Zobrazeno 1 - 10
of 5 652
pro vyhledávání: '"Niendorf"'
Autor:
Ahmad-Nejad Parviz, Bauersfeld Walter, Baum Hannsjörg, Behre Hermann M., Burkhardt Ralph, Cassens Uwe, Ceglarek Uta, Christmann Martin, Cremers Jann-Frederik, Diedrich Sabine, Döring Sybille, Gässler Norbert, Haase Gerhard, Haselmann Verena, Hofmann Jörg, Holdenrieder Stefan, Hübner Marc P., Hunfeld Klaus-Peter, Huzly Daniela, Kohlschmidt Nicolai, Köhn Frank-Michael, Kornak Uwe, Kreuzer Karl-Anton, Kunz Jürgen, Lackner Karl, Niendorf Sandra, Peetz Dirk, Petersmann Astrid, Pick Karl-Heinz, Rabenau Holger F., Sack Ulrich, Schächterle Carolin, Schaffer Sven, Schneider Sven, Schuppe Hans Christian, Seidl Christian, Tönnies Holger, Uhr Manfred, Ullmann Kerstin, Volkmann Martin, Weiss Nathalie, Wellinghausen Nele, Zeichhardt Heinz, App Urban, Auch Dieter, Barion Jürgen, Hiester Philipp, Kaiser Patricia, Klouche Mariam, Kolanowski-Albrecht Mandy, Macdonald Rainer, Malms-Fleschenberg Waltraut, Michelsen Andrea, Schellenberg Ingo, Schiffner Roman, Spannagl Michael, Stosch Rainer, van Diepen Laura, Wettmarshausen Sascha, Ziesing Stefan, Knabbe Cornelius, Schoerner Christoph, Kliesch Sabine, Nauck Matthias
Publikováno v:
Journal of Laboratory Medicine, Vol 48, Iss 6, Pp 263-306 (2024)
Externí odkaz:
https://doaj.org/article/53fd4752e341447c9c0398917df581be
Autor:
Chang Philip, Elmer Peter, Gu Yanxi, Krutelyov Vyacheslav, Niendorf Gavin, Reid Michael, Venkat Sathia Narayanan Balaji, Tadel Matevz, Vourliotis Emmanouli, Wang Bei, Wittich Peter, Yagil Avraham
Publikováno v:
EPJ Web of Conferences, Vol 295, p 02019 (2024)
The Large Hadron Collider (LHC) will be upgraded to Highluminosity LHC, increasing the number of simultaneous proton-proton collisions (pileup, PU) by several-folds. The harsher PU conditions lead to exponentially increasing combinatorics in charged
Externí odkaz:
https://doaj.org/article/a8defd22a8754a2486a587cb75863357
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:
Oberacker Eva, Kuehne Andre, Nadobny Jacek, Zschaeck Sebastian, Weihrauch Mirko, Waiczies Helmar, Ghadjar Pirus, Wust Peter, Niendorf Thoralf, Winter Lukas
Publikováno v:
Current Directions in Biomedical Engineering, Vol 3, Iss 2, Pp 473-477 (2017)
Glioblastoma multiforme is the most frequent and most aggressive malignant brain tumor with de facto no long term curation by the use of current multimodal therapeutic approaches. The efficacy of brachytherapy and enhancing interstitial hyperthermia
Externí odkaz:
https://doaj.org/article/2bc0dd20ba0741fba8b91eaa7a478450
Publikováno v:
Current Directions in Biomedical Engineering, Vol 3, Iss 2, Pp 433-436 (2017)
Mapping the effective transverse relaxation time T2* represents an emerging MRI tool for non-invasive myocardial tissue characterization and holds the promise to provide means for assessing myocardial (patho)physiology in vivo. This work takes advant
Externí odkaz:
https://doaj.org/article/b663061cce2a42a58824bf32a2dff528