Zobrazeno 1 - 10
of 1 321
pro vyhledávání: '"Schlemmer, Heinz Peter"'
Autor:
Borkowetz, Angelika, Blana, Andreas, Böhmer, Dirk, Cash, Hannes, Ehrmann, Udo, Franiel, Tobias, Henkel, Thomas-Oliver, Höcht, Stefan, Kristiansen, Glen, Machtens, Stefan, Niehoff, Peter, Penzkofer, Tobias, Pinkawa, Michael, Radtke, Jan Philipp, Roth, Wilried, Witzsch, Ullrich, Ganzer, Roman, Schlemmer, Heinz Peter, Grimm, Marc-Oliver, Hakenberg, Oliver W., Schostak, Martin
Background: Focal therapy (FT) is an option to treat localized prostate cancer (PCa) and preserve healthy prostate tissue in order to reduce known side effects from primary whole-gland treatment. The available FT modalities are manifold. Until now, n
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A88901
https://tud.qucosa.de/api/qucosa%3A88901/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A88901/attachment/ATT-0/
Autor:
Deike-Hofmann, Katerina, Dancs, Dorottya, Paech, Daniel, Schlemmer, Heinz-Peter, Maier-Hein, Klaus, Bäumer, Philipp, Radbruch, Alexander, Götz, Michael
Publikováno v:
Investigative Radiology 56(5):p 320-327, May 2021
Materials and methods: First, a dual-time approach was assessed, for which the CNN was provided sequences of the MRI that initially depicted new MM (diagnosis MRI) as well as of a prediagnosis MRI: inclusion of only contrast-enhanced T1-weighted imag
Externí odkaz:
http://arxiv.org/abs/2403.08280
Autor:
Kovacs, Balint, Netzer, Nils, Baumgartner, Michael, Eith, Carolin, Bounias, Dimitrios, Meinzer, Clara, Jaeger, Paul F., Zhang, Kevin S., Floca, Ralf, Schrader, Adrian, Isensee, Fabian, Gnirs, Regula, Goertz, Magdalena, Schuetz, Viktoria, Stenzinger, Albrecht, Hohenfellner, Markus, Schlemmer, Heinz-Peter, Wolf, Ivo, Bonekamp, David, Maier-Hein, Klaus H.
Data augmentation (DA) is a key factor in medical image analysis, such as in prostate cancer (PCa) detection on magnetic resonance images. State-of-the-art computer-aided diagnosis systems still rely on simplistic spatial transformations to preserve
Externí odkaz:
http://arxiv.org/abs/2309.03652
With the rise in importance of personalized medicine, we trained personalized neural networks to detect tumor progression in longitudinal datasets. The model was evaluated on two datasets with a total of 64 scans from 32 patients diagnosed with gliob
Externí odkaz:
http://arxiv.org/abs/2210.14228
Autor:
Sawall, Stefan, Maier, Joscha, Sen, Sinan, Gehrig, Holger, Kim, Ti-Sun, Schlemmer, Heinz-Peter, Schönberg, Stefan O., Kachelrieß, Marc, Rütters, Maurice
Publikováno v:
In Journal of Dentistry March 2024 142
Autor:
Boschheidgen, Matthias, Albers, Peter, Schlemmer, Heinz-Peter, Hellms, Susanne, Bonekamp, David, Sauter, Andreas, Hadaschik, Boris, Krilaviciute, Agne, Radtke, Jan Philipp, Seibold, Petra, Lakes, Jale, Arsov, Christian, Gschwend, Jürgen E., Herkommer, Kathleen, Makowski, Marcus, Kuczyk, Markus A., Wacker, Frank, Harke, Nina, Debus, Jürgen, Körber, Stefan A., Benner, Axel, Kristiansen, Glen, Giesel, Frederik L., Antoch, Gerald, Kaaks, Rudolf, Becker, Nikolaus, Schimmöller, Lars
Publikováno v:
In European Urology February 2024 85(2):105-111
Autor:
Krilaviciute, Agne, Kaaks, Rudolf, Seibold, Petra, de Vrieze, Maxime, Lakes, Jale, Radtke, Jan Philipp, Kuczyk, Markus, Harke, Nina N., Debus, Jürgen, Fink, Christoph A., Herkommer, Kathleen, Gschwend, Jürgen E., Meissner, Valentin H., Benner, Axel, Kristiansen, Glen, Hadaschik, Boris, Arsov, Christian, Schimmöller, Lars, Antoch, Gerald, Giesel, Frederik L., Makowski, Marcus, Wacker, Frank, Schlemmer, Heinz-Peter, Becker, Nikolaus, Albers, Peter
Publikováno v:
In European Urology April 2024
Autor:
Zhang, Ke, Triphan, Simon M.F., Wielpütz, Mark O., Ziener, Christian H., Ladd, Mark E., Schlemmer, Heinz-Peter, Kauczor, Hans-Ulrich, Kurz, Felix T., Sedlaczek, Oliver
Publikováno v:
In Magnetic Resonance Imaging January 2024 105:75-81
Autor:
Seibold, Constantin, Fink, Matthias A., Goos, Charlotte, Kauczor, Hans-Ulrich, Schlemmer, Heinz-Peter, Stiefelhagen, Rainer, Kleesiek, Jens
Detector-based spectral computed tomography is a recent dual-energy CT (DECT) technology that offers the possibility of obtaining spectral information. From this spectral data, different types of images can be derived, amongst others virtual monoener
Externí odkaz:
http://arxiv.org/abs/2102.01445
The lack of fine-grained annotations hinders the deployment of automated diagnosis systems, which require human-interpretable justification for their decision process. In this paper, we address the problem of weakly supervised identification and loca
Externí odkaz:
http://arxiv.org/abs/2010.00127