Jesper Skovhus Thomsen
Aarhus University
203 Papers
1.4K Citations
Jesper Skovhus Thomsen is an academic researcher from Aarhus University. The author has contributed to research in topics: Bone remodeling & Medicine. The author has an hindex of 38, co-authored 190 publications. Previous affiliations of Jesper Skovhus Thomsen include Aarhus University Hospital & Copenhagen Business School.
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Papers
Non-rigid landmark-based large-scale image registration in 3-D reconstruction of mouse and rat kidney nephrons.
Yan-Ling Zhang,Yan-Ling Zhang,Shi-Jie Chang,Xiao-Yue Zhai,Jesper Skovhus Thomsen,Erik Ilsø Christensen,Arne Andreasen +6 more
TL;DR: NRT has facilitated the tracing of the tubular system in kidneys, a tracing, which would otherwise have been most difficult to perform, using a landmark-based non-rigid transformation (NRT).
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Systemic Treatment with Strontium Ranelate Does Not Influence the Healing of Femoral Mid-shaft Defects in Rats
TL;DR: 3 weeks of treatment with SrR increased the thickness of the healing mid-femoral cortical bone defects in rats, but did not influence BV/TV, mechanical properties, periosteal callus volume, or Oc.S/BS after either 3 or 8 the authors weeks of treatment.
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Chaotic hierarchy in a model of competing populations
TL;DR: It is found that the basic system with one type of bacteria and phages can show oscillations in a CSTR, and the principle of generating complexity by coupling of oscillators with a common feeding source is discussed.
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Application of design-based stereology for estimation of absolute volume and surface area of the articular and calcified cartilage compartments of undecalcified human femoral heads
Louise Brøndt Hartlev,Jens R. Nyengaard,Jesper Skovhus Thomsen,Lene Warner Thorup Boel,Kristian Stengaard-Pedersen,Ellen Margrethe Hauge +5 more
TL;DR: It is concluded that design‐based stereology using the Cavalieri estimator and vertical sections can successfully be used in large undecalcified tissue specimens, like the human femoral head, to estimate the absolute volume and surface area of macroscopic as well as of microscopic tissue compartments.
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Artificial intelligence-assisted identification and quantification of osteoclasts
TL;DR: Estimation of Oc.S/BS by the new AI-assisted method was considerably less time-consuming, while still providing similar results to the conventional manual method, and a detailed step-by-step guide for the AI-based method is presented.
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