using just 10 micro-CT scans, which were post-processed into individual PLY files. Notably, our methods can be applied to any object (with discernible density from the packaging material) making this method applicable to a variety of inquiries and fields including paleontology, geology, electrical engineering, and materials science. Further, our methods may immediately be adopted by scanning institutes to pool customer orders together and offer more affordable scanning. The work presented herein is part of a larger program facilitated by the international and multi-disciplinary research consortium known as Anthropological and Mathematical Analysis of Archaeological and Zooarchaeological Evidence (AMAAZE). AMAAZE unites experts in anthropology, mathematics, and computer science to develop new methods for mass-scale virtual archaeological research. Overall, our new scanning method and processing workflows lay the groundwork and set the standard for future mass-scale, high resolution scanning studies.

Figures (12)

• Figure 1: Overview of our processing workflow.
• Figure 2: A is the plastic divider. B is a side view of the scan as it would be placed on the scan bed. Note that the topmost tier is shorter than the other two tiers, demonstrating one way the sizing can be altered to accommodate different sized objects. The extra space at the top of the package was to ensure everything would be captured during scanning. C is a bird's-eye-view of a portion of tier. You can see how each fragment is rolled in its plastic bag and inserted into one of the cells. The cell lengths and widths may be varied by adjusting the divider placement and skipping slots. D shows labeling on the side and top of the box so that it was clear how the box needed to be set on the scan bed and how it related to the CSV.
• Figure 3: Left: example "scan layout" CSV file for a 4-tier micro-CT scan. Note red lines were added to emphasize different tiers. Each row contains a scan identifier, tier number, row number, and the identifiers corresponding to the objects in that strip of the scan (where present). Right: slices from the corresponding tiers in the scan.
• Figure 4: left: a $z$-slice TIFF image of the scan. Right: visualization of the entire scan.
• Figure 5: Left: original TIFF image. Middle: cropped and rotated image. Right: CSV layout.