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

Modern archaeological studies increasingly utilize three-dimensional virtual representations of objects, high resolution scanning, large datasets, computationally intensive analyses, 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 supercomputers or the design of innovative processing methods. Here we introduce a novel protocol for en-masse micro-CT scanning of small objects with a semi-automated processing workflow with minimal user interaction that functions in memory-limited settings. Using our protocol, we successfully scanned 1112 animal bone fragments using just 10 micro-CT scans, which were post-processed into individual 3D models. Notably, our methods have the potential to be applied to any object (with discernible density from the packaging material) potentially extending this method to a variety of inquiries and fields beyond paleoanthropology and archaeology, including paleontology, geology, biology, art and cultural heritage preservation, and manufacturing. Overall, our new scanning method and processing workflows lay the groundwork for future mass-scale, high resolution scanning studies.

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Publication Details

Journal
Journal of Archaeological Science
Published
2026-10-06
DOI
https://doi.org/10.1016/j.jas.2026.106706
Primary Topic
Image Processing and 3D Reconstruction
Type
article
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article

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

Riley C. W. O'Neill, Katrina Yezzi-Woodley, Jeff Calder, Peter J. Olver
Journal of Archaeological Science
Image Processing and 3D Reconstruction
article

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

Riley C. W. O'Neill, Katrina Yezzi-Woodley, Jeff Calder, Peter J. Olver
article en

Abstract

Modern archaeological studies increasingly utilize three-dimensional virtual representations of objects, high resolution scanning, large datasets, computationally intensive analyses, 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 supercomputers or the design of innovative processing methods. Here we introduce a novel protocol for en-masse micro-CT scanning of small objects with a semi-automated processing workflow with minimal user interaction that functions in memory-limited settings. Using our protocol, we successfully scanned 1112 animal bone fragments using just 10 micro-CT scans, which were post-processed into individual 3D models. Notably, our methods have the potential to be applied to any object (with discernible density from the packaging material) potentially extending this method to a variety of inquiries and fields beyond paleoanthropology and archaeology, including paleontology, geology, biology, art and cultural heritage preservation, and manufacturing. Overall, our new scanning method and processing workflows lay the groundwork for future mass-scale, high resolution scanning studies.

Journal of Archaeological ScienceVol. 195
University of Minnesota (US)
Openalex Percentile: Top 15%
Image Processing and 3D Reconstruction
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En masse scanning and semi-automated surfacing of small objects using micro-CT — Riley C. W. O'Neill, Katrina Yezzi-Woodley, et al. · Journal of Archaeological Science (2026) | TGRS Research Map | TGRS