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1,089 results on '"Dewey, Marc"'

1. Combination of computed tomography angiography with coronary artery calcium score for improved diagnosis of coronary artery disease: a collaborative meta-analysis of stable chest pain patients referred for invasive coronary angiography.

Author

Mohamed, Mahmoud, Bosserdt, Maria, Wieske, Viktoria, Dubourg, Benjamin, Alkadhi, Hatem, Garcia, Mario, Leschka, Sebastian, Zimmermann, Elke, Shabestari, Abbas, Nørgaard, Bjarne, Meijs, Matthijs, Øvrehus, Kristian, Diederichsen, Axel, Knuuti, Juhani, Halvorsen, Bjørn, Mendoza-Rodriguez, Vladymir, Wan, Yung-Liang, Bettencourt, Nuno, Martuscelli, Eugenio, Buechel, Ronny, Mickley, Hans, Sun, Kai, Muraglia, Simone, Kaufmann, Philipp, Herzog, Bernhard, Tardif, Jean-Claude, Schütz, Georg, Laule, Michael, Newby, David, Achenbach, Stephan, Haase, Robert, Biavati, Federico, Mézquita, Aldo, Schlattmann, Peter, Dewey, Marc, and Budoff, Matthew

Subjects
Computed tomography angiography, Coronary angiography, Coronary artery disease, Humans, Female, Male, Coronary Artery Disease, Coronary Angiography, Computed Tomography Angiography, Calcium, Predictive Value of Tests, Tomography, X-Ray Computed, Coronary Stenosis, Chest Pain
Abstract

OBJECTIVES: Coronary computed tomography angiography (CCTA) has higher diagnostic accuracy than coronary artery calcium (CAC) score for detecting obstructive coronary artery disease (CAD) in patients with stable chest pain, while the added diagnostic value of combining CCTA with CAC is unknown. We investigated whether combining coronary CCTA with CAC score can improve the diagnosis of obstructive CAD compared with CCTA alone. METHODS: A total of 2315 patients (858 women, 37%) aged 61.1 ± 10.2 from 29 original studies were included to build two CAD prediction models based on either CCTA alone or CCTA combined with the CAC score. CAD was defined as at least 50% coronary diameter stenosis on invasive coronary angiography. Models were built by using generalized linear mixed-effects models with a random intercept set for the original study. The two CAD prediction models were compared by the likelihood ratio test, while their diagnostic performance was compared using the area under the receiver-operating-characteristic curve (AUC). Net benefit (benefit of true positive versus harm of false positive) was assessed by decision curve analysis. RESULTS: CAD prevalence was 43.5% (1007/2315). Combining CCTA with CAC improved CAD diagnosis compared with CCTA alone (AUC: 87% [95% CI: 86 to 89%] vs. 80% [95% CI: 78 to 82%]; p

Published
2024

6. Impact of smoking in patients with suspected coronary artery disease in the randomised DISCHARGE trial

Author

Mancone, Massimo, Mézquita, Aldo J. Vázquez, Birtolo, Lucia Ilaria, Maurovich-Horvat, Pal, Kofoed, Klaus F., Benedek, Theodora, Donnelly, Patrick, Rodriguez-Palomares, Jose, Erglis, Andrejs, Štěchovský, Cyril, Šakalytė, Gintare, Ađić, Nada Čemerlić, Gutberlet, Matthias, Diez, Ignacio, Davis, Gershan, Zimmermann, Elke, Kępka, Cezary, Vidakovic, Radosav, Francone, Marco, Ilnicka-Suckiel, Małgorzata, Plank, Fabian, Knuuti, Juhanni, Faria, Rita, Schröder, Stephen, Berry, Colin, Saba, Luca, Ruzsics, Balazs, Rieckmann, Nina, Kubiak, Christine, Hansen, Kristian Schultz, Müller-Nordhorn, Jaqueline, Merkely, Bela, Sigvardsen, Per E., Benedek, Imre, Orr, Clare, Valente, Filipa Xavier, Zvaigzne, Ligita, Suchánek, Vojtěch, Jankauskas, Antanas, Ađić, Filip, Woinke, Michael, Keane, Stephen, Lecumberri, Ignacio, Thwaite, Erica, Kruk, Mariusz, Jovanovic, Vladimir, Kuśmierz, Donata, Feuchtner, Gudren, Pietilä, Mikko, Ribeiro, Vasco Gama, Drosch, Tanja, Delles, Christian, Palmisano, Vitanio, Fisher, Michael, Drobni, Zsófia D., Kragelund, Charlotte, Aurelian, Rosca, Kelly, Stephanie, del Blanco, Bruno Garcia, Rubio, Ainhoa, Boussoussou, Melinda, Hove, Jens D., Rodean, Ioana, Regan, Susan, Calabria, Hug Cuéllar, Becker, Dávid, Larsen, Linnea, Hodas, Roxana, Napp, Adriane E., Haase, Robert, Feger, Sarah, Mohamed, Mahmoud, Neumann, Konrad, Dreger, Henryk, Rief, Matthias, Wieske, Viktoria, Douglas, Pamela S., Estrella, Melanie, Bosserdt, Maria, Martus, Peter, Serna-Higuita, Lina M., Dodd, Jonathan D., and Dewey, Marc

Published
2024
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9. The effectiveness of coronary computed tomography angiography and functional testing for the diagnosis of obstructive coronary artery disease: results from the individual patient data Collaborative Meta-Analysis of Cardiac CT (COME-CCT)

Author

Schlattmann, Peter, Wieske, Viktoria, Bressem, Keno K., Götz, Theresa, Schuetz, Georg M., Andreini, Daniele, Pontone, Gianluca, Alkadhi, Hatem, Hausleiter, Jörg, Zimmermann, Elke, Gerber, Bernhard, Shabestari, Abbas A., Meijs, Matthijs F. L., Sato, Akira, Øvrehus, Kristian A., Jenkins, Shona M. M., Knuuti, Juhani, Hamdan, Ashraf, Halvorsen, Bjørn A., Mendoza-Rodriguez, Vladimir, Rixe, Johannes, Wan, Yung-Liang, Langer, Christoph, Leschka, Sebastian, Martuscelli, Eugenio, Ghostine, Said, Tardif, Jean-Claude, Sánchez, Alejandra Rodríguez, Haase, Robert, and Dewey, Marc

Published
2024
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10. Radiomics workflow definition & challenges - German priority program 2177 consensus statement on clinically applied radiomics

Author

Floca, Ralf, Bohn, Jonas, Haux, Christian, Wiestler, Benedikt, Zöllner, Frank G., Reinke, Annika, Weiß, Jakob, Nolden, Marco, Albert, Steffen, Persigehl, Thorsten, Norajitra, Tobias, Baeßler, Bettina, Dewey, Marc, Braren, Rickmer, Büchert, Martin, Fallenberg, Eva Maria, Galldiks, Norbert, Gerken, Annika, Götz, Michael, Hahn, Horst K., Haubold, Johannes, Haueise, Tobias, Große Hokamp, Nils, Ingrisch, Michael, Iuga, Andra-Iza, Janoschke, Marco, Jung, Matthias, Kiefer, Lena Sophie, Lohmann, Philipp, Machann, Jürgen, Moltz, Jan Hendrik, Nattenmüller, Johanna, Nonnenmacher, Tobias, Oerther, Benedict, Othman, Ahmed E., Peisen, Felix, Schick, Fritz, Umutlu, Lale, Wichtmann, Barbara D., Zhao, Wenzhao, Caspers, Svenja, Schlemmer, Heinz-Peter, Schlett, Christopher L., Maier-Hein, Klaus, and Bamberg, Fabian

Published
2024
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14. Interdisciplinary perspectives on computed tomography in sepsis: survey among medical doctors at a large university medical center

Author

Opper Hernando, Maria Isabel, Witham, Denis, Steinhagen, Peter Richard, Angermair, Stefan, Bauer, Wolfgang, Compton, Friederike, Edel, Andreas, Kruse, Jan, Kühnle, York, Lachmann, Gunnar, Marz, Susanne, Müller-Redetzky, Holger, Nee, Jens, Paul, Oliver, Praeger, Damaris, Skurk, Carsten, Stegemann, Miriam, Uhrig, Alexander, Wolf, Stefan, Zimmermann, Elke, Rubarth, Kerstin, Bolanaki, Myrto, Seybold, Joachim, Dewey, Marc, and Pohlan, Julian

Published
2023
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15. Clinical quantitative coronary artery stenosis and coronary atherosclerosis imaging: a Consensus Statement from the Quantitative Cardiovascular Imaging Study Group

Author

Mézquita, Aldo J. Vázquez, Biavati, Federico, Falk, Volkmar, Alkadhi, Hatem, Hajhosseiny, Reza, Maurovich-Horvat, Pál, Manka, Robert, Kozerke, Sebastian, Stuber, Matthias, Derlin, Thorsten, Channon, Keith M., Išgum, Ivana, Coenen, Adriaan, Foellmer, Bernhard, Dey, Damini, Volleberg, Rick H. J. A., Meinel, Felix G., Dweck, Marc R., Piek, Jan J., van de Hoef, Tim, Landmesser, Ulf, Guagliumi, Giulio, Giannopoulos, Andreas A., Botnar, René M., Khamis, Ramzi, Williams, Michelle C., Newby, David E., and Dewey, Marc

Published
2023
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16. Computed tomography angiography versus Agatston score for diagnosis of coronary artery disease in patients with stable chest pain: individual patient data meta-analysis of the international COME-CCT Consortium

Author

Wieske, Viktoria, Walther, Mario, Dubourg, Benjamin, Alkadhi, Hatem, Nørgaard, Bjarne L, Meijs, Matthijs FL, Diederichsen, Axel CP, Wan, Yung-Liang, Mickley, Hans, Nikolaou, Konstantin, Shabestari, Abbas A, Halvorsen, Bjørn A, Martuscelli, Eugenio, Sun, Kai, Herzog, Bernhard A, Marcus, Roy P, Leschka, Sebastian, Garcia, Mario J, Ovrehus, Kristian A, Knuuti, Juhani, Mendoza-Rodriguez, Vladymir, Bettencourt, Nuno, Muraglia, Simone, Buechel, Ronny R, Kaufmann, Philipp A, Zimmermann, Elke, Tardif, Jean-Claude, Budoff, Matthew J, Schlattmann, Peter, and Dewey, Marc

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Heart Disease - Coronary Heart Disease, Atherosclerosis, Cardiovascular, Heart Disease, Biomedical Imaging, Clinical Research, 4.2 Evaluation of markers and technologies, Detection, screening and diagnosis, Calcium, Chest Pain, Computed Tomography Angiography, Coronary Angiography, Coronary Artery Disease, Coronary Stenosis, Humans, Predictive Value of Tests, Tomography, X-Ray Computed, Computed tomography angiography, Coronary angiography, Coronary artery disease, COME-CCT Consortium, Nuclear Medicine & Medical Imaging, Clinical sciences
Abstract

ObjectivesThere is conflicting evidence about the comparative diagnostic accuracy of the Agatston score versus computed tomography angiography (CTA) in patients with suspected obstructive coronary artery disease (CAD).PurposeTo determine whether CTA is superior to the Agatston score in the diagnosis of CAD.MethodsIn total 2452 patients with stable chest pain and a clinical indication for invasive coronary angiography (ICA) for suspected CAD were included by the Collaborative Meta-analysis of Cardiac CT (COME-CCT) Consortium. An Agatston score of > 400 was considered positive, and obstructive CAD defined as at least 50% coronary diameter stenosis on ICA was used as the reference standard.ResultsObstructive CAD was diagnosed in 44.9% of patients (1100/2452). The median Agatston score was 74. Diagnostic accuracy of CTA for the detection of obstructive CAD (81.1%, 95% confidence interval [CI]: 77.5 to 84.1%) was significantly higher than that of the Agatston score (68.8%, 95% CI: 64.2 to 73.1%, p < 0.001). Among patients with an Agatston score of zero, 17% (101/600) had obstructive CAD. Diagnostic accuracy of CTA was not significantly different in patients with low to intermediate (1 to < 100, 100-400) versus moderate to high Agatston scores (401-1000, > 1000).ConclusionsResults in our international cohort show CTA to have significantly higher diagnostic accuracy than the Agatston score in patients with stable chest pain, suspected CAD, and a clinical indication for ICA. Diagnostic performance of CTA is not affected by a higher Agatston score while an Agatston score of zero does not reliably exclude obstructive CAD.Key points• CTA showed significantly higher diagnostic accuracy (81.1%, 95% confidence interval [CI]: 77.5 to 84.1%) for diagnosis of coronary artery disease when compared to the Agatston score (68.8%, 95% CI: 64.2 to 73.1%, p < 0.001). • Diagnostic performance of CTA was not affected by increased amount of calcium and was not significantly different in patients with low to intermediate (1 to 1000). • Seventeen percent of patients with an Agatston score of zero showed obstructive coronary artery disease by invasive angiography showing absence of coronary artery calcium cannot reliably exclude coronary artery disease.

Published
2022

20. Fully automated quantification of in vivo viscoelasticity of prostate zones using magnetic resonance elastography with Dense U-net segmentation

Author

Aldoj, Nader, Biavati, Federico, Dewey, Marc, Hennemuth, Anja, Asbach, Patrick, and Sack, Ingolf

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Machine Learning
Abstract

Magnetic resonance elastography (MRE) for measuring viscoelasticity heavily depends on proper tissue segmentation, especially in heterogeneous organs such as the prostate. Using trained network-based image segmentation, we investigated if MRE data suffice to extract anatomical and viscoelastic information for automatic tabulation of zonal mechanical properties of the prostate. Overall, 40 patients with benign prostatic hyperplasia (BPH) or prostate cancer (PCa) were examined with three magnetic resonance imaging (MRI) sequences: T2-weighted MRI (T2w), diffusion-weighted imaging (DWI), and MRE-based tomoelastography yielding six independent sets of imaging data per patient (T2w, DWI, apparent diffusion coefficient (ADC), MRE magnitude, shear wave speed, and loss angle maps). Combinations of these data were used to train Dense U-nets with manually segmented masks of the entire prostate gland (PG), central zone (CZ), and peripheral zone (PZ) in 30 patients and to validate them in 10 patients. Dice score (DS), sensitivity, specificity, and Hausdorff distance were determined. We found that segmentation based on MRE magnitude maps alone (DS, PG: 0.93$\pm$0.04, CZ: 0.95$\pm$0.03, PZ: 0.77$\pm$0.05) was more accurate than magnitude maps combined with T2w and DWI_b (DS, PG: 0.91$\pm$0.04, CZ: 0.91$\pm$0.06, PZ: 0.63$\pm$0.16) or T2w alone (DS, PG: 0.92$\pm$0.03, CZ: 0.91$\pm$0.04, PZ: 0.65$\pm$0.08). Automatically tabulated MRE values were not different from ground-truth values (P>0.05). In conclusion: MRE combined with Dense U-net segmentation allows tabulation of quantitative imaging markers without manual analysis and independent of other MRI sequences and can thus contribute to PCa detection and classification.

Published
2021

21. State-of-the-art CT and MR imaging and assessment of atherosclerotic carotid artery disease: standardization of scanning protocols and measurements—a consensus document by the European Society of Cardiovascular Radiology (ESCR)

Author

Saba, Luca, Loewe, Christian, Weikert, Thomas, Williams, Michelle C., Galea, Nicola, Budde, Ricardo P. J., Vliegenthart, Rozemarijn, Velthuis, Birgitta K., Francone, Marco, Bremerich, Jens, Natale, Luigi, Nikolaou, Konstantin, Dacher, Jean-Nicolas, Peebles, Charles, Caobelli, Federico, Redheuil, Alban, Dewey, Marc, Kreitner, Karl-Friedrich, and Salgado, Rodrigo

Published
2023
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22. State-of-the-art CT and MR imaging and assessment of atherosclerotic carotid artery disease: the reporting—a consensus document by the European Society of Cardiovascular Radiology (ESCR)

Author

Saba, Luca, Loewe, Christian, Weikert, Thomas, Williams, Michelle C., Galea, Nicola, Budde, Ricardo P. J., Vliegenthart, Rozemarijn, Velthuis, Birgitta K., Francone, Marco, Bremerich, Jens, Natale, Luigi, Nikolaou, Konstantin, Dacher, Jean-Nicolas, Peebles, Charles, Caobelli, Federico, Redheuil, Alban, Dewey, Marc, Kreitner, Karl-Friedrich, and Salgado, Rodrigo

Published
2023
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24. Unsupervised Adaptive Neural Network Regularization for Accelerated Radial Cine MRI

Author

Kofler, Andreas, Dewey, Marc, Schaeffter, Tobias, Kolbitsch, Christoph, and Haltmeier, Markus

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

In this work, we propose an iterative reconstruction scheme (ALONE - Adaptive Learning Of NEtworks) for 2D radial cine MRI based on ground truth-free unsupervised learning of shallow convolutional neural networks. The network is trained to approximate patches of the current estimate of the solution during the reconstruction. By imposing a shallow network topology and constraining the $L_2$-norm of the learned filters, the network's representation power is limited in order not to be able to recover noise. Therefore, the network can be interpreted to perform a low dimensional approximation of the patches for stabilizing the inversion process. We compare the proposed reconstruction scheme to two ground truth-free reconstruction methods, namely a well known Total Variation (TV) minimization and an unsupervised adaptive Dictionary Learning (DIC) method. The proposed method outperforms both methods with respect to all reported quantitative measures. Further, in contrast to DIC, where the sparse approximation of the patches involves the solution of a complex optimization problem, ALONE only requires a forward pass of all patches through the shallow network and therefore significantly accelerates the reconstruction.

Published
2020

25. Neural Networks-based Regularization for Large-Scale Medical Image Reconstruction

Author

Kofler, Andreas, Haltmeier, Markus, Schaeffter, Tobias, Kachelrieß, Marc, Dewey, Marc, Wald, Christian, and Kolbitsch, Christoph

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

In this paper we present a generalized Deep Learning-based approach for solving ill-posed large-scale inverse problems occuring in medical image reconstruction. Recently, Deep Learning methods using iterative neural networks and cascaded neural networks have been reported to achieve state-of-the-art results with respect to various quantitative quality measures as PSNR, NRMSE and SSIM across different imaging modalities. However, the fact that these approaches employ the forward and adjoint operators repeatedly in the network architecture requires the network to process the whole images or volumes at once, which for some applications is computationally infeasible. In this work, we follow a different reconstruction strategy by decoupling the regularization of the solution from ensuring consistency with the measured data. The regularization is given in the form of an image prior obtained by the output of a previously trained neural network which is used in a Tikhonov regularization framework. By doing so, more complex and sophisticated network architectures can be used for the removal of the artefacts or noise than it is usually the case in iterative networks. Due to the large scale of the considered problems and the resulting computational complexity of the employed networks, the priors are obtained by processing the images or volumes as patches or slices. We evaluated the method for the cases of 3D cone-beam low dose CT and undersampled 2D radial cine MRI and compared it to a total variation-minimization-based reconstruction algorithm as well as to a method with regularization based on learned overcomplete dictionaries. The proposed method outperformed all the reported methods with respect to all chosen quantitative measures and further accelerates the regularization step in the reconstruction by several orders of magnitude.

Published
2019
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28. Spatio-Temporal Deep Learning-Based Undersampling Artefact Reduction for 2D Radial Cine MRI with Limited Data

Author

Kofler, Andreas, Dewey, Marc, Schaeffter, Tobias, Wald, Christian, and Kolbitsch, Christoph

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

In this work we reduce undersampling artefacts in two-dimensional ($2D$) golden-angle radial cine cardiac MRI by applying a modified version of the U-net. We train the network on $2D$ spatio-temporal slices which are previously extracted from the image sequences. We compare our approach to two $2D$ and a $3D$ Deep Learning-based post processing methods and to three iterative reconstruction methods for dynamic cardiac MRI. Our method outperforms the $2D$ spatially trained U-net and the $2D$ spatio-temporal U-net. Compared to the $3D$ spatio-temporal U-net, our method delivers comparable results, but with shorter training times and less training data. Compared to the Compressed Sensing-based methods $kt$-FOCUSS and a total variation regularised reconstruction approach, our method improves image quality with respect to all reported metrics. Further, it achieves competitive results when compared to an iterative reconstruction method based on adaptive regularization with Dictionary Learning and total variation, while only requiring a small fraction of the computational time. A persistent homology analysis demonstrates that the data manifold of the spatio-temporal domain has a lower complexity than the spatial domain and therefore, the learning of a projection-like mapping is facilitated. Even when trained on only one single subject without data-augmentation, our approach yields results which are similar to the ones obtained on a large training dataset. This makes the method particularly suitable for training a network on limited training data. Finally, in contrast to the spatial $2D$ U-net, our proposed method is shown to be naturally robust with respect to image rotation in image space and almost achieves rotation-equivariance where neither data-augmentation nor a particular network design are required., Comment: To be published in IEEE Transactions on Medical Imaging

Published
2019
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36. Standardised lesion segmentation for imaging biomarker quantitation: a consensus recommendation from ESR and EORTC

Author

deSouza, Nandita M., van der Lugt, Aad, Deroose, Christophe M., Alberich-Bayarri, Angel, Bidaut, Luc, Fournier, Laure, Costaridou, Lena, Oprea-Lager, Daniela E., Kotter, Elmar, Smits, Marion, Mayerhoefer, Marius E., Boellaard, Ronald, Caroli, Anna, de Geus-Oei, Lioe-Fee, Kunz, Wolfgang G., Oei, Edwin H., Lecouvet, Frederic, Franca, Manuela, Loewe, Christian, Lopci, Egesta, Caramella, Caroline, Persson, Anders, Golay, Xavier, Dewey, Marc, O’Connor, James P. B., deGraaf, Pim, Gatidis, Sergios, and Zahlmann, Gudrun

Published
2022
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43. Correction to: State-of-the-art CT and MR imaging and assessment of atherosclerotic carotid artery disease: the reporting—a consensus document by the European Society of Cardiovascular Radiology (ESCR)

Author

Saba, Luca, Loewe, Christian, Weikert, Thomas, Williams, Michelle C., Galea, Nicola, Budde, Ricardo P. J., Vliegenthart, Rozemarijn, Velthuis, Birgitta K., Francone, Marco, Bremerich, Jens, Natale, Luigi, Nikolaou, Konstantin, Dacher, Jean-Nicolas, Peebles, Charles, Caobelli, Federico, Redheuil, Alban, Dewey, Marc, Kreitner, Karl-Friedrich, and Salgado, Rodrigo

Published
2023
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44. Correction to: State-of-the-art CT and MR imaging and assessment of atherosclerotic carotid artery disease: standardization of scanning protocols and measurements—a consensus document by the European Society of Cardiovascular Radiology (ESCR)

Author

Saba, Luca, Loewe, Christian, Weikert, Thomas, Williams, Michelle C., Galea, Nicola, Budde, Ricardo P. J., Vliegenthart, Rozemarijn, Velthuis, Birgitta K., Francone, Marco, Bremerich, Jens, Natale, Luigi, Nikolaou, Konstantin, Dacher, Jean-Nicolas, Peebles, Charles, Caobelli, Federico, Redheuil, Alban, Dewey, Marc, Kreitner, Karl-Friedrich, and Salgado, Rodrigo

Published
2023
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45. Erratum. Computed Tomography Versus Invasive Coronary Angiography in Patients With Diabetes and Suspected Coronary Artery Disease. Diabetes Care 2023;46:2015–2023

Author

Benedek, Theodora, primary, Wieske, Viktoria, additional, Szilveszter, Bálint, additional, Kofoed, Klaus F., additional, Donnelly, Patrick, additional, Rodriguez-Palomares, José, additional, Erglis, Andrejs, additional, Veselka, Josef, additional, Šakalytė, Gintarė, additional, Ađić, Nada Čemerlić, additional, Gutberlet, Matthias, additional, Diez, Ignacio, additional, Davis, Gershan, additional, Zimmermann, Elke, additional, Kępka, Cezary, additional, Vidakovic, Radosav, additional, Francone, Marco, additional, Ilnicka-Suckiel, Małgorzata, additional, Plank, Fabian, additional, Knuuti, Juhani, additional, Faria, Rita, additional, Schröder, Stephen, additional, Berry, Colin, additional, Saba, Luca, additional, Ruzsics, Balazs, additional, Rieckmann, Nina, additional, Kubiak, Christine, additional, Hansen, Kristian Schultz, additional, Müller-Nordhorn, Jacqueline, additional, Merkely, Bela, additional, Sigvardsen, Per E., additional, Benedek, Imre, additional, Orr, Clare, additional, Valente, Filipa Xavier, additional, Zvaigzne, Ligita, additional, Horváth, Martin, additional, Jankauskas, Antanas, additional, Ađić, Filip, additional, Woinke, Michael, additional, Mulvihill, Niall, additional, Lecumberri, Iñigo, additional, Thwaite, Erica, additional, Laule, Michael, additional, Kruk, Mariusz, additional, Stefanovic, Milica, additional, Mancone, Massimo, additional, Kuśmierz, Donata, additional, Feuchtner, Gudrun, additional, Pietilä, Mikko, additional, Ribeiro, Vasco Gama, additional, Drosch, Tanja, additional, Delles, Christian, additional, Melis, Marco, additional, Fisher, Michael, additional, Boussoussou, Melinda, additional, Kragelund, Charlotte, additional, Aurelian, Rosca, additional, Kelly, Stephanie, additional, Blanco, Bruno Garcia del, additional, Rubio, Ainhoa, additional, Károlyi, Mihály, additional, Hove, Jens D., additional, Rodean, Ioana, additional, Regan, Susan, additional, Calabria, Hug Cuéllar, additional, Gellér, László, additional, Larsen, Linnea, additional, Hodas, Roxana, additional, Napp, Adriane E., additional, Haase, Robert, additional, Feger, Sarah, additional, Mohamed, Mahmoud, additional, Serna-Higuita, Lina M., additional, Neumann, Konrad, additional, Dreger, Henryk, additional, Rief, Matthias, additional, Danesh, John, additional, Estrella, Melanie, additional, Bosserdt, Maria, additional, Martus, Peter, additional, Dodd, Jonathan D., additional, and Dewey, Marc, additional

Published
2024
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46. Prognostic value of noninvasive combined anatomic/functional assessment by cardiac CT in patients with suspected coronary artery disease — Comparison with invasive coronary angiography and nuclear myocardial perfusion imaging for the five-year-follow up of the CORE320 multicenter study

Author

Dewey, Marc, Rochitte, Carlos E., Ostovaneh, Mohammad R., Chen, Marcus Y., George, Richard T., Niinuma, Hiroyuki, Kitagawa, Kakuya, Laham, Roger, Kofoed, Klaus, Nomura, Cesar, Sakuma, Hajime, Yoshioka, Kunihiro, Mehra, Vishal C., Jinzaki, Masahiro, Kuribayashi, Sachio, Laule, Michael, Paul, Narinder, Scholte, Arthur J., Cerci, Rodrigo, Hoe, John, Tan, Swee Yaw, Rybicki, Frank J., Matheson, Matthew B., Vavere, Andrea L., Arai, Andrew E., Miller, Julie M., Cox, Christopher, Brinker, Jeffrey, Clouse, Melvin E., Di Carli, Marcelo, Lima, João A.C., and Arbab-Zadeh, Armin

Published
2021
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47. The Interplay of Artificial and Human Intelligence in Radiology – Exploring Socio-Technical System Dynamics

Author

Wilkens, Uta, Dewey, Marc, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Ahram, Tareq, editor, Taiar, Redha, editor, Colson, Serge, editor, and Choplin, Arnaud, editor

Published
2020
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48. Incorporating radiomics into clinical trials: expert consensus endorsed by the European Society of Radiology on considerations for data-driven compared to biologically driven quantitative biomarkers

Author

Fournier, Laure, Costaridou, Lena, Bidaut, Luc, Michoux, Nicolas, Lecouvet, Frederic E., de Geus-Oei, Lioe-Fee, Boellaard, Ronald, Oprea-Lager, Daniela E., Obuchowski, Nancy A, Caroli, Anna, Kunz, Wolfgang G., Oei, Edwin H., O’Connor, James P. B., Mayerhoefer, Marius E., Franca, Manuela, Alberich-Bayarri, Angel, Deroose, Christophe M., Loewe, Christian, Manniesing, Rashindra, Caramella, Caroline, Lopci, Egesta, Lassau, Nathalie, Persson, Anders, Achten, Rik, Rosendahl, Karen, Clement, Olivier, Kotter, Elmar, Golay, Xavier, Smits, Marion, Dewey, Marc, Sullivan, Daniel C., van der Lugt, Aad, deSouza, Nandita M., and European Society of Radiology

Published
2021
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50. Correction to: Computed tomography angiography versus Agatston score for diagnosis of coronary artery disease in patients with stable chest pain: individual patient data meta-analysis of the international COME-CCT Consortium

Author

Wieske, Viktoria, Walther, Mario, Dubourg, Benjamin, Alkadhi, Hatem, Nørgaard, Bjarne L., Meijs, Matthijs F. L., Diederichsen, Axel C. P., Wan, Yung-Liang, Mickley, Hans, Nikolaou, Konstantin, Shabestari, Abbas A., Halvorsen, Bjørn A., Martuscelli, Eugenio, Sun, Kai, Herzog, Bernhard A., Marcus, Roy P., Leschka, Sebastian, Garcia, Mario J., Ovrehus, Kristian A., Knuuti, Juhani, Mendoza-Rodriguez, Vladymir, Bettencourt, Nuno, Muraglia, Simone, Buechel, Ronny R., Kaufmann, Philipp A., Zimmermann, Elke, Tardif, Jean-Claude, Budoff, Matthew J., Schlattmann, Peter, and Dewey, Marc

Published
2022
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