1 code implementation • 29 Sep 2023 • Yixing Huang, Christoph Bert, Ahmed Gomaa, Rainer Fietkau, Andreas Maier, Florian Putz
Incremental transfer learning, which combines peer-to-peer federated learning and domain incremental learning, can overcome the data privacy issue and meanwhile preserve model performance by using continual learning techniques.
no code implementations • 26 Jun 2023 • Amr Hagag, Ahmed Gomaa, Dominik Kornek, Andreas Maier, Rainer Fietkau, Christoph Bert, Florian Putz, Yixing Huang
The StyleGAN2 is then used to embed the photographs to its highly expressive latent space.
1 code implementation • 24 Apr 2023 • Yixing Huang, Ahmed Gomaa, Sabine Semrau, Marlen Haderlein, Sebastian Lettmaier, Thomas Weissmann, Johanna Grigo, Hassen Ben Tkhayat, Benjamin Frey, Udo S. Gaipl, Luitpold V. Distel, Andreas Maier, Rainer Fietkau, Christoph Bert, Florian Putz
The potential of large language models in medicine for education and decision making purposes has been demonstrated as they achieve decent scores on medical exams such as the United States Medical Licensing Exam (USMLE) and the MedQA exam.
no code implementations • 16 Apr 2023 • Florian Putz, Johanna Grigo, Thomas Weissmann, Philipp Schubert, Daniel Hoefler, Ahmed Gomaa, Hassen Ben Tkhayat, Amr Hagag, Sebastian Lettmaier, Benjamin Frey, Udo S. Gaipl, Luitpold V. Distel, Sabine Semrau, Christoph Bert, Rainer Fietkau, Yixing Huang
Conclusions: The Segment Anything foundation model, while trained on photos, can achieve high zero-shot accuracy for glioma brain tumor segmentation on MRI slices.
no code implementations • 17 Feb 2023 • Philipp Sommer, Yixing Huang, Christoph Bert, Andreas Maier, Manuel Schmidt, Arnd Dörfler, Rainer Fietkau, Florian Putz
We hypothesized that using radiomics and machine learning (ML), metastases at high risk for subsequent progression could be identified during follow-up prior to the onset of significant tumor growth, enabling personalized follow-up intervals and early selection for salvage treatment.
no code implementations • 28 Aug 2022 • Thomas Weissmann, Yixing Huang, Stefan Fischer, Johannes Roesch, Sina Mansoorian, Horacio Ayala Gaona, Antoniu-Oreste Gostian, Markus Hecht, Sebastian Lettmaier, Lisa Deloch, Benjamin Frey, Udo S. Gaipl, Luitpold V. Distel, Andreas Maier, Heinrich Iro, Sabine Semrau, Christoph Bert, Rainer Fietkau, Florian Putz
For a subgroup of 10 cases, intraobserver variability was compared to the average DL autosegmentation accuracy on the original and recontoured set of expert segmentations.
no code implementations • 26 Apr 2022 • Yixing Huang, Christoph Bert, Stefan Fischer, Manuel Schmidt, Arnd Dörfler, Andreas Maier, Rainer Fietkau, Florian Putz
With iterative continual learning (i. e., the shared model revisits each center multiple times during training), the sensitivity is further improved to 0. 914, which is identical to the sensitivity using mixed data for training.
no code implementations • 13 Feb 2022 • Yixing Huang, Andreas Maier, Fuxin Fan, Björn Kreher, Xiaolin Huang, Rainer Fietkau, Christoph Bert, Florian Putz
The complementary view setting provides a practical way to identify perspectively deformed structures by assessing the deviation between the two views.
1 code implementation • 22 Dec 2021 • Yixing Huang, Christoph Bert, Philipp Sommer, Benjamin Frey, Udo Gaipl, Luitpold V. Distel, Thomas Weissmann, Michael Uder, Manuel A. Schmidt, Arnd Dörfler, Andreas Maier, Rainer Fietkau, Florian Putz
To improve brain metastasis detection performance with deep learning, a custom detection loss called volume-level sensitivity-specificity (VSS) is proposed, which rates individual metastasis detection sensitivity and specificity in (sub-)volume levels.