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Although computational techniques for registration have become more accessible, challenges remain that hinder their widespread use in morphometrics. We present a two\u2010step process implemented in Python and MATLAB. The first step is Automated 3D Geometric Morphometrics (\n                    <jats:italic>auto3dgm<\/jats:italic>\n                    ), a framework for automatically aligning morphologically diverse objects representing the same anatomical structure. We introduce an updated version with a user\u2010friendly installation, improved interface, and enhanced computational efficiency.\n                    <jats:italic>Auto3dgm<\/jats:italic>\n                    outputs \u201cpseudolandmark\u201d files, which can be analyzed using traditional 3D geometric morphometrics, but they present challenges due to naive registration. The second step is Surface Analysis, Mapping, and Segmentation (\n                    <jats:italic>SAMS<\/jats:italic>\n                    ), which models shape variation and provides a more informed registration across samples. This continuous registration enables more effective 3D geometric analysis and overcomes the limitations of\n                    <jats:italic>auto3dgm<\/jats:italic>\n                    's pseudolandmarks. We tested the updated\n                    <jats:italic>auto3dgm<\/jats:italic>\n                    on various systems for installation, efficiency, and interface, finding it to be faster and more optimized than previous versions. The new implementation achieved high\u2010quality alignments with fewer pseudolandmarks, improving alignment efficiency.\n                    <jats:italic>SAMS<\/jats:italic>\n                    \u2010based registrations produced biologically homologous feature points and resolved issues with\n                    <jats:italic>auto3dgm<\/jats:italic>\n                    's pseudolandmarks, offering meaningful analysis with fewer pseudolandmarks. In conclusion, this pipeline significantly enhances the practicality of fully automated 3D registration, providing more accurate registrations and enabling advanced machine learning approaches for morphology analysis.\n                  <\/jats:p>","DOI":"10.1002\/ar.70164","type":"journal-article","created":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T11:46:52Z","timestamp":1772970412000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Registration\u2010based workflow for shape study"],"prefix":"10.1002","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0537-9617","authenticated-orcid":false,"given":"Alisha","family":"Anaya","sequence":"first","affiliation":[{"name":"Department of Anthropology, National Museum of Natural History Smithsonian Institution  Washington DC USA"},{"name":"Division of Mammals, National Museum of Natural History Smithsonian Institution  Washington DC USA"},{"name":"Department of Evolutionary Anthropology Duke University  Durham North Carolina USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6260-2010","authenticated-orcid":false,"given":"Robert","family":"Ravier","sequence":"additional","affiliation":[{"name":"Department of Mathematics Duke University  Durham, North Carolina USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0320-9726","authenticated-orcid":false,"given":"Shira","family":"Faigenbaum\u2010Golovin","sequence":"additional","affiliation":[{"name":"Department of Mathematics Bar\u2010Ilan University  Ramat Gan Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6578-764X","authenticated-orcid":false,"given":"Julie","family":"Winchester","sequence":"additional","affiliation":[{"name":"Department of Evolutionary Anthropology Duke University  Durham North Carolina USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6472-1056","authenticated-orcid":false,"given":"Ingrid","family":"Daubechies","sequence":"additional","affiliation":[{"name":"Department of Mathematics Duke University  Durham, North Carolina USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8697-2999","authenticated-orcid":false,"given":"Doug M.","family":"Boyer","sequence":"additional","affiliation":[{"name":"Department of Evolutionary Anthropology Duke University  Durham North Carolina USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2026,3,6]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0889-5406(05)81520-3"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1112822108"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/ar.23084"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11692-020-09508-8"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-022-14395-4"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1137\/18M1203481"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1023\/B:JMIV.0000011323.32914.f3"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1002\/ajpa.22934"},{"key":"e_1_2_9_10_1","article-title":"Towards a morphological metric of assemblage dynamics in the fossil record: A test case using plnktonic foraminifera","volume":"371","author":"Hsiang A. Y.","year":"2016","journal-title":"Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-97-1923-5_35"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1111\/joa.12195"},{"key":"e_1_2_9_13_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1469-7580.2006.00576.x"},{"key":"e_1_2_9_14_1","unstructured":"Ravier R.(2018).Eyes on the prize: Improved biological surface registration via forward propagation. arXiv preprint: arXiv:1812.10592."},{"key":"e_1_2_9_15_1","unstructured":"Ravier R.(2024).SAMS. Github repository.https:\/\/github.com\/RRavier\/SAMS"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1558-5646.2008.00557.x"},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.1093\/imaiai\/iau011"},{"key":"e_1_2_9_18_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmor.1051730307"},{"key":"e_1_2_9_19_1","doi-asserted-by":"publisher","DOI":"10.1002\/ece3.3058"},{"key":"e_1_2_9_20_1","doi-asserted-by":"publisher","DOI":"10.1002\/ece3.9373"},{"key":"e_1_2_9_21_1","doi-asserted-by":"publisher","DOI":"10.1017\/S1089332600001868"},{"key":"e_1_2_9_22_1","unstructured":"Winchester J. M.(2020).hecate.https:\/\/github.com\/JuliaWinchester\/hecate"},{"key":"e_1_2_9_23_1","volume-title":"Geometric morphometrics for biologists: A primer","author":"Zelditch M. 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