<i>MiTiSegmenter</i>: Software for high throughput segmentation and meshing of microCT data in microtiter plate arrays.

Abstract

Lab-based microCT is a powerful means of visualising the internal structure of physical specimens deployed across the physical sciences, engineering and the arts. As its popularity has grown, demand for bulk digitisation of multiple samples within a single scan has increased. High throughput workflows can increase sample sizes and reduce scan time, yet downstream segmentation and meshing remain a bottleneck. We present <i>MiTiSegmenter</i> as a new tool for the bulk archiving of valuable zooarchaeological and palaeontological remains. We foresee <i>MiTiSegmenter</i> as particularly useful when incorporated into workflows that ultimately require the destructive testing of specimens, including sampling for ancient DNA and proteomics. The software may also play an important role in national museums' ongoing mass digitisation efforts, facilitating the high-speed archiving of specimen 3D morphology across extensive collections with very minimal user intervention or prior training. •We present <i>MiTiSegmenter</i>, a software package for semi-automated image processing and segmentation of array-based batch microCT data.•Implemented in Python, <i>MiTiSegmenter</i> expedites cropping, meshing and exporting samples within stacked microtiter plates, facilitating the rapid digitisation of hundreds-thousands of samples per scan.•We illustrate <i>MiTiSegmenter's</i> capabilities when applied to bulk archiving of valuable zooarchaeological and palaeontological remains.