Zobrazeno 1 - 10
of 128
pro vyhledávání: '"Raphael, Sznitman"'
Machine learning for predicting Plasmodium liver stage development in vitro using microscopy imaging
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 24, Iss , Pp 334-342 (2024)
Malaria, a significant global health challenge, is caused by Plasmodium parasites. The Plasmodium liver stage plays a pivotal role in the establishment of the infection. This study focuses on the liver stage development of the model organism Plasmodi
Externí odkaz:
https://doaj.org/article/526a79d2a5b54abe97d90832e78665f4
Autor:
Lorenzo Ferro Desideri, Rodrigo Anguita, Lieselotte E. Berger, Helena M. A. Feenstra, Davide Scandella, Raphael Sznitman, Camiel J. F. Boon, Elon H. C. van Dijk, Martin S. Zinkernagel
Publikováno v:
International Journal of Retina and Vitreous, Vol 10, Iss 1, Pp 1-6 (2024)
Abstract Aim To adopt a novel artificial intelligence (AI) optical coherence tomography (OCT)-based program to identify the presence of biomarkers associated with central serous chorioretinopathy (CSC) and whether these can differentiate between acut
Externí odkaz:
https://doaj.org/article/5242f88c97b64a93bb849fbb4a4da208
Autor:
Negin Ghamsarian, Yosuf El-Shabrawi, Sahar Nasirihaghighi, Doris Putzgruber-Adamitsch, Martin Zinkernagel, Sebastian Wolf, Klaus Schoeffmann, Raphael Sznitman
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-12 (2024)
Abstract In recent years, the landscape of computer-assisted interventions and post-operative surgical video analysis has been dramatically reshaped by deep-learning techniques, resulting in significant advancements in surgeons’ skills, operation r
Externí odkaz:
https://doaj.org/article/2ff693ec85df47a291734435a0800f05
Autor:
Negin Ghamsarian, Doris Putzgruber-Adamitsch, Stephanie Sarny, Raphael Sznitman, Klaus Schoeffmann, Yosuf El-Shabrawi
Publikováno v:
IEEE Access, Vol 12, Pp 21012-21025 (2024)
A critical yet unpredictable complication following cataract surgery is intraocular lens dislocation. Postoperative stability is imperative, as even a tiny decentration of multifocal lenses or inadequate alignment of the torus in toric lenses due to
Externí odkaz:
https://doaj.org/article/d610e6c5e4ae4d48a4b61ad0ec923ae7
Autor:
Javier Gamazo Tejero, Pablo Márquez Neila, Thomas Kurmann, Mathias Gallardo, Martin Zinkernagel, Sebastian Wolf, Raphael Sznitman
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-11 (2023)
Abstract Recent developments in deep learning have shown success in accurately predicting the location of biological markers in Optical Coherence Tomography (OCT) volumes of patients with Age-Related Macular Degeneration (AMD) and Diabetic Retinopath
Externí odkaz:
https://doaj.org/article/28f47c05f55e4c85bb2b3afd071f9e08
Autor:
Paulo Sampaio, Maria Lopez-Antuña, Federico Storni, Jonatan Wicht, Greta Sökeland, Martin Wartenberg, Pablo Márquez-Neila, Daniel Candinas, Brice-Olivier Demory, Aurel Perren, Raphael Sznitman
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-9 (2023)
Abstract Polarimetry is an optical characterization technique capable of analyzing the polarization state of light reflected by materials and biological samples. In this study, we investigate the potential of Müller matrix polarimetry (MMP) to analy
Externí odkaz:
https://doaj.org/article/eaed0988715140fa9c1d1e35bf32b0a2
Autor:
Lukas Zbinden, Damiano Catucci, Yannick Suter, Annalisa Berzigotti, Lukas Ebner, Andreas Christe, Verena Carola Obmann, Raphael Sznitman, Adrian Thomas Huber
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-11 (2022)
Abstract We evaluated the effectiveness of automated segmentation of the liver and its vessels with a convolutional neural network on non-contrast T1 vibe Dixon acquisitions. A dataset of non-contrast T1 vibe Dixon liver magnetic resonance images was
Externí odkaz:
https://doaj.org/article/bfb6af6dbcb64cd58c2af9ead711dfc6
Autor:
Rui Guo, Song Xue, Jiaxi Hu, Hasan Sari, Clemens Mingels, Konstantinos Zeimpekis, George Prenosil, Yue Wang, Yu Zhang, Marco Viscione, Raphael Sznitman, Axel Rominger, Biao Li, Kuangyu Shi
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-9 (2022)
Deep learning-based methods have been proposed to substitute CT-based PET attenuation and scatter correction to achieve CT-free PET imaging. Here, the authors present a simple way to integrate domain knowledge in deep learning for CT-free PET imaging
Externí odkaz:
https://doaj.org/article/2669a4cebe2441658deeaa6f5c04e23d
Autor:
Henning Nilius, Adam Cuker, Sigve Haug, Christos Nakas, Jan-Dirk Studt, Dimitrios A. Tsakiris, Andreas Greinacher, Adriana Mendez, Adrian Schmidt, Walter A. Wuillemin, Bernhard Gerber, Johanna A. Kremer Hovinga, Prakash Vishnu, Lukas Graf, Alexander Kashev, Raphael Sznitman, Tamam Bakchoul, Michael Nagler
Publikováno v:
EClinicalMedicine, Vol 55, Iss , Pp 101745- (2023)
Summary: Background: Diagnosing heparin-induced thrombocytopenia (HIT) at the bedside remains challenging, exposing a significant number of patients at risk of delayed diagnosis or overtreatment. We hypothesized that machine-learning algorithms could
Externí odkaz:
https://doaj.org/article/abfa12e6d5a74c3790cf25650e4523cd
Autor:
Marc‐Antoine Jacques, Maciej Dobrzyński, Paolo Armando Gagliardi, Raphael Sznitman, Olivier Pertz
Publikováno v:
Molecular Systems Biology, Vol 17, Iss 4, Pp 1-14 (2021)
Abstract Current studies of cell signaling dynamics that use live cell fluorescent biosensors routinely yield thousands of single‐cell, heterogeneous, multi‐dimensional trajectories. Typically, the extraction of relevant information from time ser
Externí odkaz:
https://doaj.org/article/f2829017a251456bbdf08ad8a70f4824