Zobrazeno 1 - 10
of 4 065
pro vyhledávání: '"Niendorf, A."'
Autor:
Graf, Robert, Hunecke, Florian, Pohl, Soeren, Atad, Matan, Moeller, Hendrik, Starck, Sophie, Kroencke, Thomas, Bette, Stefanie, Bamberg, Fabian, Pischon, Tobias, Niendorf, Thoralf, Schmidt, Carsten, Paetzold, Johannes C., Rueckert, Daniel, Kirschke, Jan S
Deep learning has made significant strides in medical imaging, leveraging the use of large datasets to improve diagnostics and prognostics. However, large datasets often come with inherent errors through subject selection and acquisition. In this pap
Externí odkaz:
http://arxiv.org/abs/2410.10220
Autor:
Vourliotis, Emmanouil, Chang, Philip, Elmer, Peter, Gu, Yanxi, Guiang, Jonathan, Krutelyov, Vyacheslav, Narayanan, Balaji Venkat Sathia, Niendorf, Gavin, Reid, Michael, Silva, Mayra, Tascon, Andres Rios, Tadel, Matevž, Wittich, Peter, Yagil, Avraham
Charged particle reconstruction is one the most computationally heavy components of the full event reconstruction of Large Hadron Collider (LHC) experiments. Looking to the future, projections for the High Luminosity LHC (HL-LHC) indicate a superline
Externí odkaz:
http://arxiv.org/abs/2407.18231
Autor:
Häntze, Hartmut, Xu, Lina, Mertens, Christian J., Dorfner, Felix J., Donle, Leonhard, Busch, Felix, Kader, Avan, Ziegelmayer, Sebastian, Bayerl, Nadine, Navab, Nassir, Rueckert, Daniel, Schnabel, Julia, Aerts, Hugo JWL, Truhn, Daniel, Bamberg, Fabian, Weiß, Jakob, Schlett, Christopher L., Ringhof, Steffen, Niendorf, Thoralf, Pischon, Tobias, Kauczor, Hans-Ulrich, Nonnenmacher, Tobias, Kröncke, Thomas, Völzke, Henry, Schulz-Menger, Jeanette, Maier-Hein, Klaus, Prokop, Mathias, van Ginneken, Bram, Hering, Alessa, Makowski, Marcus R., Adams, Lisa C., Bressem, Keno K.
Purpose: To develop and evaluate a deep learning model for multi-organ segmentation of MRI scans. Materials and Methods: The model was trained on 1,200 manually annotated 3D axial MRI scans from the UK Biobank, 221 in-house MRI scans, and 1228 CT sca
Externí odkaz:
http://arxiv.org/abs/2405.06463
Autor:
Guiang, Jonathan, Krutelyov, Slava, Vourliotis, Manos, Gu, Yanxi, Yagil, Avi, Narayanan, Balaji Venkat Sathia, Tadel, Matevz, Chang, Philip, Silva, Mayra, Niendorf, Gavin, Wittich, Peter, Reid, Tres, Elmer, Peter
In this work, we present a study on ways that tracking algorithms can be improved with machine learning (ML). We base this study on the line segment tracking (LST) algorithm that we have designed to be naturally parallelized and vectorized in order t
Externí odkaz:
http://arxiv.org/abs/2403.13166
Autor:
Möller, Hendrik, Graf, Robert, Schmitt, Joachim, Keinert, Benjamin, Atad, Matan, Sekuboyina, Anjany, Streckenbach, Felix, Schön, Hanna, Kofler, Florian, Kroencke, Thomas, Bette, Stefanie, Willich, Stefan, Keil, Thomas, Niendorf, Thoralf, Pischon, Tobias, Endemann, Beate, Menze, Bjoern, Rueckert, Daniel, Kirschke, Jan S.
Purpose. To present SPINEPS, an open-source deep learning approach for semantic and instance segmentation of 14 spinal structures (ten vertebra substructures, intervertebral discs, spinal cord, spinal canal, and sacrum) in whole body T2w MRI. Methods
Externí odkaz:
http://arxiv.org/abs/2402.16368
Autor:
Scheibel, Franziska, Lauhoff, Christian, Krooß, Philipp, Riegg, Stefan, Sommer, Niklas, Koch, David, Opelt, Konrad, Gutte, Heiner, Volkova, Olena, Böhm, Stefan, Niendorf, Thomas, Gutfleisch, Oliver
Ni-Mn-based Heusler alloys like Ni-Mn-Sn show an elastocaloric as well as magnetocaloric effect during the magneto-structural phase transition, making this material interesting for solid-state cooling application. Material processing by additive manu
Externí odkaz:
http://arxiv.org/abs/2304.05383
Publikováno v:
Journal of Materials Research and Technology, Vol 31, Iss , Pp 1044-1053 (2024)
The goal of this study is to investigate the impact of beam deflection pattern characteristics on microstructure and porosity formation during Powder Bed Fusion Electron Beam Melting (PBF-EB/M) processing of Inconel 718. Specifically, the complex int
Externí odkaz:
https://doaj.org/article/d25d0a729b9e45198ad5877460b04c07
Autor:
Pini, Stefano, Perone, Christian S., Ahuja, Aayush, Ferreira, Ana Sofia Rufino, Niendorf, Moritz, Zagoruyko, Sergey
The goal of autonomous vehicles is to navigate public roads safely and comfortably. To enforce safety, traditional planning approaches rely on handcrafted rules to generate trajectories. Machine learning-based systems, on the other hand, scale with d
Externí odkaz:
http://arxiv.org/abs/2211.02131
Autor:
Tschodu, Dimitrij, Lippoldt, Jürgen, Gottheil, Pablo, Wegscheider, Anne-Sophie, Niendorf, Axel, Käs, Josef A.
Cancer prognosis can be regarded as estimating the risk of future outcomes from multiple variables. In prognostic signatures, these variables represent expressions of genes that are summed up to calculate a risk score. However, it is a natural phenom
Externí odkaz:
http://arxiv.org/abs/2211.00905
Autor:
Chang, Philip, Elmer, Peter, Gu, Yanxi, Krutelyov, Vyacheslav, Niendorf, Gavin, Reid, Michael, Narayanan, Balaji Venkat Sathia, Tadel, Matevž, Vourliotis, Emmanouil, Wang, Bei, Wittich, Peter, Yagil, Avraham
Publikováno v:
2022 J. Phys.: Conf. Ser. 2375 012005
The High Luminosity upgrade of the Large Hadron Collider (HL-LHC) will produce particle collisions with up to 200 simultaneous proton-proton interactions. These unprecedented conditions will create a combinatorial complexity for charged-particle trac
Externí odkaz:
http://arxiv.org/abs/2209.13711