bioRxiv preprint doi: https://doi.org/10.1101/859983; this version posted August 12, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 1 A machine learning based approach to the segmentation of micro CT data in 2 archaeological and evolutionary sciences 3 4 Authors: 5 Thomas O’Mahoney (1,2)* 6 Lidija Mcknight (3) 7 Tristan Lowe (3,4) 8 Maria Mednikova (5) 9 Jacob Dunn (1,6,7) 10 1. School of Life Sciences, Faculty of Science and Engineering, Anglia Ruskin 11 University, Cambridge, UK 12 2. McDonald institute for Archaeological Research, University of Cambridge, 13 Cambridge, UK 14 3. School of Earth and Environmental Sciences, University of Manchester, 15 Manchester, United Kingdom 16 4. Henry Mosely X-Ray Imaging Facility, University of Manchester, 17 Manchester, UK 18 5. Institute of Archaeology, Russian Academy of Sciences, Moscow, Russian 19 Federation 20 6. Division of Biological Anthropology, Department of Archaeology, 21 University of Cambridge, UK 22 7. Department of Cognitive Biology, Universität Vienna, Vienna, Austria 23 *correspondence to Thomas O’Mahoney:
[email protected] 24 KEY WORDS: MICROCT; IMAGE SEGMENTATION; BIOINFORMATICS; 25 MACHINE LEARNING; ANTHROPOLOGY; PALEONTOLOGY bioRxiv preprint doi: https://doi.org/10.1101/859983; this version posted August 12, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.