Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Felix C. Müller"'
Autor:
Felix C. Müller, Henrik Børgesen, Kasper Gosvig, Anders Rodell, Christian Booz, Bernhard Schmidt, Bernhard Krauss, Mikael Boesen
Publikováno v:
European Radiology Experimental, Vol 3, Iss 1, Pp 1-8 (2019)
Abstract Background We investigated the influence of dose, spectral separation, pitch, rotation time, and reconstruction kernel on accuracy and image noise of virtual non-calcium images using a bone marrow phantom. Methods The phantom was developed a
Externí odkaz:
https://doaj.org/article/627af97bbc7947d1b479b50ae6dcb987
Autor:
Anna Døssing, Marius Henriksen, Karen Ellegaard, Sabrina Mai Nielsen, Lisa K Stamp, Felix C Müller, Margreet Kloppenburg, Ida K Haugen, Geraldine M McCarthy, Philip G Conaghan, Louise Ulff-Møller Dahl, Lene Terslev, Roy D Altman, Fabio Becce, Elisabeth Ginnerup-Nielsen, Lene Jensen, Mikael Boesen, Robin Christensen, Ulla Dal, Henning Bliddal
Publikováno v:
The Lancet Rheumatology. 5:e254-e262
Autor:
Peter V Vester-Glowinski, Mikkel Herly, Mathias Ørholt, Bo S Rasmussen, Felix C Müller, Jens J Elberg, Carsten Thomsen, Krzysztof T Drzewiecki
Publikováno v:
Aesthetic Surgery Journal. 42:1279-1289
Background The main challenge with fat grafting is loss of some of the graft to postsurgery resorption. Previous studies suggest that adipose-derived stromal cells (ASCs) can improve the volume retention of fat grafts but there is a lack of randomize
Autor:
Louis L. Plesner, Felix C. Müller, Janus D. Nybing, Lene C. Laustrup, Finn Rasmussen, Olav W. Nielsen, Mikael Boesen, Michael B. Andersen
Publikováno v:
Plesner, L L, Müller, F C, Nybing, J D, Laustrup, L C, Rasmussen, F, Nielsen, O W, Boesen, M & Andersen, M B 2023, ' Autonomous Chest Radiograph Reporting Using AI : Estimation of Clinical Impact ', Radiology, vol. 307, no. 3, e222268 . https://doi.org/10.1148/radiol.222268
Background Automated interpretation of normal chest radiographs could alleviate the workload of radiologists. However, the performance of such an artificial intelligence (AI) tool compared with clinical radiology reports has not been established. Pur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::43b7c410fafa538623e3f4b94d6813b8
https://pure.au.dk/portal/da/publications/autonomous-chest-radiograph-reporting-using-ai(584ed712-5b37-4f61-a8f5-6b6c0a24afd6).html
https://pure.au.dk/portal/da/publications/autonomous-chest-radiograph-reporting-using-ai(584ed712-5b37-4f61-a8f5-6b6c0a24afd6).html
Autor:
Peter V Vester-Glowinski, Mikkel Herly, Mathias Ørholt, Bo S Rasmussen, Felix C Müller, Jens J Elberg, Krzysztof T Drzewiecki
Publikováno v:
Aesthetic Surgery Journal. 43:NP302-NP303
Autor:
Christian Booz, Thomas J. Vogl, Marco Cavallaro, Tommaso D'Angelo, Felix C. Müller, Vitali Koch, Lukas Lenga, Ibrahim Yel, Christoph Mader, Moritz H. Albrecht, Giuseppe Cicero, Silvio Mazziotti, Kasper Kjærulf Gosvig, Julian L. Wichmann, Simon S. Martin
Publikováno v:
European Radiology. 31:4428-4437
To investigate the diagnostic accuracy of color-coded dual-energy CT virtual non-calcium (VNCa) reconstructions for the assessment of bone marrow edema (BME) of the scaphoid in patients with acute wrist trauma. Our retrospective study included data f
Publikováno v:
Brejnebøl, M W, Nielsen, Y W, Taubmann, O, Eibenberger, E & Müller, F C 2022, ' Artificial Intelligence based detection of pneumoperitoneum on CT scans in patients presenting with acute abdominal pain : A clinical diagnostic test accuracy study ', European Journal of Radiology, vol. 150, 110216 . https://doi.org/10.1016/j.ejrad.2022.110216
Purpose: The primary aim was to investigate the diagnostic performance of an Artificial Intelligence (AI) algorithm for pneumoperitoneum detection in patients with acute abdominal pain who underwent an abdominal CT scan. Method: This retrospective di
Autor:
Lene Collatz, Felix C. Müller, Michael Brun Andersen, Henriette Raaschou, Naurien Akhtar, Mathias Brejnebøl
Publikováno v:
Müller, F C, Raaschou, H, Akhtar, N, Brejnebøl, M, Collatz, L & Andersen, M B 2022, ' Impact of Concurrent Use of Artificial Intelligence Tools on Radiologists Reading Time : A Prospective Feasibility Study ', Academic Radiology, vol. 29, no. 7, pp. 1085-1090 . https://doi.org/10.1016/j.acra.2021.10.008
Rational and Objectives: This study investigated how an AI tool impacted radiologists reading time for non-contrast chest CT exams. Materials and Methods: An AI tool was implemented into the PACS reading workflow of non-contrast chest CT exams betwee
Autor:
Felix C. Müller, Sophie Sværke, Krzysztof T. Drzewiecki, Mathias Ørholt, Peter V Vester-Glowinski, Mathilde N. Hemmingsen, Jens Jørgen Elberg, J. L. Hansen, Mikkel Herly, Bo S. Rasmussen
Publikováno v:
Journal of Plastic, Reconstructive & Aesthetic Surgery. 72:1278-1284
Summary Background MRI is generally considered as the gold standard for measuring breast volume because of its high accuracy of the modality. Many techniques used to measure total breast volume have been validated, but none of these techniques have b
Publikováno v:
Dialogues in Human Geography. 9:88-93
Inspired by five commentaries on our forum article, in this response article we elaborate on three points related to geographies of dissociation, namely positioning dissociation, dealing with plurality and moving from agenda-setting to empirical rese