Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Claudio E von Schacky"'
Autor:
Gregor S Zimmermann, Alexander A Fingerle, Christina Müller-Leisse, Felix Gassert, Claudio E von Schacky, Tareq Ibrahim, Karl-Ludwig Laugwitz, Fabian Geisler, Christoph Spinner, Bernhard Haller, Markus R Makowski, Jonathan Nadjiri
Publikováno v:
PLoS ONE, Vol 15, Iss 12, p e0244707 (2020)
BackgroundSince the outbreak of the COVID-19 pandemic, a number of risk factors for a poor outcome have been identified. Thereby, cardiovascular comorbidity has a major impact on mortality. We investigated whether coronary calcification as a marker f
Externí odkaz:
https://doaj.org/article/aa07cad0a783438b86d1b2c4beab9a91
Autor:
Aleksandra M. Paciorek, Claudio E. von Schacky, Sarah C. Foreman, Felix G. Gassert, Florian T. Gassert, Jan S. Kirschke, Karl-Ludwig Laugwitz, Tobias Geith, Martin Hadamitzky, Jonathan Nadjiri
Publikováno v:
BMC Medical Imaging, Vol 24, Iss 1, Pp 1-13 (2024)
Abstract Background A deep learning (DL) model that automatically detects cardiac pathologies on cardiac MRI may help streamline the diagnostic workflow. To develop a DL model to detect cardiac pathologies on cardiac MRI T1-mapping and late gadoliniu
Externí odkaz:
https://doaj.org/article/a5ad92af55354f5f974c629581339eff
Autor:
Manuel Schultheiss, Philipp Schmette, Jannis Bodden, Juliane Aichele, Christina Müller-Leisse, Felix G. Gassert, Florian T. Gassert, Joshua F. Gawlitza, Felix C. Hofmann, Daniel Sasse, Claudio E. von Schacky, Sebastian Ziegelmayer, Fabio De Marco, Bernhard Renger, Marcus R. Makowski, Franz Pfeiffer, Daniela Pfeiffer
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
Abstract We present a method to generate synthetic thorax radiographs with realistic nodules from CT scans, and a perfect ground truth knowledge. We evaluated the detection performance of nine radiologists and two convolutional neural networks in a r
Externí odkaz:
https://doaj.org/article/d2e234157a904202804449b039ffdf57
Autor:
Rafael Adolf, Nejva Nano, Alessa Chami, Claudio E. von Schacky, Albrecht Will, Eva Hendrich, Stefan A. Martinoff, Martin Hadamitzky
Publikováno v:
The International Journal of Cardiovascular Imaging. 39:1209-1216
To assess the prognostic value of convolutional neural networks (CNN) on coronary computed tomography angiography (CCTA) in comparison to conventional computed tomography (CT) reporting and clinical risk scores. 5468 patients who underwent CCTA with
Autor:
Florian T. Gassert, Johannes Hammel, Felix C. Hofmann, Jan Neumann, Claudio E. von Schacky, Felix G. Gassert, Daniela Pfeiffer, Franz Pfeiffer, Marcus R. Makowski, Klaus Woertler, Alexandra S. Gersing, Benedikt J. Schwaiger
Publikováno v:
Diagnostics, Vol 11, Iss 6, p 953 (2021)
The aim of this study is to assess whether perifocal bone marrow edema (BME) in patients with osteoid osteoma (OO) can be accurately detected on dual-layer spectral CT (DLCT) with three-material decomposition. To that end, 18 patients with OO (25.33
Externí odkaz:
https://doaj.org/article/48f761e8e6134389aafd5c51b227c81f
Autor:
Egon Burian, Benjamin Palla, Nicholas Callahan, Thomas Pyka, Constantin Wolff, Claudio E. von Schacky, Annabelle Schmid, Matthias F. Froelich, Johannes Rübenthaler, Marcus R. Makowski, Felix G. Gassert
Publikováno v:
Burian, Egon; Palla, Benjamin; Callahan, Nicholas; Pyka, Thomas; Wolff, Constantin; von Schacky, Claudio E; Schmid, Annabelle; Froelich, Matthias F; Rübenthaler, Johannes; Makowski, Marcus R; Gassert, Felix G (2022). Comparison of CT, MRI, and F-18 FDG PET/CT for initial N-staging of oral squamous cell carcinoma: a cost-effectiveness analysis. European journal of nuclear medicine and molecular imaging, 49(11), pp. 3870-3877. Springer 10.1007/s00259-022-05843-4
Background and purpose Treatment of oral squamous cell carcinoma (OSCC) is based on clinical exam, biopsy, and a precise imaging-based TNM-evaluation. A high sensitivity and specificity for magnetic resonance imaging (MRI) and F-18 FDG PET/CT are rep
Autor:
Claudio E. von Schacky, Nikolas J. Wilhelm, Valerie S. Schäfer, Yannik Leonhardt, Matthias Jung, Pia M. Jungmann, Maximilian F. Russe, Sarah C. Foreman, Felix G. Gassert, Florian T. Gassert, Benedikt J. Schwaiger, Carolin Mogler, Carolin Knebel, Ruediger von Eisenhart-Rothe, Marcus R. Makowski, Klaus Woertler, Rainer Burgkart, Alexandra S. Gersing
Publikováno v:
European Radiology. 32:6247-6257
Objectives To develop and validate machine learning models to distinguish between benign and malignant bone lesions and compare the performance to radiologists. Methods In 880 patients (age 33.1 ± 19.4 years, 395 women) diagnosed with malignant (n =
Autor:
Alexandra S. Gersing, Rainer Burgkart, Marcus R. Makowski, Rüdiger von Eisenhart-Rothe, Florian T. Gassert, Carolin Mogler, Matthias Jung, Pia M. Jungmann, Felix G. Gassert, Claudio E. von Schacky, Valerie S. Schäfer, Sarah C. Foreman, Maximilian F. Russe, Klaus Woertler, Yannik Leonhardt, Nikolas J. Wilhelm, Carolin Knebel
Publikováno v:
Radiology. 301:398-406
Background An artificial intelligence model that assesses primary bone tumors on radiographs may assist in the diagnostic workflow. Purpose To develop a multitask deep learning (DL) model for simultaneous bounding box placement, segmentation, and cla
Autor:
Justus Wolff, Julian Matschinske, Dietrich Baumgart, Anne Pytlik, Andreas Keck, Arunakiry Natarajan, Claudio E. von Schacky, Josch K. Pauling, Jan Baumbach
Publikováno v:
Journal of Integrative Bioinformatics. 19
The implementation of Artificial Intelligence (AI) still faces significant hurdles and one key factor is the access to data. One approach that could support that is federated machine learning (FL) since it allows for privacy preserving data access. F
Autor:
Claudio E. von Schacky
Publikováno v:
Osteologie. 30:261-263