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4 papers · 1 filter
Evaluating the Explainability of Attributes and Prototypes for a Medical Classification Model
Luisa Gallée, Catharina Silvia Lisson, Christoph Gerhard Lisson +5
Due to the sensitive nature of medicine, it is particularly important and highly demanded that AI methods are explainable. This need has been recognised and there is great research…
Interpretable Medical Image Classification using Prototype Learning and Privileged Information
Luisa Gallee, Meinrad Beer, Michael Goetz
Interpretability is often an essential requirement in medical imaging. Advanced deep learning methods are required to address this need for explainability and high performance. In…
Self-Supervised Pre-Training with Contrastive and Masked Autoencoder Methods for Dealing with Small Datasets in Deep Learning for Medical Imaging
Daniel Wolf, Tristan Payer, Catharina Silvia Lisson +4
Deep learning in medical imaging has the potential to minimize the risk of diagnostic errors, reduce radiologist workload, and accelerate diagnosis. Training such deep learning mod…
Algorithm guided outlining of 105 pancreatic cancer liver metastases in Ultrasound
Alexander Hann, Lucas Bettac, Mark M. Haenle +6
Manual segmentation of hepatic metastases in ultrasound images acquired from patients suffering from pancreatic cancer is common practice. Semiautomatic measurements promising assi…