Johanna P. Müller

According to our database, Johanna P. Müller authored at least 14 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Resource-Efficient Medical Image Analysis with Self-adapting Forward-Forward Networks.

Johanna P. Müller, Bernhard Kainz

Proceedings of the Machine Learning in Medical Imaging - 15th International Workshop, 2024

Uncertainty-Aware Vision Transformers for Medical Image Analysis.

Franciskus Xaverius Erick, Mina Rezaei, Johanna Paula Müller, Bernhard Kainz

Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2024

Image-Conditioned Diffusion Models for Medical Anomaly Detection.

Matthew Baugh, Hadrien Reynaud, Sergio Naval Marimont, Sarah Cechnicka, Johanna P. Müller, Giacomo Tarroni, Bernhard Kainz

Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2024

Automatic Segmentation of Lymphatic Perfusion in Patients with Congenital Single Ventricle Defects.

Marietta Stegmaier, Johanna P. Müller, Christian Schröder, Thomas G. Day, Michela Cuomo, Oliver Dewald, Sven Dittrich, Bernhard Kainz

Proceedings of the Bildverarbeitung für die Medizin 2024, 2024

Trade-Offs in Fine-Tuned Diffusion Models between Accuracy and Interpretability.

Mischa Dombrowski, Hadrien Reynaud, Johanna P. Müller, Matthew Baugh, Bernhard Kainz

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Stochastic Vision Transformers with Wasserstein Distance-Aware Attention.

Franciskus Xaverius Erick, Mina Rezaei, Johanna Paula Müller, Bernhard Kainz

CoRR, 2023

Zero-Shot Anomaly Detection with Pre-trained Segmentation Models.

Matthew Baugh, James Batten, Johanna P. Müller, Bernhard Kainz

CoRR, 2023

Pay Attention: Accuracy Versus Interpretability Trade-off in Fine-tuned Diffusion Models.

Mischa Dombrowski, Hadrien Reynaud, Johanna P. Müller, Matthew Baugh, Bernhard Kainz

CoRR, 2023

Whole Slide Multiple Instance Learning for Predicting Axillary Lymph Node Metastasis.

Glejdis Shkëmbi, Johanna P. Müller, Zhe Li, Katharina Breininger, Peter J. Schüffler, Bernhard Kainz

Proceedings of the Data Engineering in Medical Imaging - First MICCAI Workshop, 2023

Confidence-Aware and Self-supervised Image Anomaly Localisation.

Johanna P. Müller, Matthew Baugh, Jeremy Tan, Mischa Dombrowski, Bernhard Kainz

Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2023

Many Tasks Make Light Work: Learning to Localise Medical Anomalies from Multiple Synthetic Tasks.

Matthew Baugh, Jeremy Tan, Johanna P. Müller, Mischa Dombrowski, James Batten, Bernhard Kainz

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Learnable Slice-to-volume Reconstruction for Motion Compensation in Fetal Magnetic Resonance Imaging.

Constantin Jehn, Johanna P. Müller, Bernhard Kainz

Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

2022

Adnexal Mass Segmentation with Ultrasound Data Synthesis.

Clara Lebbos, Jen Barcroft, Jeremy Tan, Johanna P. Müller, Matthew Baugh, Athanasios Vlontzos, Srdjan Saso, Bernhard Kainz

Proceedings of the Simplifying Medical Ultrasound - Third International Workshop, 2022

nnOOD: A Framework for Benchmarking Self-supervised Anomaly Localisation Methods.

Matthew Baugh, Jeremy Tan, Athanasios Vlontzos, Johanna P. Müller, Bernhard Kainz

Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2022