MIA-Clustering: a novel method for segmentation of paleontological material

Christopher J. Dunmore​, Gert Wollny, Matthew M. Skinner

Paleontological research increasingly uses high-resolution micro-computed tomography (μCT) to study the inner architecture of modern and fossil bone material to answer important questions regarding vertebrate evolution. This non-destructive method allows for the measurement of otherwise inaccessible morphology. Digital measurement is predicated on the accurate segmentation of modern or fossilized bone from other structures imaged in μCT scans, as errors in segmentation can result in inaccurate calculations of structural parameters. Several approaches to image segmentation have been proposed with varying degrees of automation, ranging from completely manual segmentation, to the selection of input parameters required for computational algorithms. Many of these segmentation algorithms provide speed and reproducibility at the cost of flexibility that manual segmentation provides. In particular, the segmentation of modern and fossil bone in the presence of materials such as desiccated soft tissue, soil matrix or precipitated crystalline material can be difficult. Here we present a free open-source segmentation algorithm application capable of segmenting modern and fossil bone, which also reduces subjective user decisions to a minimum.