Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Muscular atrophy/diagnostic imaging"'
Publikováno v:
Pingel, J, Kjer, H M, Biering-Sørensen, F, Feidenhans'l, R & Dyrby, T B 2022, ' 3D synchrotron imaging of muscle tissues at different atrophic stages in stroke and spinal cord injury : a proof-of-concept study ', Scientific Reports, vol. 12, no. 1, 17289 . https://doi.org/10.1038/s41598-022-21741-z
Pingel, J, Kjer, H M, Biering-Sorensen, F, Feidenhans'l, R & Dyrby, T B 2022, ' 3D synchrotron imaging of muscle tissues at different atrophic stages in stroke and spinal cord injury : a proof-of-concept study ', Scientific Reports, vol. 12, 17289 . https://doi.org/10.1038/s41598-022-21741-z
Pingel, J, Kjer, H M, Biering-Sorensen, F, Feidenhans'l, R & Dyrby, T B 2022, ' 3D synchrotron imaging of muscle tissues at different atrophic stages in stroke and spinal cord injury : a proof-of-concept study ', Scientific Reports, vol. 12, 17289 . https://doi.org/10.1038/s41598-022-21741-z
Synchrotron X-ray computed tomography (SXCT) allows 3D imaging of tissue with a very large field of view and an excellent micron resolution and enables the investigation of muscle fiber atrophy in 3D. The study aimed to explore the 3D micro-architect
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6df56f6f76ed63922ed8217e24444ab9
https://curis.ku.dk/ws/files/322801842/Fulltext.pdf
https://curis.ku.dk/ws/files/322801842/Fulltext.pdf
Autor:
Sunita Mathur, João Luiz Quaglioti Durigan, Priscilla Flávia de Melo, Luciana Marques Vieira, Larissa Santana, Gerson Cipriano, Lara Patrícia Bastos Rocha, Vinicius Zacarias Maldaner da Silva
Publikováno v:
Revista Brasileira de Terapia Intensiva
To evaluate the safety and feasibility of the ultrasound assessment of quadriceps in the emergency setting. To assess the intra- and interrater reliability for the acquisition and analysis of ultrasound images of muscle thickness and echogenicity in
Autor:
Alain Farron, Fabio Becce, Stacey Gidoin, Oskar Truffer, Elham Taghizadeh, Alexandre Terrier, Sylvain Eminian, Philippe Büchler
Publikováno v:
European radiology, vol. 31, no. 1, pp. 181-190
European Radiology
Taghizadeh, Elham; Truffer, Oskar; Becce, Fabio; Eminian, Sylvain; Gidoin, Stacey; Terrier, Alexandre; Farron, Alain; Büchler, Philippe (2021). Deep learning for the rapid automatic quantification and characterization of rotator cuff muscle degeneration from shoulder CT datasets. European radiology, 31(1), pp. 181-190. Springer-Verlag 10.1007/s00330-020-07070-7
European Radiology
Taghizadeh, Elham; Truffer, Oskar; Becce, Fabio; Eminian, Sylvain; Gidoin, Stacey; Terrier, Alexandre; Farron, Alain; Büchler, Philippe (2021). Deep learning for the rapid automatic quantification and characterization of rotator cuff muscle degeneration from shoulder CT datasets. European radiology, 31(1), pp. 181-190. Springer-Verlag 10.1007/s00330-020-07070-7
Objectives This study aimed at developing a convolutional neural network (CNN) able to automatically quantify and characterize the level of degeneration of rotator cuff (RC) muscles from shoulder CT images including muscle atrophy and fatty infiltrat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c0f97c9c646870e3a8927e3b4efba0ba
https://serval.unil.ch/notice/serval:BIB_CF8206F40600
https://serval.unil.ch/notice/serval:BIB_CF8206F40600
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