Blar i Brage NIH på forfatter "Cronin, Neil J."
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Distinct muscle-tendon interaction during running at different speeds and in different loading conditions
Werkhausen, Amelie; Cronin, Neil J.; Albracht, Kirsten; Bojsen-Møller, Jens; Seynnes, Olivier R. (Peer reviewed; Journal article, 2019)The interaction between the Achilles tendon and the triceps surae muscles seems to be modulated differently with various task configurations. Here we tested the hypothesis that the increased forces and ankle joint work ... -
DL_Track_US: A python package to analyse muscle ultrasonography images
Ritsche, Paul; Seynnes, Olivier Roger; Cronin, Neil J. (Peer reviewed; Journal article, 2023)Ultrasonography can be used to assess muscle architectural parameters during static and dynamic conditions. Nevertheless, the analysis of the acquired ultrasonography images presents a major difficulty. Muscle architectural ... -
Simple muscle architecture analysis (SMA): An ImageJ macro tool to automate measurements in B-mode ultrasound scans
Seynnes, Olivier R.; Cronin, Neil J. (Peer reviewed; Journal article, 2020)In vivo measurements of muscle architecture (i.e. the spatial arrangement of muscle fascicles) are routinely included in research and clinical settings to monitor muscle structure, function and plasticity. However, in most ... -
Training-induced increase in Achilles tendon stiffness affects tendon strain pattern during running
Werkhausen, Amelie; Cronin, Neil J.; Albracht, Kirsten; Paulsen, Gøran; Larsen, Askild V.; Bojsen-Møller, Jens; Seynnes, Olivier R. (Peer reviewed; Journal article, 2019)Background: During the stance phase of running, the elasticity of the Achilles tendon enables the utilisation of elastic energy and allows beneficial contractile conditions for the triceps surae muscles. However, the effect ... -
Using deep learning to generate synthetic B-mode musculoskeletal ultrasound images
Cronin, Neil J.; Finni, Taija; Seynnes, Olivier R. (Peer reviewed; Journal article, 2020)Background and objective Deep learning approaches are common in image processing, but often rely on supervised learning, which requires a large volume of training images, usually accompanied by hand-crafted labels. As ...