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Lisa M. Koch
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- affiliation: University of Tübingen, Germany
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2020 – today
- 2024
- [j5]Lisa M. Koch
, Christian F. Baumgartner
Distribution shift detection for the postmarket surveillance of medical AI algorithms: a retrospective simulation study. npj Digit. Medicine 7(1) (2024) - [c16]Anna M. Wundram, Paul Fischer, Michael Mühlebach, Lisa M. Koch, Christian F. Baumgartner:
Conformal Performance Range Prediction for Segmentation Output Quality Control. UNSURE@MICCAI 2024: 81-91 - [c15]Julius Gervelmeyer, Sarah Müller, Kerol Djoumessi, David Merle, Simon J. Clark, Lisa M. Koch, Philipp Berens:
Interpretable-by-Design Deep Survival Analysis for Disease Progression Modeling. MICCAI (10) 2024: 502-512 - [c14]Kerol Djoumessi, Bubacarr Bah, Laura Kühlewein, Philipp Berens
This Actually Looks Like that: Proto-BagNets for Local and Global Interpretability-by-Design. MICCAI (10) 2024: 718-728 - [c13]Sarah Müller, Louisa Fay, Lisa M. Koch, Sergios Gatidis, Thomas Küstner, Philipp Berens:
Benchmarking Dependence Measures to Prevent Shortcut Learning in Medical Imaging. MLMI@MICCAI (2) 2024: 53-62 - [e2]Lisa M. Koch
Domain Adaptation and Representation Transfer - 5th MICCAI Workshop, DART 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings. Lecture Notes in Computer Science 14293, Springer 2024, ISBN 978-3-031-45856-9 [contents] - [i17]Sarah Müller, Lisa M. Koch, Hendrik P. A. Lensch, Philipp Berens:
Disentangling representations of retinal images with generative models. CoRR abs/2402.19186 (2024) - [i16]Susu Sun, Stefano Woerner, Andreas K. Maier, Lisa M. Koch, Christian F. Baumgartner:
Attri-Net: A Globally and Locally Inherently Interpretable Model for Multi-Label Classification Using Class-Specific Counterfactuals. CoRR abs/2406.05477 (2024) - [i15]Jeremiah Fadugba, Patrick Köhler, Lisa M. Koch, Petru Manescu, Philipp Berens:
Benchmarking Retinal Blood Vessel Segmentation Models for Cross-Dataset and Cross-Disease Generalization. CoRR abs/2406.14994 (2024) - [i14]Kerol Djoumessi, Bubacarr Bah, Laura Kühlewein, Philipp Berens, Lisa M. Koch:
This actually looks like that: Proto-BagNets for local and global interpretability-by-design. CoRR abs/2406.15168 (2024) - [i13]Anna M. Wundram, Paul Fischer, Michael Muehlebach, Lisa M. Koch, Christian F. Baumgartner:
Conformal Performance Range Prediction for Segmentation Output Quality Control. CoRR abs/2407.13307 (2024) - [i12]Sarah Müller, Louisa Fay, Lisa M. Koch, Sergios Gatidis, Thomas Küstner, Philipp Berens:
Benchmarking Dependence Measures to Prevent Shortcut Learning in Medical Imaging. CoRR abs/2407.18792 (2024) - 2023
- [c12]Susu Sun, Lisa M. Koch
Right for the Wrong Reason: Can Interpretable ML Techniques Detect Spurious Correlations? MICCAI (2) 2023: 425-434 - [c11]Kerol R. Djoumessi Donteu, Indu Ilanchezian, Laura Kühlewein, Hanna Faber, Christian F. Baumgartner, Bubacarr Bah, Philipp Berens, Lisa M. Koch
Sparse Activations for Interpretable Disease Grading. MIDL 2023: 1-17 - [c10]Susu Sun, Stefano Woerner, Andreas K. Maier, Lisa M. Koch, Christian F. Baumgartner:
Inherently Interpretable Multi-Label Classification Using Class-Specific Counterfactuals. MIDL 2023: 937-956 - [i11]Susu Sun, Stefano Woerner, Andreas Maier, Lisa M. Koch
Inherently Interpretable Multi-Label Classification Using Class-Specific Counterfactuals. CoRR abs/2303.00500 (2023) - [i10]Lisa M. Koch
Deep Hypothesis Tests Detect Clinically Relevant Subgroup Shifts in Medical Images. CoRR abs/2303.04862 (2023) - [i9]Susu Sun, Lisa M. Koch, Christian F. Baumgartner
Right for the Wrong Reason: Can Interpretable ML Techniques Detect Spurious Correlations? CoRR abs/2307.12344 (2023) - [i8]Indu Ilanchezian, Valentyn Boreiko, Laura Kühlewein, Ziwei Huang, Murat Seçkin Ayhan, Matthias Hein, Lisa M. Koch
Generating Realistic Counterfactuals for Retinal Fundus and OCT Images using Diffusion Models. CoRR abs/2311.11629 (2023) - 2022
- [c9]Valentyn Boreiko, Indu Ilanchezian, Murat Seçkin Ayhan, Sarah Müller, Lisa M. Koch
Visual Explanations for the Detection of Diabetic Retinopathy from Retinal Fundus Images. MICCAI (2) 2022: 539-549 - [c8]Lisa M. Koch, Christian M. Schürch, Arthur Gretton, Philipp Berens:
Hidden in Plain Sight: Subgroup Shifts Escape OOD Detection. MIDL 2022: 726-740 - [e1]Konstantinos Kamnitsas
Domain Adaptation and Representation Transfer - 4th MICCAI Workshop, DART 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings. Lecture Notes in Computer Science 13542, Springer 2022, ISBN 978-3-031-16851-2 [contents]
2010 – 2019
- 2018
- [j4]Lisa M. Koch
Multi-Atlas Segmentation Using Partially Annotated Data: Methods and Annotation Strategies. IEEE Trans. Pattern Anal. Mach. Intell. 40(7): 1683-1696 (2018) - [j3]Olivier Bernard
Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved? IEEE Trans. Medical Imaging 37(11): 2514-2525 (2018) - [c7]Christian F. Baumgartner
Visual Feature Attribution Using Wasserstein GANs. CVPR 2018: 8309-8319 - [c6]Yigit Baran Can, Krishna Chaitanya
Learning to Segment Medical Images with Scribble-Supervision Alone. DLMIA/ML-CDS@MICCAI 2018: 236-244 - [c5]Katarína Tóthová
Uncertainty Quantification in CNN-Based Surface Prediction Using Shape Priors. ShapeMI@MICCAI 2018: 300-310 - [i7]Yigit Baran Can, Krishna Chaitanya, Basil Mustafa, Lisa M. Koch, Ender Konukoglu, Christian F. Baumgartner:
Learning to Segment Medical Images with Scribble-Supervision Alone. CoRR abs/1807.04668 (2018) - [i6]Katarína Tóthová, Sarah Parisot, Matthew C. H. Lee, Esther Puyol-Antón, Lisa M. Koch, Andrew P. King, Ender Konukoglu, Marc Pollefeys:
Uncertainty Quantification in CNN-Based Surface Prediction Using Shape Priors. CoRR abs/1807.11272 (2018) - 2017
- [j2]Christian F. Baumgartner
SonoNet: Real-Time Detection and Localisation of Fetal Standard Scan Planes in Freehand Ultrasound. IEEE Trans. Medical Imaging 36(11): 2204-2215 (2017) - [c4]Christian F. Baumgartner
An Exploration of 2D and 3D Deep Learning Techniques for Cardiac MR Image Segmentation. STACOM@MICCAI 2017: 111-119 - [i5]Martin Rajchl, Lisa M. Koch, Christian Ledig, Jonathan Passerat-Palmbach, Kazunari Misawa, Kensaku Mori, Daniel Rueckert:
Employing Weak Annotations for Medical Image Analysis Problems. CoRR abs/1708.06297 (2017) - [i4]Christian F. Baumgartner, Lisa M. Koch, Marc Pollefeys, Ender Konukoglu:
An Exploration of 2D and 3D Deep Learning Techniques for Cardiac MR Image Segmentation. CoRR abs/1709.04496 (2017) - [i3]Christian F. Baumgartner, Lisa M. Koch, Kerem Can Tezcan, Jia Xi Ang, Ender Konukoglu:
Visual Feature Attribution using Wasserstein GANs. CoRR abs/1711.08998 (2017) - 2016
- [i2]Lisa M. Koch, Martin Rajchl, Wenjia Bai, Christian F. Baumgartner, Tong Tong, Jonathan Passerat-Palmbach, Paul Aljabar, Daniel Rueckert:
Multi-Atlas Segmentation using Partially Annotated Data: Methods and Annotation Strategies. CoRR abs/1605.00029 (2016) - [i1]Christian F. Baumgartner, Konstantinos Kamnitsas, Jacqueline Matthew, Tara P. Fletcher, Sandra Smith, Lisa M. Koch, Bernhard Kainz, Daniel Rueckert:
Real-Time Detection and Localisation of Fetal Standard Scan Planes in 2D Freehand Ultrasound. CoRR abs/1612.05601 (2016) - 2015
- [j1]Robert Wright
Construction of a fetal spatio-temporal cortical surface atlas from in utero MRI: Application of spectral surface matching. NeuroImage 120: 467-480 (2015) - [c3]Lisa M. Koch
Multi-atlas Segmentation as a Graph Labelling Problem: Application to Partially Annotated Atlas Data. IPMI 2015: 221-232 - [c2]Christian F. Baumgartner
Self-Aligning Manifolds for Matching Disparate Medical Image Datasets. IPMI 2015: 363-374 - 2014
- [c1]Lisa M. Koch
Graph-Based Label Propagation in Fetal Brain MR Images. MLMI 2014: 9-16
Coauthor Index
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