Christian Baumgartner is starting an Assistant Professorship at the University of Lucerne, Switzerland

Christian Baumgartner got appointed as Assistant Professor in Health Data Science at the University of Lucerne, Switzerland. While part of the group will be physically moving to Lucerne, Christian will also maintain a position at the University of Tübingen, where the majority of the group remains.

Two papers presented at MICCAI 2024 in Vancouver

Our group presented two papers at this year’s MICCAI in Vancouver. Susu Sun was presenting her work on short-cut learning in medical image classifiers at the main conference. See Right for the Wrong Reason: Can Interpretable ML Techniques Detect Spurious Correlations?

Announcing the MICCAI Learn2Learn Challenge!

We are delighted to announce the MICCAI Learn2Learn challenge and the release of a novel dataset of datasets containing 28 medical classification tasks derived from 17 public datasets. With the L2L challenge, we aim to bring cross-domain few-shot learning (CD-FSL) to the medical imaging domain.

Best poster jury award for Susu Sun at the Bern Interpretable AI Symposium (BIAS)!

Susu Sun presented a preliminiary version of her work on counterfactual explanations for multi-label classifiers at the Bern Interpretable AI Symposium (BIAS) and won the best poster jury award for her short presentation about the work.

Paper on inherently interpretable multi-label classifiers using counterfactuals accepted to MIDL 2023!

Our research on using class-specific counterfactuals to create an inherently interpretable multi-label classifier led by MLMIA lab member Susu Sun has been accepted to the Medical Imaging with Deep Learning (MIDL) conference, which will be held in Nashville, Tennessee this year.

MLMIA team wins MICCAI K2S MR reconstruction and segmentation challenge!

We are delighted to announce that MLMIA lab members Nikolas Morshuis and Paul Fischer won the MICCAI 2022 K2S Challenge in Singapore! The objective of this challenge was to segment knee structures directly from 8x undersampled 3D MR images.

MICCAI 2022 UNSURE workshop successfully held for the 4th time in Singapore

MLMIA group leader Christian Baumgartner has co-organised the MICCAI UNSURE 2022 workshop on uncertainty and safety of machine learning based medical image analysis systems. The workshop was held as satellite event of the main MICCAI conference in Singapore.

New MIDL 2022 short paper on strategies for meta-learning with diverse tasks

Stefano Woerner’s paper on “Strategies for Meta-Learning with Diverse Tasks” got accepted to the MIDL 2022 short paper track. Meta-learning research is typically evaluated on very homogenous toy tasks and it is unclear how directly this technology is applicable to much more diverse medical imaging tasks.

New paper on adversarial robustness of MR reconstruction algorithms

Our paper on “Adversarial Robustness of MR Image Reconstruction Under Realistic Perturbations” first-authored by Nikolas Morshuis got accepted to the MICCAI workshop on Machine Learning for Medical Image Reconstruction (MLMIR) 2022 as an oral presentation.