Zobrazeno 1 - 10
of 17 997
pro vyhledávání: '"Niendorf, A."'
Publikováno v:
Music Trades. Aug2017, Vol. 165 Issue 7, p34-38. 4p.
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
Publikováno v:
Music Trades. Jan2018, Vol. 165 Issue 12, p44-46. 2p.
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:
Grabowski, M.
Publikováno v:
Archäologie in Deutschland, 2009 Nov 01(6), 58-58.
Externí odkaz:
https://www.jstor.org/stable/26318948
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:
Ralph Tuchtenhagen
Publikováno v:
Historische Zeitschrift. 316:475-477
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c871e3c2672575d28d2ce772a59ac1d3
https://doi.org/10.1515/hzhz-2023-1096
https://doi.org/10.1515/hzhz-2023-1096