Search Results - "Eulig, Elias"

Benchmarking deep learning-based low-dose CT image denoising algorithms by Eulig, Elias, Ommer, Björn, Kachelrieß, Marc

“…Long-lasting efforts have been made to reduce radiation dose and thus the potential radiation risk to the patient for computed tomography (CT) acquisitions…”
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Real‐time estimation of patient‐specific dose distributions for medical CT using the deep dose estimation by Maier, Joscha, Klein, Laura, Eulig, Elias, Sawall, Stefan, Kachelrieß, Marc

“…Purpose With the rising number of computed tomography (CT) examinations and the trend toward personalized medicine, patient‐specific dose estimates are…”
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Real‐time scatter estimation for medical CT using the deep scatter estimation: Method and robustness analysis with respect to different anatomies, dose levels, tube voltages, and data truncation by Maier, Joscha, Eulig, Elias, Vöth, Tim, Knaup, Michael, Kuntz, Jan, Sawall, Stefan, Kachelrieß, Marc

“…Purpose X‐ray scattering leads to CT images with a reduced contrast, inaccurate CT values as well as streak and cupping artifacts. Therefore, scatter…”
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Reconstructing and analyzing the invariances of low-dose CT image denoising networks by Eulig, Elias, Jäger, Fabian, Maier, Joscha, Ommer, Björn, Kachelrieß, Marc

“…Deep learning-based methods led to significant advancements in many areas of medical imaging, most of which are concerned with the reduction of artifacts…”
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Training of a deep learning based digital subtraction angiography method using synthetic data by Duan, Lizhen, Eulig, Elias, Knaup, Michael, Adamus, Ralf, Lell, Michael, Kachelrieß, Marc

“…Background Digital subtraction angiography (DSA) is a fluoroscopy method primarily used for the diagnosis of cardiovascular diseases (CVDs). Deep…”
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Real-time 3D reconstruction of guidewires and stents using two update X-ray projections in a rotating imaging setup by Vöth, Tim, Koenig, Thomas, Eulig, Elias, Knaup, Michael, Wiesmann, Veit, Hörndler, Klaus, Kachelrieß, Marc

“…Vascular diseases are often treated minimally invasively. The interventional material (stents, guidewires, etc.) used during such percutaneous interventions…”
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Deep learning‐based coronary artery motion estimation and compensation for short‐scan cardiac CT by Maier, Joscha, Lebedev, Sergej, Erath, Julien, Eulig, Elias, Sawall, Stefan, Fournié, Eric, Stierstorfer, Karl, Lell, Michael, Kachelrieß, Marc

“…Purpose During a typical cardiac short scan, the heart can move several millimeters. As a result, the corresponding CT reconstructions may be corrupted by…”
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Deep learning‐based reconstruction of interventional tools and devices from four X‐ray projections for tomographic interventional guidance by Eulig, Elias, Maier, Joscha, Knaup, Michael, Bennett, N. Robert, Hörndler, Klaus, Wang, Adam S., Kachelrieß, Marc

“…Purpose Image guidance for minimally invasive interventions is usually performed by acquiring fluoroscopic images using a monoplanar or a biplanar C‐arm…”
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DiagViB-6: A Diagnostic Benchmark Suite for Vision Models in the Presence of Shortcut and Generalization Opportunities by Eulig, Elias, Saranrittichai, Piyapat, Mummadi, Chaithanya Kumar, Rambach, Kilian, Beluch, William, Shi, Xiahan, Fischer, Volker

“…Common deep neural networks (DNNs) for image classification have been shown to rely on shortcut opportunities (SO) in the form of predictive and…”
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Benchmarking Deep Learning-Based Low-Dose CT Image Denoising Algorithms by Eulig, Elias, Ommer, Björn, Kachelrieß, Marc

“…Long lasting efforts have been made to reduce radiation dose and thus the potential radiation risk to the patient for computed tomography acquisitions without…”
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Toward Falsifying Causal Graphs Using a Permutation-Based Test by Eulig, Elias, Mastakouri, Atalanti A, Blöbaum, Patrick, Hardt, Michaela, Janzing, Dominik

“…Understanding the causal relationships among the variables of a system is paramount to explain and control its behaviour. Inferring the causal graph from…”
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Assumption violations in causal discovery and the robustness of score matching by Montagna, Francesco, Mastakouri, Atalanti A, Eulig, Elias, Noceti, Nicoletta, Rosasco, Lorenzo, Janzing, Dominik, Aragam, Bryon, Locatello, Francesco

“…When domain knowledge is limited and experimentation is restricted by ethical, financial, or time constraints, practitioners turn to observational causal…”
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DiagViB-6: A Diagnostic Benchmark Suite for Vision Models in the Presence of Shortcut and Generalization Opportunities by Eulig, Elias, Saranrittichai, Piyapat, Mummadi, Chaithanya Kumar, Rambach, Kilian, Beluch, William, Shi, Xiahan, Fischer, Volker

“…Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021, pp. 10655-10664 Common deep neural networks (DNNs) for image…”
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Deep Learning-Based Reconstruction of Interventional Tools from Four X-Ray Projections for Tomographic Interventional Guidance by Eulig, Elias, Maier, Joscha, Knaup, Michael, Bennett, N. Robert, Hörndler, Klaus, Wang, Adam S, Kachelrieß, Marc

“…Eulig, E., et al. Deep learning-based reconstruction of interventional tools and devices from four X-ray projections for tomographic interventional guidance…”
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Real-Time Patient-Specific CT Dose Estimation using a Deep Convolutional Neural Network by Maier, Joscha, Eulig, Elias, Dorn, Sabrina, Sawall, Stefan, Kachelries, Marc

“…Due to the potential risk of ionizing radiation, the assessment of the administered radiation dose is an important topic in CT. However, dosimetric quantities…”
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