{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T20:48:17Z","timestamp":1778705297909,"version":"3.51.4"},"posted":{"date-parts":[[2025,8,12]]},"group-title":"Developmental Biology","reference-count":60,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2025,8,12]],"date-time":"2025-08-12T00:00:00Z","timestamp":1754956800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2025,8,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:p>\n                  Image registration-based volumetric morphometrics have emerged as a valuable method for identifying subtle morphological differences in neuroimaging and other biomedical images. However, accurate registration out-of-the-box remains challenging when overt morphological phenotypes\u2014such as those observed in developmental and comparative studies\u2014are present in a dataset. A new label-informed image registration function developed in the ANTsX ecosystem provides an easy to use, generalizable solution for anatomy-aware registration of a wide diversity of morphological variation. In this approach, segmentations (\n                  <jats:italic>i.e.<\/jats:italic>\n                  , labels) provide\n                  <jats:italic>a priori<\/jats:italic>\n                  regional correspondences that guide the registration. These labels can be generated by any method\u2013manually, using semi-automated tools, or through deep learning-based approaches\u2013and allow morphological experts to define regions of correspondence based on biological concepts of homology (\n                  <jats:italic>e.g.,<\/jats:italic>\n                  tissue origin, gene expression patterns). Here we demonstrate the utility of this label-informed image registration approach for improving the registration knockout mouse embryos which fail to register to a wildtype (normative) template image by traditional registration methods. E15.5\n                  <jats:italic>\n                    Gli2\n                    <jats:sup>\u2212\/-<\/jats:sup>\n                  <\/jats:italic>\n                  mouse embryos show a severe scoliosis and radical topological rearrangement of the internal organs. Compared to traditional, intensity-only registration, the new label-informed image registration improved the correspondence of knockout subjects to the canonical template image, which resulted in increased power and sensitivity of downstream statistical analyses. All in all, label-informed image registration provides a flexible and customizable method to allow image registration in datasets for which registration-based morphometrics were previously unfeasible, unlocking new potential applications of registration-based morphometrics in developmental, comparative, and evolutionary studies.\n                <\/jats:p>","DOI":"10.1101\/2025.08.11.669599","type":"posted-content","created":{"date-parts":[[2025,8,13]],"date-time":"2025-08-13T06:20:14Z","timestamp":1755066014000},"source":"Crossref","is-referenced-by-count":1,"title":["Anatomy-aware, label-informed approach improves image registration for challenging datasets"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1958-4849","authenticated-orcid":false,"given":"Rachel A.","family":"Roston","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9418-5103","authenticated-orcid":false,"given":"Nicholas J.","family":"Tustison","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7921-9018","authenticated-orcid":false,"given":"A. Murat","family":"Maga","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"54368","reference":[{"key":"2025081410550769000_2025.08.11.669599v1.1","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1016\/S0169-5347(97)01125-7","article-title":"Developmental genetics and homology: a hierarchical approach","volume":"12","year":"1997","journal-title":"Trends in ecology & evolution"},{"key":"2025081410550769000_2025.08.11.669599v1.2","doi-asserted-by":"crossref","unstructured":"Akinci D\u2019Antonoli T , Berger LK , Indrakanti AK , Vishwanathan N , Weiss J , Jung M , Berkarda Z , Rau A , Reisert M , K\u00fcstner T , et al. 2025. TotalSegmentator MRI: Robust Sequence-independent Segmentation of Multiple Anatomic Structures in MRI. 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