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• W2955929233 abstract "Synopsis Advances in imaging technologies, such as computed tomography (CT) and surface scanning, have facilitated the rapid generation of large datasets of high-resolution three-dimensional (3D) specimen reconstructions in recent years. The wealth of phenotypic information available from these datasets has the potential to inform our understanding of morphological variation and evolution. However, the ever-increasing ease of compiling 3D datasets has created an urgent need for sophisticated methods of capturing high-density shape data that reflect the biological complexity in form. Landmarks often do not take full advantage of the rich shape information available from high-resolution 3D specimen reconstructions, as they are typically restricted to sutures or processes that can be reliably identified across specimens and exclude most of the surface morphology. The development of sliding and surface semilandmark techniques has greatly enhanced the quantification of shape, but their application to diverse datasets can be challenging, especially when dealing with the variable absence of some regions within a structure. Using comprehensive 3D datasets of crania that span the entire clades of birds, squamates and caecilians, we demonstrate methods for capturing morphology across incredibly diverse shapes. We detail many of the difficulties associated with applying semilandmarks to comparable regions across highly disparate structures, and provide solutions to some of these challenges, while considering the consequences of decisions one makes in applying these approaches. Finally, we analyze the benefits of high-density sliding semilandmark approaches over landmark-only studies for capturing shape across diverse organisms and discuss the promise of these approaches for the study of organismal form." @default.
• W2955929233 created "2019-07-12" @default.
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• W2955929233 date "2019-01-01" @default.
• W2955929233 modified "2023-10-14" @default.
• W2955929233 title "A Practical Guide to Sliding and Surface Semilandmarks in Morphometric Analyses" @default.
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• W2955929233 doi "https://doi.org/10.1093/iob/obz016" @default.
• W2955929233 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7780474" @default.
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• W2955929233 hasPublicationYear "2019" @default.
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