Oshane O. Thomas
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View article: Trustworthy detection of exencephaly in high-throughput micro-CT embryo screens with focal-loss transformers
Trustworthy detection of exencephaly in high-throughput micro-CT embryo screens with focal-loss transformers Open
1. Abstract Lethal and sub-viable knockout mouse lines require whole-embryo 3D imaging to connect genotype to phenotype (Dickinson et al., 2016; Cacheiro et al., 2022). There are often far fewer samples of in-class (e.g., homozygous knocko…
View article: SlicerMorph photogrammetry: an open-source photogrammetry workflow for reconstructing 3D models
SlicerMorph photogrammetry: an open-source photogrammetry workflow for reconstructing 3D models Open
High-fidelity three-dimensional (3D) models of skeletal specimens underpin many ecological and evolutionary analyses. Here we present a fully open pipeline inside the 3D Slicer platform that couples automatic image masking by the Segment A…
View article: SlicerMorph Photogrammetry: An Open-Source Photogrammetry Workflow for Reconstructing 3D Models
SlicerMorph Photogrammetry: An Open-Source Photogrammetry Workflow for Reconstructing 3D Models Open
1. Context Accurate three-dimensional (3D) models of skeletal and other biological specimens are crucial for ecological and evolutionary research and teaching. Here, we present a streamlined, open-source workflow for 3D photogrammetry that…
View article: Leveraging descriptor learning and functional map‐based shape matching for automated anatomical Landmarking in mouse mandibles
Leveraging descriptor learning and functional map‐based shape matching for automated anatomical Landmarking in mouse mandibles Open
Geometric morphometrics is used in the biological sciences to quantify morphological traits. However, the need for manual landmark placement hampers scalability, which is both time‐consuming, labor‐intensive, and open to human error. The s…
View article: Leveraging Descriptor Learning and Functional Map-based Shape Matching for Automatic Landmark Acquisition
Leveraging Descriptor Learning and Functional Map-based Shape Matching for Automatic Landmark Acquisition Open
Geometric morphometrics is widely employed across the biological sciences for the quantification of morphological traits. However, the scalability of these methods to large datasets is hampered by the requisite placement of landmarks, whic…
View article: Automated morphological phenotyping using learned shape descriptors and functional maps: A novel approach to geometric morphometrics
Automated morphological phenotyping using learned shape descriptors and functional maps: A novel approach to geometric morphometrics Open
The methods of geometric morphometrics are commonly used to quantify morphology in a broad range of biological sciences. The application of these methods to large datasets is constrained by manual landmark placement limiting the number of …