ArticleScientific data2018
Micro-computed tomography reconstructions of tibiae of stem cell transplanted osteogenesis imperfecta mice.
Article in Scientific data, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- A robust deep learning approach for segmenting cortical and trabecular bone from 3D high resolution µCT scans of mouse bone.Scientific reports · 2025Article
- Murine Animal Models in Osteogenesis Imperfecta: The Quest for Improving the Quality of Life.International journal of molecular sciences · 2022Review
- A preclinical micro-computed tomography database including 3D whole body organ segmentations.Scientific data · 2018Article
- Micro-computed tomography reconstructions of tibiae of stem cell transplanted osteogenesis imperfecta mice.Scientific data · 2018Article
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Authors and funding
4 authors.
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Abstract
Micro-computed tomography (micro-CT) is commonly used to assess bone quality and to evaluate the outcome of experimental therapies in animal models of bone diseases. Generating large datasets is however challenging and data are rarely made publicly available through shared repositories. Here we describe a dataset of micro-CT reconstructed scans of the proximal part of 21 tibiae from wild-type mice, osteogenesis imperfecta mice (homozygous oim/oim) and oim/oim mice transplanted with human amniotic fluid stem cells. The dataset contains, for each sample, 991 8-bit Bitmap reconstructed images and a 3D reconstruction of the bone in the PLY format, available at the online repository Figshare. In line with the increasing effort to make scientific datasets open-access, our data can be downloaded and used by other researchers to compare their observations with ours and to directly test scientific questions on osteogenesis imperfecta bones without the need to generate complete datasets.
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