Christian F. Baumgartner

Assistant Professor of Medical Data Science

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Christian F. Baumgartner is an Assistant Professor for Health Data Science in the Faculty of Health Sciences and Medicine at the University of Lucerne, where he is leading the research group for Medical AI.

Education

Ph.D. Biomedical Engineering | King’s College London
M.Sc. Biomedical Engineering | ETH Zürich
B.Sc. Electrical Engineering | ETH Zürich


Publications

Unsupervised Anomaly Detection in Medical Imaging using Aggregated Normative Diffusion

Unsupervised Anomaly Detection in Medical Imaging using Aggregated Normative Diffusion
Alexander Frotscher, Jaivardhan Kapoor, Thomas Wolfers, Christian F. Baumgartner
Medical Image Analysis, 103895 (2025)

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Understanding Benefits and Pitfalls of Current Methods for the Segmentation of Undersampled MRI Data

Understanding Benefits and Pitfalls of Current Methods for the Segmentation of Undersampled MRI Data
Jan Nikolas Morshuis, Matthias Hein, Christian F. Baumgartner
arXiv preprint arXiv:2508.18975 (2025)

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Subgroup Performance Analysis in Hidden Stratifications

Subgroup Performance Analysis in Hidden Stratifications
Alceu Bissoto, Trung-Dung Hoang, Tim Flühmann, Susu Sun, Christian F. Baumgartner, Lisa M. Koch
Lecture Notes in Computer Science, 594-603 (2025)

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Studying therapy effects and disease outcomes in silico using artificial counterfactual tissue samples

Studying therapy effects and disease outcomes in silico using artificial counterfactual tissue samples
Martin Paulikat, Christian M. Schürch, Christian F. Baumgartner
Computers in Biology and Medicine, 197, 110997 (2025)

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Segmentation-Guided MRI Reconstruction for Meaningfully Diverse Reconstructions

Segmentation-Guided MRI Reconstruction for Meaningfully Diverse Reconstructions
Jan Nikolas Morshuis, Matthias Hein, Christian F. Baumgartner
Lecture Notes in Computer Science, 180-190 (2024)

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Prototype-Based Multiple Instance Learning for Gigapixel Whole Slide Image Classification

Prototype-Based Multiple Instance Learning for Gigapixel Whole Slide Image Classification
Susu Sun, Dominique van Midden, Geert Litjens, Christian F. Baumgartner
Lecture Notes in Computer Science, 507-517 (2025)

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Navigating the unknown: out-of-distribution detection for medical imaging

Navigating the unknown: out-of-distribution detection for medical imaging
Moritz Fuchs, Anastasios Nikolas Angelopoulos, Magdalini Paschali, Christian F. Baumgartner, Anirban Mukhopadhyay
Trustworthy AI in Medical Imaging, 73-99 (2025)

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Navigating Data Scarcity Using Foundation Models: A Benchmark of Few-Shot and Zero-Shot Learning Approaches in Medical Imaging

Navigating Data Scarcity Using Foundation Models: A Benchmark of Few-Shot and Zero-Shot Learning Approaches in Medical Imaging
Stefano Woerner, Christian F. Baumgartner
Lecture Notes in Computer Science, 30-39 (2024)

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Mind the Detail: Uncovering Clinically Relevant Image Details in Accelerated MRI with Semantically Diverse Reconstructions

Mind the Detail: Uncovering Clinically Relevant Image Details in Accelerated MRI with Semantically Diverse Reconstructions
Jan Nikolas Morshuis, Christian Schlarmann, Thomas Küstner, Christian F. Baumgartner, Matthias Hein
Lecture Notes in Computer Science, 356-366 (2025)

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Label-free concept based multiple instance learning for gigapixel histopathology

Label-free concept based multiple instance learning for gigapixel histopathology
Susu Sun, Leslie Tessier, Frederique Meeuwsen, Clement Grisi, Dominique van Midden, Geert Litjens, Christian F. Baumgartner
arXiv preprint arXiv:2501.02922 (2025)

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Is Uncertainty Quantification a Viable Alternative to Learned Deferral?

Is Uncertainty Quantification a Viable Alternative to Learned Deferral?
Anna M. Wundram, Christian F. Baumgartner
Lecture Notes in Computer Science, 34-44 (2025)

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Evaluation of an automated laminar cartilage T2 relaxation time analysis method in an early osteoarthritis model

Evaluation of an automated laminar cartilage T2 relaxation time analysis method in an early osteoarthritis model
Wolfgang Wirth, Susanne Maschek, Anna Wisser, Jana Eder, Christian F. Baumgartner, Akshay Chaudhari, Francis Berenbaum, Felix Eckstein, OA-BIO Consortium
Skeletal radiology, 54, 571--584 (2025)

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Development and comprehensive clinical validation of a deep neural network for radiation dose modelling to enhance magnetic resonance imaging guided radiotherapy

Development and comprehensive clinical validation of a deep neural network for radiation dose modelling to enhance magnetic resonance imaging guided radiotherapy
Moritz Schneider, Simon Gutwein, David Mönnich, Cihan Gani, Paul Fischer, Christian F. Baumgartner, Daniela Thorwarth
Physics and Imaging in Radiation Oncology, 33, 100723 (2025)

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Deep Unsupervised Anomaly Detection in Brain Imaging: Large-Scale Benchmarking and Bias Analysis

Deep Unsupervised Anomaly Detection in Brain Imaging: Large-Scale Benchmarking and Bias Analysis
Alexander Frotscher, Christian F. Baumgartner, Thomas Wolfers
arXiv preprint arXiv:2512.01534 (2025)

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CUTE-MRI: Conformalized Uncertainty-based framework for Time-adaptivE MRI

CUTE-MRI: Conformalized Uncertainty-based framework for Time-adaptivE MRI
Paul Fischer, Jan Nikolas Morshuis, Thomas Kustner, Christian F. Baumgartner
arXiv preprint arXiv:2508.14952 (2025)

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Conformal Performance Range Prediction for Segmentation Output Quality Control

Conformal Performance Range Prediction for Segmentation Output Quality Control
Anna M. Wundram, Paul Fischer, Michael Mühlebach, Lisa M. Koch, Christian F. Baumgartner
Lecture Notes in Computer Science, 81-91 (2024)

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A comprehensive and easy-to-use multi-domain multi-task medical imaging meta-dataset

A comprehensive and easy-to-use multi-domain multi-task medical imaging meta-dataset
Stefano Woerner, Arthur Jaques, Christian F. Baumgartner
Scientific Data, 12, 666 (2025)

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1930 Estimating uncertainty for AI-based dose modelling in MRI-guided RT using ensemble networks, mean variance estimation and Monte Carlo dropout
Tabea Eberhardt, Moritz Schneider, Christian F. Baumgartner, Paul Fischer, Maximilian Niyazi, Daniela Thorwarth
Radiotherapy and Oncology, 206, S3387-S3389 (2025)

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Subgroup-Specific Risk-Controlled Dose Estimation in Radiotherapy

Subgroup-Specific Risk-Controlled Dose Estimation in Radiotherapy
Paul Fischer, Hannah Willms, Moritz Schneider, Daniela Thorwarth, Michael Muehlebach, Christian F. Baumgartner
Lecture Notes in Computer Science, 696-706 (2024)

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SC29.03 AUTOMATIC AI-BASED SEGMENTATION OF LIVER METASTASES AND ORGANS-AT-RISK FOR MR-GUIDED RADIOTHERAPY
D. Langner, C. Gani, Christian F. Baumgartner, D. Thorwarth
Physica Medica, 125, 103528 (2024)

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SC29.02 UNCERTAINTY ESTIMATION FOR AI-BASED DOSE MODELLING IN MR-GUIDED RADIOTHERAPY USING ENSEMBLE LEARNING AND MONTE CARLO DROPOUT
T. Eberhardt, M. Schneider, Paul Fischer, C. Gani, Christian F. Baumgartner, D. Thorwarth
Physica Medica, 125, 103527 (2024)

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PULPo: Probabilistic Unsupervised Laplacian Pyramid Registration

PULPo: Probabilistic Unsupervised Laplacian Pyramid Registration
Leonard Siegert, Paul Fischer, Mattias P. Heinrich, Christian F. Baumgartner
Lecture Notes in Computer Science, 717-727 (2024)

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MRExtrap: Linear Prediction of Brain Aging in Autoencoder Latent Space of MRI Scans
Jaivardhan Kapoor, Jakob H Macke, Christian F. Baumgartner
Medical Imaging with Deep Learning (short paper) (2024)

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MedIMeta: An easy-to-use meta-dataset for medical imaging applications
Stefano Woerner, Arthur Jaques, Christian F. Baumgartner
Medical Imaging with Deep Learning (short paper) (2024)

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Leveraging probabilistic segmentation models for improved glaucoma diagnosis: A clinical pipeline approach

Leveraging probabilistic segmentation models for improved glaucoma diagnosis: A clinical pipeline approach
Anna M. Wundram, Paul Fischer, Stephan Wunderlich, Hanna Faber, Lisa M Koch, Philipp Berens, Christian F. Baumgartner
Proceedings of Machine Learning Research, 25-, 1725-1740 (2024)

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Distribution shift detection for the postmarket surveillance of medical AI algorithms: a retrospective simulation study

Distribution shift detection for the postmarket surveillance of medical AI algorithms: a retrospective simulation study
Lisa M. Koch, Christian F. Baumgartner, Philipp Berens
npj Digital Medicine, 7, 120 (2024)

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Attri-Net: A Globally and Locally Inherently Interpretable Model for Multi-Label Classification Using Class-Specific Counterfactuals

Attri-Net: A Globally and Locally Inherently Interpretable Model for Multi-Label Classification Using Class-Specific Counterfactuals
Susu Sun, Stefano Woerner, Andreas Maier, Lisa M Koch, Christian F. Baumgartner
Journal of Machine Learning for Biomedical Research (MELBA) (2024)

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Uncertainty Estimation and Propagation in Accelerated MRI Reconstruction

Uncertainty Estimation and Propagation in Accelerated MRI Reconstruction
Paul Fischer, K. Thomas, Christian F. Baumgartner
Lecture Notes in Computer Science, 84-94 (2023)

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Sparse Activations for Interpretable Disease Grading

Sparse Activations for Interpretable Disease Grading
Kerol R. Donteu Djoumessi, Indu Ilanchezian, Laura Kühlewein, Hanna Faber, Christian F. Baumgartner, Bubacarr Bah, Philipp Berens, Lisa M. Koch
Proceedings of Machine Learning Research, 227, 1-17 (2023)

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Right for the Wrong Reason: Can Interpretable ML Techniques Detect Spurious Correlations?

Right for the Wrong Reason: Can Interpretable ML Techniques Detect Spurious Correlations?
Susu Sun, Lisa M. Koch, Christian F. Baumgartner
Lecture Notes in Computer Science, 425-434 (2023)

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Multiscale Metamorphic VAE for 3D Brain MRI Synthesis

Multiscale Metamorphic VAE for 3D Brain MRI Synthesis
Jaivardhan Kapoor, Jakob H Macke, Christian F. Baumgartner
arXiv preprint arXiv:2301.03588 (2023)

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K2S Challenge: From Undersampled K-Space to Automatic Segmentation

K2S Challenge: From Undersampled K-Space to Automatic Segmentation
Aniket A. Tolpadi, Upasana Bharadwaj, Kenneth T. Gao, Rupsa Bhattacharjee, Felix G. Gassert, Johanna Luitjens, Paula Giesler, Jan Nikolas Morshuis, Paul Fischer, Matthias Hein, Christian F. Baumgartner, Artem Razumov, Dmitry Dylov, Quintin van Lohuizen, Stefan J. Fransen, Xiaoxia Zhang, Radhika Tibrewala, Hector Lise de Moura, Kangning Liu, Marcelo V. W. Zibetti, Ravinder Regatte, Sharmila Majumdar, Valentina Pedoia
Bioengineering, 10, 267 (2023)

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Inherently interpretable multi-label classification using class-specific counterfactuals

Inherently interpretable multi-label classification using class-specific counterfactuals
Susu Sun, Stefano Woerner, Andreas Maier, Lisa M Koch, Christian F. Baumgartner
Proceedings of Machine Learning Research, 227, 937-956 (2023)

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Deep Hypothesis Tests Detect Clinically Relevant Subgroup Shifts in Medical Images

Deep Hypothesis Tests Detect Clinically Relevant Subgroup Shifts in Medical Images
Lisa M Koch, Christian M Schurch, Christian F. Baumgartner, Arthur Gretton, Philipp Berens
arXiv preprint arXiv:2303.04862 (2023)

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Agreement and accuracy of fully automated morphometric femorotibial cartilage analysis in radiographic knee osteoarthritis

Agreement and accuracy of fully automated morphometric femorotibial cartilage analysis in radiographic knee osteoarthritis
Felix Eckstein, Akshay S. Chaudhari, Jana Kemnitz, Christian F. Baumgartner, Wolfgang Wirth
Osteoarthritis Imaging, 3, 100156 (2023)

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Strategies for Meta-Learning with Diverse Tasks
Stefano Woerner, Christian F. Baumgartner
Medical Imaging with Deep Learning (short paper) (2022)

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Sampling Possible Reconstructions of Undersampled Acquisitions in MR Imaging With a Deep Learned Prior
Kerem C. Tezcan, Neerav Karani, Christian F. Baumgartner, Ender Konukoglu
IEEE Transactions on Medical Imaging, 41, 1885-1896 (2022)

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PO-1637 Influence of training data variability on deep learning dose prediction robustness for MR-guided RT
M. Nachbar, S. Gutwein, M. Schneider, D. Zips, Christian F. Baumgartner, D. Thorwarth
Radiotherapy and Oncology, 170, S1431-S1433 (2022)

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Detection of Differences in Longitudinal Cartilage Thickness Loss Using a Deep‐Learning Automated Segmentation Algorithm: Data From the Foundation for the National Institutes of Health Biomarkers Study of the Osteoarthritis Initiative
Felix Eckstein, Akshay S. Chaudhari, David Fuerst, Martin Gaisberger, Jana Kemnitz, Christian F. Baumgartner, Ender Konukoglu, David J. Hunter, Wolfgang Wirth
Arthritis Care & Research, 74, 929-936 (2022)

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Adversarial Robustness of MR Image Reconstruction Under Realistic Perturbations

Adversarial Robustness of MR Image Reconstruction Under Realistic Perturbations
Jan Nikolas Morshuis, Sergios Gatidis, Matthias Hein, Christian F. Baumgartner
Lecture Notes in Computer Science, 24-33 (2022)

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A deep learning automated segmentation algorithm accurately detects differences in longitudinal cartilage thickness loss-data from the FNIH biomarkers study of the osteoarthritis initiative
Felix Eckstein, Akshay S Chaudhari, David Fuerst, Martin Gaisberger, Jana Kemnitz, Christian F. Baumgartner, Ender Konukoglu, David J Hunter, Wolfgang Wirth
Arthritis Care Res (Hoboken), 74, 929--936 (2022)

Semi-supervised task-driven data augmentation for medical image segmentation

Semi-supervised task-driven data augmentation for medical image segmentation
Krishna Chaitanya, Neerav Karani, Christian F. Baumgartner, Ertunc Erdil, Anton Becker, Olivio Donati, Ender Konukoglu
Medical Image Analysis, 68, 101934 (2021)

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Effect of training set sample size on the agreement, accuracy, and sensitivity to change of automated U-net-based cartilage thickness analysis
F. Eckstein, A. Chaudhari, Christian F. Baumgartner, E. Konukoglu, A. Wisser, D. Fürst, W. Wirth
Osteoarthritis and Cartilage, 29, S326-S327 (2021)

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Agreement and accuracy of femorotibial cartilage morphometry in radiographic knee OA using different training sets for automateddeep learning segmentation - comparison between flash and dess MRI
W. Wirth, A.S. Chaudhari, J. Kemnitz, Christian F. Baumgartner, E. Konukoglu, D. Fürst, F. Eckstein
Osteoarthritis and Cartilage, 29, S334 (2021)

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A deep-learning-based technique for the quantitative analysis of femorotibial osteophyte and bone volumes -data from the osteoarthritis initiative
J.K. Schachinger, S. Maschek, A. Wisser, D. Fürst, A.S. Chaudhari, J. Kemnitz, Christian F. Baumgartner, E. Konukoglu, F. Eckstein, W. Wirth
Osteoarthritis and Cartilage, 29, S328-S329 (2021)

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Clinical evaluation of fully automated thigh muscle and adipose tissue segmentation using a U-Net deep learning architecture in context of osteoarthritic knee pain
Jana Kemnitz, Christian F. Baumgartner, Felix Eckstein, Akshay Chaudhari, Anja Ruhdorfer, Wolfgang Wirth, Sebastian K Eder, Ender Konukoglu
Magnetic Resonance Materials in Physics, Biology and Medicine, 33, 483--493 (2020)

Automated quantification of myocardial tissue characteristics from native T1 mapping using neural networks with uncertainty-based quality-control

Automated quantification of myocardial tissue characteristics from native T1 mapping using neural networks with uncertainty-based quality-control
Esther Puyol-Antón, Bram Ruijsink, Christian F. Baumgartner, Pier-Giorgio Masci, Matthew Sinclair, Ender Konukoglu, Reza Razavi, Andrew P. King
Journal of Cardiovascular Magnetic Resonance, 22, 60 (2020)

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Semi-supervised and Task-Driven Data Augmentation

Semi-supervised and Task-Driven Data Augmentation
Krishna Chaitanya, Neerav Karani, Christian F. Baumgartner, Anton Becker, Olivio Donati, Ender Konukoglu
Lecture Notes in Computer Science, 29-41 (2019)

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PHiSeg: Capturing Uncertainty in Medical Image Segmentation

PHiSeg: Capturing Uncertainty in Medical Image Segmentation
Christian F. Baumgartner, Kerem C. Tezcan, Krishna Chaitanya, Andreas M. Hötker, Urs J. Muehlematter, Khoschy Schawkat, Anton S. Becker, Olivio Donati, Ender Konukoglu
Lecture Notes in Computer Science, 119-127 (2019)

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Clinical validation of fully automated segmentation of thigh muscle and adipose tissue cross sectional areas using maching learning with a convolutional neural network

Clinical validation of fully automated segmentation of thigh muscle and adipose tissue cross sectional areas using maching learning with a convolutional neural network
J. Kemnitz, Christian F. Baumgartner, A. Ruhdorfer, W. Wirth, F. Eckstein, S.K. Eder, E. Konukoglu
Osteoarthritis and Cartilage, 27, S383-S384 (2019)

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A Partially Reversible U-Net for Memory-Efficient Volumetric Image Segmentation

A Partially Reversible U-Net for Memory-Efficient Volumetric Image Segmentation
Robin Brügger, Christian F. Baumgartner, Ender Konukoglu
Lecture Notes in Computer Science, 429-437 (2019)

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Visual Feature Attribution Using Wasserstein GANs

Visual Feature Attribution Using Wasserstein GANs
Christian F. Baumgartner, Lisa M. Koch, Kerem Can Tezcan, Jia Xi Ang, Ender Konukoglu
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 8309-8319 (2018)

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MR image reconstruction using deep density priors

MR image reconstruction using deep density priors
Kerem C Tezcan, Christian F. Baumgartner, Roger Luechinger, Klaas P Pruessmann, Ender Konukoglu
IEEE transactions on medical imaging, 38, 1633--1642 (2018)

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Learning to Segment Medical Images with Scribble-Supervision Alone

Learning to Segment Medical Images with Scribble-Supervision Alone
Yigit B. Can, Krishna Chaitanya, Basil Mustafa, Lisa M. Koch, Ender Konukoglu, Christian F. Baumgartner
Lecture Notes in Computer Science, 236-244 (2018)

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Human-level Performance On Automatic Head Biometrics In Fetal Ultrasound Using Fully Convolutional Neural Networks

Human-level Performance On Automatic Head Biometrics In Fetal Ultrasound Using Fully Convolutional Neural Networks
Matthew Sinclair, Christian F. Baumgartner, Jacqueline Matthew, Wenjia Bai, Juan Cerrolaza Martinez, Yuanwei Li, Sandra Smith, Caroline L. Knight, Bernhard Kainz, Jo Hajnal, Andrew P. King, Daniel Rueckert
2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 714-717 (2018)

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Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?

Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?
Olivier Bernard, Alain Lalande, Clement Zotti, Frederick Cervenansky, Xin Yang, Pheng-Ann Heng, Irem Cetin, Karim Lekadir, Oscar Camara, Miguel Angel Gonzalez Ballester, Gerard Sanroma, Sandy Napel, Steffen Petersen, Georgios Tziritas, Elias Grinias, Mahendra Khened, Varghese Alex Kollerathu, Ganapathy Krishnamurthi, Marc-Michel Rohé, Xavier Pennec, Maxime Sermesant, Fabian Isensee, Paul Jäger, Klaus H. Maier-Hein, Peter M. Full, Ivo Wolf, Sandy Engelhardt, Christian F. Baumgartner, Lisa M. Koch, Jelmer M. Wolterink, Ivana Išgum, Yeonggul Jang, Yoonmi Hong, Jay Patravali, Shubham Jain, Olivier Humbert, Pierre-Marc Jodoin
IEEE Transactions on Medical Imaging, 37, 2514-2525 (2018)

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Combining Heterogeneously Labeled Datasets For Training Segmentation Networks

Combining Heterogeneously Labeled Datasets For Training Segmentation Networks
Jana Kemnitz, Christian F. Baumgartner, Wolfgang Wirth, Felix Eckstein, Sebastian K. Eder, Ender Konukoglu
Lecture Notes in Computer Science, 276-284 (2018)

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Cascaded transforming multi-task networks for abdominal biometric estimation from ultrasound

Cascaded transforming multi-task networks for abdominal biometric estimation from ultrasound
Matthew D Sinclair, Juan Cerrolaza Martinez, Emily Skelton, Yuanwei Li, Christian F. Baumgartner, Wenjia Bai, Jacqueline Matthew, Caroline L Knight, Sandra Smith, Jo Hajnal, others
Medical Imaging with Deep Learning (MIDL 2018) (2018)

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Automatic Shadow Detection in 2D Ultrasound Images
Qingjie Meng, Christian F. Baumgartner, Matthew Sinclair, James Housden, Martin Rajchl, Alberto Gomez, Benjamin Hou, Nicolas Toussaint, Veronika Zimmer, Jeremy Tan, Jacqueline Matthew, Daniel Rueckert, Julia Schnabel, Bernhard Kainz
Lecture Notes in Computer Science, 66-75 (2018)

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A Lifelong Learning Approach to Brain MR Segmentation Across Scanners and Protocols

A Lifelong Learning Approach to Brain MR Segmentation Across Scanners and Protocols
Neerav Karani, Krishna Chaitanya, Christian F. Baumgartner, Ender Konukoglu
Lecture Notes in Computer Science, 476-484 (2018)

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Unsupervised Domain Adaptation in Brain Lesion Segmentation with Adversarial Networks

Unsupervised Domain Adaptation in Brain Lesion Segmentation with Adversarial Networks
Konstantinos Kamnitsas, Christian F. Baumgartner, Christian Ledig, Virginia Newcombe, Joanna Simpson, Andrew Kane, David Menon, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker
Lecture Notes in Computer Science, 597-609 (2017)

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SonoNet: Real-Time Detection and Localisation of Fetal Standard Scan Planes in Freehand Ultrasound

SonoNet: Real-Time Detection and Localisation of Fetal Standard Scan Planes in Freehand Ultrasound
Christian F. Baumgartner, Konstantinos Kamnitsas, Jacqueline Matthew, Tara P. Fletcher, Sandra Smith, Lisa M. Koch, Bernhard Kainz, Daniel Rueckert
IEEE Transactions on Medical Imaging, 36, 2204-2215 (2017)

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Multi-atlas segmentation using partially annotated data: methods and annotation strategies
Lisa Margret Koch, Martin Rajchl, Wenjia Bai, Christian F. Baumgartner, Tong Tong, Jonathan Passerat-Palmbach, Paul Aljabar, Daniel Rueckert
IEEE transactions on pattern analysis and machine intelligence, 40, 1683--1696 (2017)

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High-Resolution Self-Gated Dynamic Abdominal MRI Using Manifold Alignment
Xin Chen, Muhammad Usman, Christian F. Baumgartner, Daniel R. Balfour, Paul K. Marsden, Andrew J. Reader, Claudia Prieto, Andrew P. King
IEEE Transactions on Medical Imaging, 36, 960-971 (2017)

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Fully Convolutional Networks in Medical Imaging: Applications to Image Enhancement and Recognition
Christian F. Baumgartner, Ozan Oktay, Daniel Rueckert
Advances in Computer Vision and Pattern Recognition, 159-179 (2017)

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Compositional neural-network modeling of complex analog circuits
Ramin M. Hasani, Dieter Haerle, Christian F. Baumgartner, Alessio R. Lomuscio, Radu Grosu
2017 International Joint Conference on Neural Networks (IJCNN), 2235-2242 (2017)

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Automated Detection of Motion Artefacts in MR Imaging Using Decision Forests
Benedikt Lorch, Ghislain Vaillant, Christian F. Baumgartner, Wenjia Bai, Daniel Rueckert, Andreas Maier
Journal of Medical Engineering, 2017, 1-9 (2017)

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Autoadaptive motion modelling for MR-based respiratory motion estimation

Autoadaptive motion modelling for MR-based respiratory motion estimation
Christian F. Baumgartner, Christoph Kolbitsch, Jamie R. McClelland, Daniel Rueckert, Andrew P. King
Medical Image Analysis, 35, 83-100 (2017)

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An exploration of 2D and 3D deep learning techniques for cardiac MR image segmentation

An exploration of 2D and 3D deep learning techniques for cardiac MR image segmentation
Christian F. Baumgartner, Lisa M. Koch, Marc Pollefeys, Ender Konukoglu
International Workshop on Statistical Atlases and Computational Models of the Heart, 111--119 (2017)

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Real-Time Standard Scan Plane Detection and Localisation in Fetal Ultrasound Using Fully Convolutional Neural Networks

Real-Time Standard Scan Plane Detection and Localisation in Fetal Ultrasound Using Fully Convolutional Neural Networks
Christian F. Baumgartner, Konstantinos Kamnitsas, Jacqueline Matthew, Sandra Smith, Bernhard Kainz, Daniel Rueckert
Lecture Notes in Computer Science, 203-211 (2016)

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Motionfree abdominal MRI using manifold alignment
Xin Chen, Muhammad Usman, Christian F. Baumgartner, Claudia Prieto, Andrew King
Proc. Int. Soc. Magn. Reson. Med (2016)

Self-Aligning Manifolds for Matching Disparate Medical Image Datasets

Self-Aligning Manifolds for Matching Disparate Medical Image Datasets
Christian F. Baumgartner, Alberto Gomez, Lisa M. Koch, James R. Housden, Christoph Kolbitsch, Jamie R. McClelland, Daniel Rueckert, Andy P. King
Lecture Notes in Computer Science, 363-374 (2015)

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The Estimation of Free-Water Corrected Diffusion Tensors
Ofer Pasternak, Klaus Maier-Hein, Christian F. Baumgartner, Martha E. Shenton, Yogesh Rathi, Carl-Fredrik Westin
Mathematics and Visualization, 249-270 (2014)

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High-resolution dynamic MR imaging of the thorax for respiratory motion correction of PET using groupwise manifold alignment

High-resolution dynamic MR imaging of the thorax for respiratory motion correction of PET using groupwise manifold alignment
Christian F. Baumgartner, Christoph Kolbitsch, Daniel R. Balfour, Paul K. Marsden, Jamie R. McClelland, Daniel Rueckert, Andrew P. King
Medical Image Analysis, 18, 939-952 (2014)

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Autoadaptive motion modelling

Autoadaptive motion modelling
Christian F. Baumgartner, C. Kolbitsch, J. R. McClelland, D. Rueckert, A. P. King
2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI), 457-460 (2014)

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Achieving 3D CINE from free breathing multi-slice 2D acquisitions via Simultaneous Groupwise Manifold Alignment
Muhammad Usman, Christian F. Baumgartner, Andrew King, David Atkinson, Tobias Schaeffter, Claudia Prieto
Proc. Intl. Soc. Mag. Reson. Med, 22, 4359 (2014)

Groupwise Simultaneous Manifold Alignment for High-Resolution Dynamic MR Imaging of Respiratory Motion

Groupwise Simultaneous Manifold Alignment for High-Resolution Dynamic MR Imaging of Respiratory Motion
Christian F. Baumgartner, Christoph Kolbitsch, Jamie R. McClelland, Daniel Rueckert, Andrew P. King
Lecture Notes in Computer Science, 232-243 (2013)

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Filtered multi-tensor tractography using free water estimation
Christian F. Baumgartner, Ofer Pasternak, Sylvain Bouix, Carl-Fredrik Westin, Yogesh Rathi
Inernational Society for Magnetic Resonance in Medicine Meeting (2012)

A unified tractography framework for comparing diffusion models on clinical scans
Christian F. Baumgartner, O Michailovich, J Levitt, O Pasternak, S Bouix, CF Westin, Yogesh Rathi
Computational Diffusion MRI Workshop of MICCAI, Nice, 27-32 (2012)
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