ArticleRoyal Society open science2020
Three-dimensional segmentation of computed tomography data using
Article in Royal Society open science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- Resilient Calvarial Bone Marrow Supports Retinal Repair in Type 2 Diabetes.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- CCDC141 is a Connectin/Titin and Nesprin-1 binding protein that adapts cardiomyocytes to mechanical stress.Communications biology · 2025Article
- The origin and evolution of shrews (Soricidae, Mammalia).Proceedings. Biological sciences · 2024Article
- Advanced three-dimensional X-ray imaging unravels structural development of the human thymus compartments.Communications medicine · 2024Article
- Multiple embryonic sources converge to form the pectoral girdle skeleton in zebrafish.Nature communications · 2024Article
- 3D revisualization: a new method to revisit segmented data.Royal Society open science · 2024Article
- Single-cell guided prenatal derivation of primary fetal epithelial organoids from human amniotic and tracheal fluids.Nature medicine · 2024Article
- FOXI3 pathogenic variants cause one form of craniofacial microsomia.Nature communications · 2023Article
- Article
- Mineralized belemnoid cephalic cartilage from the late Triassic Polzberg Konservat-Lagerstätte (Austria).PloS one · 2022Article
- Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Computed tomography (CT) has become very widely used in scientific and medical research and industry for its non-destructive and high-resolution means of detecting internal structure. Three-dimensional segmentation of computed tomography data sheds light on internal features of target objects. Three-dimensional segmentation of CT data is supported by various well-established software programs, but the powerful functionalities and capabilities of open-source software have not been fully revealed. Here, we present a new release of the open-source volume exploration, rendering and three-dimensional segmentation software,
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Registered trials
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