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. - Daniel Wolf; Tristan Payer; Catharina Silvia Lisson; Christoph Gerhard Lisson; Meinrad Beer; Timo Ropinski; Michael Götz (CoRR, 2023)

Abstract: Self-supervised Pre-training for Dealing with Small Datasets in Deep Learning for Medical Imaging - Evaluation of Contrastive and Masked Autoencoder Methods. - Daniel Wolf; Tristan Payer; Catharina Silvia Lisson; Christoph Gerhard Lisson; Meinrad Beer; Michael Götz; Timo Ropinski (Bildverarbeitung für die Medizin, 2024)

Evaluating the Explainability of Attributes and Prototypes for a Medical Classification Model. - Luisa Gallée; Catharina Silvia Lisson; Christoph Gerhard Lisson; Daniela Drees; Felix Weig; Daniel Vogele; Meinrad Beer; Michael Götz (xAI (1), 2024)

Less is More: Selective reduction of CT data for self-supervised pre-training of deep learning models with contrastive learning improves downstream classification performance. - Daniel Wolf; Tristan Payer; Catharina Silvia Lisson; Christoph Gerhard Lisson; Meinrad Beer; Michael Götz; Timo Ropinski (Comput. Biol. Medicine, 2024)

Abstract: Evaluating the Explainability of Attributes and Prototypes for a Medical Classification Model. - Luisa Gallée; Catharina Silvia Lisson; Christoph Gerhard Lisson; Daniela Drees; Felix Weig; Daniel Vogele; Meinrad Beer; Michael Götz (Bildverarbeitung für die Medizin, 2025)

Abstract: Selective Reduction of CT Data for Self-supervised Pre-training Improves Downstream Classification Performance. - Daniel Wolf; Tristan Payer; Catharina Silvia Lisson; Christoph Gerhard Lisson; Meinrad Beer; Michael Götz; Timo Ropinski (Bildverarbeitung für die Medizin, 2025)

Minimum Data, Maximum Impact: 20 annotated samples for explainable lung nodule classification. - Luisa Gallée; Catharina Silvia Lisson; Christoph Gerhard Lisson; Daniela Drees; Felix Weig; Daniel Vogele; Meinrad Beer; Michael Götz (CoRR, 2025)