A multimethod approach to the differentiation of enthesis bone microstructure based on soft tissue type
| Autor: | Jason S. Anderson, A. S. M. Hossain Bari, Marina L. Gavrilova, S. Amber Whitebone |
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| Rok vydání: | 2021 |
| Předmět: |
Orientation (computer vision)
Thin section Soft tissue Biology Enthesis Microstructure Bone and Bones Soft tissue reconstruction Microscopy Microscopy Electron Scanning Animals Animal Science and Zoology Microstructure morphology Collagen Neural Networks Computer Developmental Biology Biomedical engineering |
| Zdroj: | Journal of Morphology. 282:1362-1373 |
| ISSN: | 1097-4687 0362-2525 |
| DOI: | 10.1002/jmor.21391 |
| Popis: | Whereas there is a wealth of research studying the nature of various soft tissues that attach to bone, comparatively little research focuses on the bone's microscopic properties in the area where these tissues attach. Using scanning electron microscopy to generate a dataset of 1600 images of soft tissue attachment sites, an image classification program with novel convolutional neural network architecture can categorize images of attachment areas by soft tissue type based on observed patterns in microstructure morphology. Using stained histological thin section and liquid crystal cross-polarized microscopy, it is determined that soft tissue type can be quantitatively determined from the microstructure. The primary diagnostic characters are the orientation of collagen fibers and heterogeneity of collagen density throughout the attachment area thickness. These determinations are made across broad taxonomic sampling and multiple skeletal elements. |
| Databáze: | OpenAIRE |
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