Meinrad Beer

24 papers Journal 14Unranked 10
YearRankTypeTitle / Venue / Authors
2026 — conf
Abstract: Minimum Data, Maximum Impact - 20 Annotated Samples for Explainable Lung Nodule Classification.
Bildverarbeitung für die Medizin
Luisa Gallée, Catharina Silvia Lisson, Christoph Gerhard Lisson, Daniela Drees, Felix Weig, Daniel Vogele, Meinrad Beer, Michael Götz
2026 — conf
Abstract: Your other Left! Vision-language Models Fail to Understand Relative Positions in Medical Images.
Bildverarbeitung für die Medizin
Daniel Wolf, Heiko Hillenhagen, Billurvan Taskin, Alex Bäuerle, Meinrad Beer, Michael Götz, Timo Ropinski
2025 — conf
Abstract: Evaluating the Explainability of Attributes and Prototypes for a Medical Classification Model.
Bildverarbeitung für die Medizin
Luisa Gallée, Catharina Silvia Lisson, Christoph Gerhard Lisson, Daniela Drees, Felix Weig, Daniel Vogele, Meinrad Beer, Michael Götz
2025 — conf
Abstract: Selective Reduction of CT Data for Self-supervised Pre-training Improves Downstream Classification Performance.
Bildverarbeitung für die Medizin
Daniel Wolf, Tristan Payer, Catharina Silvia Lisson, Christoph Gerhard Lisson, Meinrad Beer, Michael Götz, Timo Ropinski
2025 J jnl
FunnyNodules: A Customizable Medical Dataset Tailored for Evaluating Explainable AI.
CoRR
Luisa Gallée, Yiheng Xiong, Meinrad Beer, Michael Götz
2025 J jnl
Hierarchical Vision Transformer with Prototypes for Interpretable Medical Image Classification.
CoRR
Luisa Gallée, Catharina Silvia Lisson, Meinrad Beer, Michael Götz
2025 — conf
Minimum Data, Maximum Impact: 20 Annotated Samples for Explainable Lung Nodule Classification.
iMIMIC@MICCAI
Luisa Gallée, Catharina Silvia Lisson, Christoph Gerhard Lisson, Daniela Drees, Felix Weig, Daniel Vogele, Meinrad Beer, Michael Götz
2025 J jnl
Minimum Data, Maximum Impact: 20 annotated samples for explainable lung nodule classification.
CoRR
Luisa Gallée, Catharina Silvia Lisson, Christoph Gerhard Lisson, Daniela Drees, Felix Weig, Daniel Vogele, Meinrad Beer, Michael Götz
2025 J jnl
Proto-Caps: interpretable medical image classification using prototype learning and privileged information.
PeerJ Comput. Sci.
Luisa Gallée, Catharina Silvia Lisson, Timo Ropinski, Meinrad Beer, Michael Götz
2025 — conf
Your other Left! Vision-Language Models Fail to Identify Relative Positions in Medical Images.
MICCAI (5)
Daniel Wolf, Heiko Hillenhagen, Billurvan Taskin, Alex Bäuerle, Meinrad Beer, Michael Götz, Timo Ropinski
2025 J jnl
Your other Left! Vision-Language Models Fail to Identify Relative Positions in Medical Images.
CoRR
Daniel Wolf, Heiko Hillenhagen, Billurvan Taskin, Alex Bäuerle, Meinrad Beer, Michael Götz, Timo Ropinski
2024 — conf
Abstract: Interpretable Medical Image Classification Using Prototype Learning and Privileged Information.
Bildverarbeitung für die Medizin
Luisa Gallée, Meinrad Beer, Michael Götz
2024 — conf
Abstract: Self-supervised Pre-training for Dealing with Small Datasets in Deep Learning for Medical Imaging - Evaluation of Contrastive and Masked Autoencoder Methods.
Bildverarbeitung für die Medizin
Daniel Wolf, Tristan Payer, Catharina Silvia Lisson, Christoph Gerhard Lisson, Meinrad Beer, Michael Götz, Timo Ropinski
2024 — conf
Evaluating the Explainability of Attributes and Prototypes for a Medical Classification Model.
xAI (1)
Luisa Gallée, Catharina Silvia Lisson, Christoph Gerhard Lisson, Daniela Drees, Felix Weig, Daniel Vogele, Meinrad Beer, Michael Götz
2024 J jnl
Evaluating the Explainability of Attributes and Prototypes for a Medical Classification Model.
CoRR
Luisa Gallée, Catharina Silvia Lisson, Christoph Gerhard Lisson, Daniela Drees, Felix Weig, Daniel Vogele, Meinrad Beer, Michael Götz
2024 J jnl
Less is More: Selective Reduction of CT Data for Self-Supervised Pre-Training of Deep Learning Models with Contrastive Learning Improves Downstream Classification Performance.
CoRR
Daniel Wolf, Tristan Payer, Catharina Silvia Lisson, Christoph Gerhard Lisson, Meinrad Beer, Michael Götz, Timo Ropinski
2024 J jnl
Less is More: Selective reduction of CT data for self-supervised pre-training of deep learning models with contrastive learning improves downstream classification performance.
Comput. Biol. Medicine
Daniel Wolf, Tristan Payer, Catharina Silvia Lisson, Christoph Gerhard Lisson, Meinrad Beer, Michael Götz, Timo Ropinski
2024 J jnl
Non-Hodgkin's lymphoma classification using 3D radiomics machine learning models for precision imaging in oncology.
BMC Bioinform.
Christoph Gerhard Lisson, Michael Götz, Daniel Wolf, Sabitha Manoj, Luisa Gallée, Stefan A. Schmidt, Eugen Tausch, Christof Schneider, Stephan Stilgenbauer, Ambros J. Beer, Meinrad Beer, Nico Sollmann, Catharina Silvia Lisson
2023 J jnl
Dealing with Small Datasets for Deep Learning in Medical Imaging: An Evaluation of Self-Supervised Pre-Training on CT Scans Comparing Contrastive and Masked Autoencoder Methods for Convolutional Models.
CoRR
Daniel Wolf, Tristan Payer, Catharina Silvia Lisson, Christoph Gerhard Lisson, Meinrad Beer, Timo Ropinski, Michael Götz
2023 — conf
Interpretable Medical Image Classification Using Prototype Learning and Privileged Information.
MICCAI (2)
Luisa Gallée, Meinrad Beer, Michael Götz
2023 J jnl
Interpretable Medical Image Classification using Prototype Learning and Privileged Information.
CoRR
Luisa Gallée, Meinrad Beer, Michael Götz
2023 J jnl
Unsupervised domain adaptation for the detection of cardiomegaly in cross-domain chest X-ray images.
Frontiers Artif. Intell.
Patrick Thiam, Ludwig Lausser, Christopher Kloth, Daniel Blaich, Andreas Liebold, Meinrad Beer, Hans A. Kestler
2021 J jnl
Improving COVID-19 CXR Detection with Synthetic Data Augmentation.
CoRR
Daniel Schaudt, Christopher Kloth, Christian Spaete, Andreas Hinteregger, Meinrad Beer, Reinhold von Schwerin
2019 J jnl
Potential role of CT-textural features for differentiation between viral interstitial pneumonias, pneumocystis jirovecii pneumonia and diffuse alveolar hemorrhage in early stages of disease: a proof of principle.
BMC Medical Imaging
Christopher Kloth, Wolfgang Maximilian Thaiss, Robert Beck, Michael Haap, Jan Fritz, Meinrad Beer, Marius Horger