no code implementations • 15 Apr 2024 • Luisa Gallée, Catharina Silvia Lisson, Christoph Gerhard Lisson, Daniela Drees, Felix Weig, Daniel Vogele, Meinrad Beer, Michael Götz
We can conclude that attribute scores and visual prototypes enhance confidence in the model.
no code implementations • 13 Mar 2024 • Katerina Deike-Hofmann, Dorottya Dancs, Daniel Paech, Heinz-Peter Schlemmer, Klaus Maier-Hein, Philipp Bäumer, Alexander Radbruch, Michael Götz
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 images (CNNdual_ce) was compared with inclusion of also the native T1-weighted images, T2-weighted images, and FLAIR sequences of both time points (CNNdual_all). Second, results were compared with the corresponding single time approaches, in which the CNN was provided exclusively the respective sequences of the diagnosis MRI. Casewise diagnostic performance parameters were calculated from 5-fold cross-validation.
no code implementations • 12 Mar 2024 • Michael Götz, Christian Weber, Franciszek Binczyk, Joanna Polanska, Rafal Tarnawski, Barbara Bobek-Billewicz, Ullrich Köthe, Jens Kleesiek, Bram Stieltjes, Klaus H. Maier-Hein
We propose a new method that employs transfer learning techniques to effectively correct sampling selection errors introduced by sparse annotations during supervised learning for automated tumor segmentation.
no code implementations • 12 Mar 2024 • Michael Götz, Christian Weber, Christoph Kolb, Klaus Maier-Hein
In machine learning larger databases are usually associated with higher classification accuracy due to better generalization.
no code implementations • 7 Nov 2023 • Leonard Sasse, Eliana Nicolaisen-Sobesky, Juergen Dukart, Simon B. Eickhoff, Michael Götz, Sami Hamdan, Vera Komeyer, Abhijit Kulkarni, Juha Lahnakoski, Bradley C. Love, Federico Raimondo, Kaustubh R. Patil
Machine learning (ML) provides powerful tools for predictive modeling.
1 code implementation • 12 Aug 2023 • Daniel Wolf, Tristan Payer, Catharina Silvia Lisson, Christoph Gerhard Lisson, Meinrad Beer, Michael Götz, Timo Ropinski
Based on our results, we propose the SparK pre-training for medical imaging tasks with only small annotated datasets.