Zobrazeno 1 - 10
of 830
pro vyhledávání: '"P Isfort"'
Autor:
Arasteh, Soroosh Tayebi, Kuhl, Christiane, Saehn, Marwin-Jonathan, Isfort, Peter, Truhn, Daniel, Nebelung, Sven
Publikováno v:
Sci Rep 13, 22576 (2023)
Developing robust artificial intelligence (AI) models that generalize well to unseen datasets is challenging and usually requires large and variable datasets, preferably from multiple institutions. In federated learning (FL), a model is trained colla
Externí odkaz:
http://arxiv.org/abs/2310.00757
Autor:
Arasteh, Soroosh Tayebi, Lotfinia, Mahshad, Nolte, Teresa, Saehn, Marwin, Isfort, Peter, Kuhl, Christiane, Nebelung, Sven, Kaissis, Georgios, Truhn, Daniel
Publikováno v:
Radiology: Artificial Intelligence, 2024, 6(1), e230212
Developing robust and effective artificial intelligence (AI) models in medicine requires access to large amounts of patient data. The use of AI models solely trained on large multi-institutional datasets can help with this, yet the imperative to ensu
Externí odkaz:
http://arxiv.org/abs/2306.06503
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol X-2-2024, Pp 57-64 (2024)
The presented research investigates different strategies to acquire high-precision digital elevation models (DEMs) of complex and inaccessible terrain using Structure-from-Motion and Multi-View Stereo applied to data of an unoccupied aerial system (U
Externí odkaz:
https://doaj.org/article/e619dcd8ce2244af89a0489483e823ab
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol X-2-2024, Pp 113-120 (2024)
Robust and automated point cloud registration methods are required in many geoscience applications using multi-temporal and multi-modal 3D point clouds. Therefore, a 3D keypoint-based coarse registration workflow has been implemented, utilizing the I
Externí odkaz:
https://doaj.org/article/c6fd52494e09401f85be7bd70e6c12ed
Autor:
Arasteh, Soroosh Tayebi, Isfort, Peter, Saehn, Marwin, Mueller-Franzes, Gustav, Khader, Firas, Kather, Jakob Nikolas, Kuhl, Christiane, Nebelung, Sven, Truhn, Daniel
Publikováno v:
Sci Rep 13, 6046 (2023)
Due to the rapid advancements in recent years, medical image analysis is largely dominated by deep learning (DL). However, building powerful and robust DL models requires training with large multi-party datasets. While multiple stakeholders have prov
Externí odkaz:
http://arxiv.org/abs/2211.13606
Autor:
Claire Melchior, Peter Isfort, Till Braunschweig, Max Witjes, Vincent Van den Bosch, Ashkan Rashad, Jan Egger, Matías de la Fuente, Rainer Röhrig, Frank Hölzle, Behrus Puladi
Publikováno v:
BMC Medical Education, Vol 24, Iss 1, Pp 1-12 (2024)
Abstract Objective The gold standard of oral cancer (OC) treatment is diagnostic confirmation by biopsy followed by surgical treatment. However, studies have shown that dentists have difficulty performing biopsies, dental students lack knowledge abou
Externí odkaz:
https://doaj.org/article/89361731633a456eba0c0d9c46c4d587
Autor:
Soroosh Tayebi Arasteh, Christiane Kuhl, Marwin-Jonathan Saehn, Peter Isfort, Daniel Truhn, Sven Nebelung
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)
Abstract Developing robust artificial intelligence (AI) models that generalize well to unseen datasets is challenging and usually requires large and variable datasets, preferably from multiple institutions. In federated learning (FL), a model is trai
Externí odkaz:
https://doaj.org/article/f36d788857b04c089eade8cdc781ab7a
Autor:
Han, Tianyu, Kather, Jakob Nikolas, Pedersoli, Federico, Zimmermann, Markus, Keil, Sebastian, Schulze-Hagen, Maximilian, Terwoelbeck, Marc, Isfort, Peter, Haarburger, Christoph, Kiessling, Fabian, Schulz, Volkmar, Kuhl, Christiane, Nebelung, Sven, Truhn, Daniel
Disease-modifying management aims to prevent deterioration and progression of the disease, not just relieve symptoms. Unfortunately, the development of necessary therapies is often hampered by the failure to recognize the presymptomatic disease and l
Externí odkaz:
http://arxiv.org/abs/2111.11439
Autor:
Bruno Frackowiak, Vincent Van den Bosch, Zoi Tokoutsi, Marco Baragona, Martijn de Greef, Aaldert Elevelt, Peter Isfort
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-11 (2023)
Abstract A model-based planning tool, integrated in an imaging system, is envisioned for CT-guided percutaneous microwave ablation. This study aims to evaluate the biophysical model performance, by comparing its prediction retrospectively with the ac
Externí odkaz:
https://doaj.org/article/1d0392b1d6af457da6ff6c2cbd723b9e
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.