Zobrazeno 1 - 10
of 232
pro vyhledávání: '"Andreas, Michael P."'
Autor:
Denner, Stefan, Scherer, Jonas, Kades, Klaus, Bounias, Dimitrios, Schader, Philipp, Kausch, Lisa, Bujotzek, Markus, Bucher, Andreas Michael, Penzkofer, Tobias, Maier-Hein, Klaus
In the rapidly evolving field of medical imaging, machine learning algorithms have become indispensable for enhancing diagnostic accuracy. However, the effectiveness of these algorithms is contingent upon the availability and organization of high-qua
Externí odkaz:
http://arxiv.org/abs/2309.17285
Autor:
Gupta, Vikash, Erdal, Barbaros Selnur, Ramirez, Carolina, Floca, Ralf, Jackson, Laurence, Genereaux, Brad, Bryson, Sidney, Bridge, Christopher P, Kleesiek, Jens, Nensa, Felix, Braren, Rickmer, Younis, Khaled, Penzkofer, Tobias, Bucher, Andreas Michael, Qin, Ming Melvin, Bae, Gigon, Lee, Hyeonhoon, Cardoso, M. Jorge, Ourselin, Sebastien, Kerfoot, Eric, Choudhury, Rahul, White, Richard D., Cook, Tessa, Bericat, David, Lungren, Matthew, Haukioja, Risto, Shuaib, Haris
Artificial Intelligence (AI) has become commonplace to solve routine everyday tasks. Because of the exponential growth in medical imaging data volume and complexity, the workload on radiologists is steadily increasing. We project that the gap between
Externí odkaz:
http://arxiv.org/abs/2212.14177
Autor:
Christopher Jonck, Andreas Michael Weimer, Beatrice Fundel, Wolfgang Heinz, Daniel Merkel, Hendrik Fiedel, Carlotta Ille, Roman Kloeckner, Holger Buggenhagen, Tim Piepho, Johannes Weimer
Publikováno v:
BMC Medical Education, Vol 24, Iss 1, Pp 1-14 (2024)
Abstract Background Point-of-care ultrasound (POCUS) is steadily growing in use in prehospital emergency medicine. While currently used primarily by emergency physicians, POCUS could also be employed by paramedics to support diagnosis and decision-ma
Externí odkaz:
https://doaj.org/article/724a2970826442c1bd8f77cb6d4a1295
Autor:
Jasmin Zeindler, Gabriel Fridolin Hess, Maximilian vonHeesen, Noa Aegerter, Cornelia Reber, Andreas Michael Schmitt, Simone Muenst, Martin Bolli, Savas Deniz Soysal, Otto Kollmar
Publikováno v:
Cancer Medicine, Vol 13, Iss 5, Pp n/a-n/a (2024)
Abstract Background The incidence of hepatocellular carcinoma (HCC) is increasing in the western world over the past decades. As liver resection (LR) represents one of the most efficient treatment options, advantages of anatomic (ALR) versus non‐an
Externí odkaz:
https://doaj.org/article/e977f32f79e44d8bb39bf44d4fe91a57
Publikováno v:
e-Journal of Nondestructive Testing, Vol 29, Iss 3 (2024)
Externí odkaz:
https://doaj.org/article/7f0d72c3f46f4db7aa49753709e39d3c
Autor:
Blickenstorfer, Yves, Müller, Markus, Dreyfus, Roland, Reichmuth, Andreas Michael, Fattinger, Christof, Frutiger, Andreas
Publikováno v:
Phys. Rev. Applied 15, 034023 (2021)
Diffractometric biosensing is a promising technology to overcome critical limitations of refractometric biosensors, the dominant class of label-free optical transducers. These limitations manifest themselves by higher noise and drifts due to insuffic
Externí odkaz:
http://arxiv.org/abs/2011.15052
We present a scheme to neutralize the dephasing effect induced by classical noise on a qubit. The scheme builds upon the key idea that this kind of noise can be recorded by a classical device during the qubit evolution, and that its effect can be und
Externí odkaz:
http://arxiv.org/abs/2004.08709
Akademický článek
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Akademický článek
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Autor:
Johannes Matthias Weimer, Nina Widmer, Kai-Uwe Strelow, Paula Hopf, Holger Buggenhagen, Klaus Dirks, Julian Künzel, Norbert Börner, Andreas Michael Weimer, Liv Annebritt Lorenz, Maximilian Rink, Henrik Bellhäuser, Lina Judit Schiestl, Roman Kloeckner, Lukas Müller, Julia Weinmann-Menke
Publikováno v:
Tomography, Vol 9, Iss 4, Pp 1315-1328 (2023)
Introduction: Ultrasound diagnostics is an important examination method in everyday clinical practice, but student education is often inadequate for acquiring sufficient basic skills. Individual universities have therefore started integrating (extra)
Externí odkaz:
https://doaj.org/article/ebb18c6995a84d6abe36bba4c69f1f56