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ORCIDJohanna P. Müller
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2020 – today
- 2024
[c11]Mischa Dombrowski, Hadrien Reynaud, Johanna P. Müller, Matthew Baugh, Bernhard Kainz
:
Trade-Offs in Fine-Tuned Diffusion Models between Accuracy and Interpretability. AAAI 2024: 21037-21045- [c10]Marietta Stegmaier, Johanna P. Müller, Christian Schröder, Thomas G. Day, Michela Cuomo, Oliver Dewald, Sven Dittrich, Bernhard Kainz:
Automatic Segmentation of Lymphatic Perfusion in Patients with Congenital Single Ventricle Defects. Bildverarbeitung für die Medizin 2024: 255-260 - [c9]Matthew Baugh, Hadrien Reynaud, Sergio Naval Marimont, Sarah Cechnicka, Johanna P. Müller, Giacomo Tarroni, Bernhard Kainz:
Image-Conditioned Diffusion Models for Medical Anomaly Detection. UNSURE@MICCAI 2024: 117-127 - [c8]Franciskus Xaverius Erick, Mina Rezaei, Johanna Paula Müller, Bernhard Kainz:
Uncertainty-Aware Vision Transformers for Medical Image Analysis. UNSURE@MICCAI 2024: 171-180 - [c7]Johanna P. Müller, Bernhard Kainz:
Resource-Efficient Medical Image Analysis with Self-adapting Forward-Forward Networks. MLMI@MICCAI (2) 2024: 180-190 - [i9]Johanna P. Müller, Bernhard Kainz:
Resource-efficient Medical Image Analysis with Self-adapting Forward-Forward Networks. CoRR abs/2406.14038 (2024) - 2023
- [c6]Constantin Jehn, Johanna P. Müller, Bernhard Kainz:
Learnable Slice-to-volume Reconstruction for Motion Compensation in Fetal Magnetic Resonance Imaging. Bildverarbeitung für die Medizin 2023: 25-31 - [c5]Glejdis Shkëmbi, Johanna P. Müller, Zhe Li, Katharina Breininger, Peter J. Schüffler, Bernhard Kainz:
Whole Slide Multiple Instance Learning for Predicting Axillary Lymph Node Metastasis. DEMI@MICCAI 2023: 11-20 - [c4]Matthew Baugh, Jeremy Tan, Johanna P. Müller, Mischa Dombrowski, James Batten, Bernhard Kainz:
Many Tasks Make Light Work: Learning to Localise Medical Anomalies from Multiple Synthetic Tasks. MICCAI (1) 2023: 162-172 - [c3]Johanna P. Müller, Matthew Baugh, Jeremy Tan, Mischa Dombrowski, Bernhard Kainz:
Confidence-Aware and Self-supervised Image Anomaly Localisation. UNSURE@MICCAI 2023: 177-187 - [e1]Bernhard Kainz, J. Alison Noble, Julia A. Schnabel, Bishesh Khanal, Johanna P. Müller, Thomas G. Day:
Simplifying Medical Ultrasound - 4th International Workshop, ASMUS 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings. Lecture Notes in Computer Science 14337, Springer 2023, ISBN 978-3-031-44520-0 [contents] - [i8]Johanna P. Müller, Matthew Baugh, Jeremy Tan, Mischa Dombrowski, Bernhard Kainz:
Confidence-Aware and Self-Supervised Image Anomaly Localisation. CoRR abs/2303.13227 (2023) - [i7]Mischa Dombrowski, Hadrien Reynaud, Johanna P. Müller, Matthew Baugh, Bernhard Kainz:
Pay Attention: Accuracy Versus Interpretability Trade-off in Fine-tuned Diffusion Models. CoRR abs/2303.17908 (2023) - [i6]Matthew Baugh, James Batten, Johanna P. Müller, Bernhard Kainz:
Zero-Shot Anomaly Detection with Pre-trained Segmentation Models. CoRR abs/2306.09269 (2023) - [i5]Matthew Baugh, Jeremy Tan, Johanna P. Müller, Mischa Dombrowski, James Batten, Bernhard Kainz:
Many tasks make light work: Learning to localise medical anomalies from multiple synthetic tasks. CoRR abs/2307.00899 (2023) - [i4]Glejdis Shkëmbi, Johanna P. Müller, Zhe Li, Katharina Breininger, Peter J. Schüffler, Bernhard Kainz:
Whole Slide Multiple Instance Learning for Predicting Axillary Lymph Node Metastasis. CoRR abs/2310.04187 (2023) - [i3]Franciskus Xaverius Erick, Mina Rezaei, Johanna Paula Müller, Bernhard Kainz:
Stochastic Vision Transformers with Wasserstein Distance-Aware Attention. CoRR abs/2311.18645 (2023) - 2022
- [c2]Matthew Baugh, Jeremy Tan, Athanasios Vlontzos, Johanna P. Müller, Bernhard Kainz:
nnOOD: A Framework for Benchmarking Self-supervised Anomaly Localisation Methods. UNSURE@MICCAI 2022: 103-112 - [c1]Clara Lebbos, Jen Barcroft, Jeremy Tan, Johanna P. Müller, Matthew Baugh, Athanasios Vlontzos, Srdjan Saso, Bernhard Kainz:
Adnexal Mass Segmentation with Ultrasound Data Synthesis. ASMUS@MICCAI 2022: 106-116 - [i2]Matthew Baugh, Jeremy Tan, Athanasios Vlontzos, Johanna P. Müller, Bernhard Kainz:
nnOOD: A Framework for Benchmarking Self-supervised Anomaly Localisation Methods. CoRR abs/2209.01124 (2022) - [i1]Clara Lebbos, Jen Barcroft, Jeremy Tan, Johanna P. Müller, Matthew Baugh, Athanasios Vlontzos, Srdjan Saso, Bernhard Kainz:
Adnexal Mass Segmentation with Ultrasound Data Synthesis. CoRR abs/2209.12305 (2022)
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