2026
Hierarchical Vision Transformer with Prototypes for Interpretable Medical Image Classification
Luisa Gallée, Catharina Silvia Lisson, Meinrad Beer, Michael Götz
IEEE Journal of Biomedical and Health Informatics (JBHI), 2026
arXiv Code
A Modular Agent for Reliable and Auditable Spatial Relation Verification in CT Scans
Simon Vincent Abel, Heiko Hillenhagen, Michael Götz, Timo Ropinski, Ayhan Can Erdur†, Daniel Santak Wolf†
MICCAI Workshop on Agentic AI for Medicine (AgenticMed), 2026
arXiv Code
Towards Practical Algorithm Selection for Unsupervised Domain Adaptation in Medical Imaging
Yiheng Xiong, Luisa Gallée, Daniel Santak Wolf, Heiko Hillenhagen, Michael Götz
MICCAI Workshop on Applications of Medical AI (AMAI), 2026 · Oral
arXiv Code
Computed Tomography-Based Assessment of Sarcopenia and Disease Progression in Pancreatic Ductal Adenocarcinoma: A Radiomics and Machine Learning Approach
Jean-Philippe R. Krieg, Luisa Gallée, Daniel Santak Wolf, Konstantin Müller, Michael Götz, Thomas J. Ettrich, Thomas Seufferlein, Christopher Kloth, Meinrad Beer, Daniel Vogele
Gastroenterology Research, 2026
Paper
FunnyNodules: A Customizable Medical Dataset Tailored for Evaluating Explainable AI
Luisa Gallée, Yiheng Xiong, Meinrad Beer, Michael Götz
Medical Imaging with Deep Learning (MIDL), 2026 · Oral
arXiv Code Paper
Contrastive Virtual Staining Enhances Deep Learning‐Based PDAC Subtyping from H&E‐Stained Tissue Cores
Maximilian Fischer, Alexander Muckenhuber, Robin Peretzke, Luay Farah, Constantin Ulrich, Sebastian Ziegler, et al., Michael Götz, et al.
The Journal of Pathology, 2026
Paper
2025
Non-Hodgkin’s Lymphoma Classification Using 3D Radiomics Machine Learning Models for Precision Imaging in Oncology
Christoph G. Lisson, Michael Götz, Daniel Santak Wolf, Sabitha Manoj, Luisa Gallée, Stefan A. Schmidt, Eugen Tausch, Christof Schneider, Stephan Stilgenbauer, Ambros J. Beer, Meinrad Beer, Nico Sollmann, Catharina S. Lisson
BMC Medical Imaging, 2025
Paper
Your Other Left! Vision-Language Models Fail to Identify Relative Positions in Medical Images
Daniel Santak Wolf, Heiko Hillenhagen, Billurvan Taskin, Alex Bäuerle, Meinrad Beer, Michael Götz†, Timo Ropinski†
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2025
Best Oral Presentation Award, BVM 2026
arXiv Paper Code
Minimum Data, Maximum Impact: 20 Annotated Samples for Explainable Lung Nodule Classification
Luisa Gallée, Catharina Silvia Lisson, Christoph Gerhard Lisson, Daniela Drees, Felix Weig, Daniel Vogele, Meinrad Beer, Michael Götz
MICCAI Workshop on Interpretability of Machine Intelligence in Medical Image Computing (iMIMIC), 2025 · Oral
arXiv Code
Machine Learning-Based Radiomics for Bladder Cancer Staging: Evaluating the Role of Imaging Timing in Differentiating T2 from T3 Disease
Christoph G. Lisson, Luisa Gallée, Konstantin Müller, Sabitha Manoj, Hannah Stöckl, Friedemann Zengerling, Christian Bolenz, Meinrad Beer, Michael Götz, Catharina S. Lisson
Frontiers in Oncology, 2025
Paper
Overview of Leakage Scenarios in Supervised Machine Learning
Leonard Sasse, Eliana Nicolaisen-Sobesky, Juergen Dukart, Simon B. Eickhoff, Michael Götz, Sami Hamdan, Vera Komeyer, Abhijit Kulkarni, Juha M. Lahnakoski, Bradley C. Love, Federico Raimondo, Kaustubh R. Patil
Journal of Big Data, 2025
Paper
Unlocking the Potential of Digital Pathology: Novel Baselines for Compression
Maximilian Fischer, Peter Neher, Peter Schüffler, Sebastian Ziegler, Shuhan Xiao, Robin Peretzke, et al., Michael Götz, et al.
Journal of Pathology Informatics, 2025
Paper
2024
Deep Learning-Based Classification and Segmentation of Whole-Body 18F-FDG PET/CT Examinations Using Manually Generated Segmentation Masks
Daniel Steube, Heiko Hillenhagen, Stephan Stilgenbauer, Ambros J. Beer, Meinrad Beer, Michael Götz, et al.
Annual Congress of the European Association of Nuclear Medicine (EANM), 2024
Paper
Radiomics Workflow Definition & Challenges – German Priority Program 2177 Consensus Statement on Clinically Applied Radiomics
Ralf Floca, Jonas Bohn, Christian Haux, Benedikt Wiestler, Frank G. Zöllner, Annika Reinke, et al., Michael Götz, et al.
Insights into Imaging, 2024
Paper
Evaluating the Explainability of Attributes and Prototypes for a Medical Classification Model
Luisa Gallée, Catharina Silvia Lisson, Christoph Gerhard Lisson, Daniela Drees, Felix Weig, Daniel Vogele, Meinrad Beer, Michael Götz
World Conference on Explainable Artificial Intelligence (xAI), 2024 · Oral
Paper
Learned Image Compression for HE-Stained Histopathological Images via Stain Deconvolution
Maximilian Fischer, Peter F. Neher, Tassilo Wald, Silvia Dias Almeida, Shuhan Xiao, Peter Schüffler, Rickmer Braren, Michael Götz, Alexander Muckenhuber, Jens Kleesiek, Marco Nolden, Klaus H. Maier-Hein
MICCAI Workshop on Medical Optical Imaging and Virtual Microscopy (MOVI), 2024
Paper
Segmental Quantification of Hepatic Lipid Content Based on Volumetric MRI Data in Patients with Suspected Iron Overload
Arthur P. Wunderlich, Holger Cario, Stephan Kannengießer, Veronika Grunau, Michael Götz, Felix Hüttner, Johanna Backhus, Meinrad Beer, Stefan Andreas Schmidt
RöFo-Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, 2024
Paper
2023
Self-Supervised Pre-Training with Contrastive and Masked Autoencoder Methods for Dealing with Small Datasets in Deep Learning for Medical Imaging
Daniel Santak Wolf, Tristan Payer, Catharina Silvia Lisson, Christoph Gerhard Lisson, Meinrad Beer, Michael Götz†, Timo Ropinski†
Nature Scientific Reports, 2023
arXiv Paper Code
Interpretable Medical Image Classification Using Prototype Learning and Privileged Information
Luisa Gallée, Meinrad Beer, Michael Götz
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2023 · Oral
Best Oral Presentation Award, Women in MICCAI (WiM) 2023 Best Oral Presentation Award, BVM 2024
arXiv Paper Code
Artificial Intelligence in Radiology–Beyond the Black Box
Luisa Gallée, Hannah Kniesel, Timo Ropinski, Michael Götz
RöFo-Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, 2023
Paper
Radiomics and Clinicopathological Characteristics for Predicting Lymph Node Metastasis in Testicular Cancer
Catharina Silvia Lisson, Sabitha Manoj, Daniel Santak Wolf, Christoph Gerhard Lisson, Stefan A Schmidt, Meinrad Beer, Wolfgang Thaiss, Christian Bolenz, Friedemann Zengerling, Michael Götz
MDPI Cancers, 2023
Paper
CT Radiomics and Clinical Feature Model to Predict Lymph Node Metastases in Early-Stage Testicular Cancer
Catharina Silvia Lisson, Sabitha Manoj, Daniel Santak Wolf, Jasper Schrader, Stefan Andreas Schmidt, Meinrad Beer, Michael Götz, Friedemann Zengerling, Christoph Gerhard Sebastian Lisson
MDPI Onco, 2023
Paper
Medical Volume Segmentation by Overfitting Sparsely Annotated Data
Tristan Payer, Faraz Nizamani, Meinrad Beer, Michael Götz, Timo Ropinski
Journal of Medical Imaging, 2023
Paper
Artificial Intelligence in Coronary Computed Tomography Angiography: Demands and Solutions from a Clinical Perspective
Bettina Baeßler, Michael Götz, Charalambos Antoniades, Julius F. Heidenreich, Tim Leiner, Meinrad Beer
Frontiers in Cardiovascular Medicine, 2023
Paper
On Leakage in Machine Learning Pipelines
Leonard Sasse, Eliana Nicolaisen-Sobesky, Juergen Dukart, Simon B Eickhoff, Michael Götz, Sami Hamdan, Vera Komeyer, Abhijit Kulkarni, Juha Lahnakoski, Bradley C Love, Federico Raimondo, Kaustubh R Patil
arXiv preprint, 2023
arXiv
Machine Learning Classifiers for Predictive Biomarkers Combining Clinical and Radiomic Data in Testicular Cancer
Catharina Silvia Lisson, Sabitha Manoj, Daniel Santak Wolf, Christoph Gerhard Lisson, Stefan A. Schmidt, Meinrad Beer, Wolfgang Thaiss, Christian Bolenz, Friedemann Zengerling, Michael Götz
Preprints.org, 2023
Paper
RPTK: The Role of Feature Computation on Prediction Performance
Jonas R. Bohn, Christian M. Heidt, Silvia D. Almeida, Lisa Kausch, Michael Götz, Marco Nolden, Petros Christopoulos, Stephan Rheinheimer, Alan A. Peters, Oyunbileg von Stackelberg, Hans-Ulrich Kauczor, Klaus H. Maier-Hein, Claus P. Heußel, Tobias Norajitra
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2023
Paper
Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning
Maximilian Fischer, Peter F. Neher, Peter Schüffler, Shuhan Xiao, Silvia Dias Almeida, Constantin Ulrich, Alexander Muckenhuber, Rickmer Braren, Michael Götz, Jens Kleesiek, Marco Nolden, Klaus H. Maier-Hein
MICCAI Workshop on Machine Learning in Medical Imaging (MLMI), 2023
Paper
Prediction of Bone Marrow Biopsy Results from MRI in Multiple Myeloma Patients Using Deep Learning and Radiomics
Markus Wennmann, Wenlong Ming, Fabian Bauer, Jiri Chmelik, André Klein, Charlotte Uhlenbrock, et al., Michael Götz, et al.
Investigative Radiology, 2023
Paper
Noninvasive Liver Iron Quantification by MRI Using Refocused Gradient-Echo (bSSFP): Preliminary Results
Arthur P. Wunderlich, Holger Cario, Michael Götz, Meinrad Beer, Stefan Andreas Schmidt
RöFo-Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, 2023
Paper
In vivo Reproduzierbarkeit von Radiomics-Merkmalen zwischen verschiedenen MRT-Geräten bei Patienten mit monoklonalen Plasmazellerkrankungen – eine prospektive Bi-institutionelle Studie
Markus Wennmann, Fabian Bauer, Peter F. Neher, Martin Grözinger, Lukas T. Rotkopf, Hartmut Goldschmidt, Tim F. Weber, Stefan Delorme, Klaus H. Maier-Hein, Heinz-Peter Schlemmer, Michael Götz
RöFo-Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, 2023
Paper
Volumetric Evaluation of 3D Multi-Gradient-Echo MRI Data to Assess Whole Liver Iron Distribution by Segmental R2* Analysis: First Experience
Arthur P Wunderlich, Holger Cario, Stephan Kannengießer, Veronika Grunau, Lena Hering, Michael Götz, Meinrad Beer, Stefan Andreas Schmidt
RöFo-Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, 2023
Paper
Liver R2* with Magnitude Fitting in Iron-Overload Patients–Initial Results on Agreement between Protocol Settings and between 1.5 T and 3T
Stephan Kannengießer, Arthur Wunderlich, Xiaodong Zhong, Dominik Nickel, Holger Cario, Michael Götz, Meinrad Beer, Stefan Schmidt
Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM), 2023
Paper
MR-Based Segmental Quantification of Hepatic Lipid Content in Patients with Suspected Iron Overload
Arthur Wunderlich, Holger Cario, Stephan Kannengießer, Veronika Grunau, Michael Götz, Meinrad Beer, Stefan Schmidt
Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM), 2023
Paper
MRI-Based Liver Iron Quantification Using Refocused Gradient-Echo (bSSFP): Initial Results
Arthur Wunderlich, Holger Cario, Michael Götz, Meinrad Beer, Stefan Schmidt
Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM), 2023
Paper
2022
Weakly Supervised Learning with Positive and Unlabeled Data for Automatic Brain Tumor Segmentation
Daniel Santak Wolf, Sebastian Regnery, Rafal Tarnawski, Barbara Bobek-Billewicz, Joanna Polańska, Michael Götz
MDPI Applied Sciences, 2022
Paper
Deep Neural Networks and Machine Learning Radiomics Modelling for Prediction of Relapse in Mantle Cell Lymphoma
Catharina Silvia Lisson, Christoph Gerhard Lisson, Marc Fabian Mezger, Daniel Santak Wolf, Stefan Andreas Schmidt, Wolfgang M Thaiss, Eugen Tausch, Ambros J Beer, Stephan Stilgenbauer, Meinrad Beer, Michael Götz
MDPI Cancers, 2022
Paper
Longitudinal CT Imaging to Explore the Predictive Power of 3D Radiomic Tumour Heterogeneity in Precise Imaging of Mantle Cell Lymphoma (MCL)
Catharina Silvia Lisson, Christoph Gerhard Lisson, Sherin Achilles, Marc Fabian Mezger, Daniel Santak Wolf, Stefan Andreas Schmidt, Wolfgang M Thaiss, Johannes Bloehdorn, Ambros J Beer, Stephan Stilgenbauer, Meinrad Beer, Michael Götz
MDPI Cancers, 2022
Paper
Combining Deep Learning and Radiomics for Automated, Objective, Comprehensive Bone Marrow Characterization from Whole-Body MRI: A Multicentric Feasibility Study
Markus Wennmann, André Klein, Fabian Bauer, Jiri Chmelik, Martin Grözinger, Charlotte Uhlenbrock, et al., Michael Götz, et al.
Investigative Radiology, 2022
Paper
Deep Learning on Lossily Compressed Pathology Images: Adverse Effects for ImageNet Pre-Trained Models
Maximilian Fischer, Peter F. Neher, Michael Götz, Shuhan Xiao, Silvia Dias Almeida, Peter Schüffler, Alexander Muckenhuber, Rickmer Braren, Jens Kleesiek, Marco Nolden, Klaus H. Maier-Hein
MICCAI Workshop on Medical Optical Imaging and Virtual Microscopy (MOVI), 2022
Paper
DICOM Whole Slide Imaging for Computational Pathology Research in Kaapana and the Joint Imaging Platform
Maximilian Fischer, Philipp Schader, Rickmer Braren, Michael Götz, Alexander Muckenhuber, Wilko Weichert, Peter Schüffler, Jens Kleesiek, Jonas Scherer, Klaus Kades, Klaus H. Maier-Hein, Marco Nolden
BVM Workshop, 2022
Paper
MR-Based Liver Iron Quantification Using Gradient Echo: Co-Factors Influencing the Calibration of R 2* with Reference Liver Iron Content Values
Arthur Wunderlich, Holger Cario, Stephan Kannengießer, Lena Hering, Michael Götz, Meinrad Beer, Stefan Schmidt
Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM), 2022
Paper
3D Multi-Echo GRE MRI of the Whole Liver: First Experiences of a Volumetric Segment-by-Segment R 2* Analysis
Arthur Wunderlich, Holger Cario, Stephan Kannengießer, Veronika Grunau, Michael Götz, Meinrad Beer, Stefan Schmidt
Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM), 2022
Paper
2018
Correlation between Genomic Index Lesions and mpMRI and 68Ga-PSMA-PET/CT Imaging Features in Primary Prostate Cancer
Claudia Kesch, Jan-Philipp Radtke, Axel Wintsche, Manuel Wiesenfarth, Mariska Luttje, Claudia Gasch, et al., Michael Götz, et al.
Nature Scientific Reports, 2018
Paper
Radiomic Machine Learning for Characterization of Prostate Lesions with MRI: Comparison to ADC Values
David Bonekamp, Simon Kohl, Manuel Wiesenfarth, Patrick Schelb, Jan Philipp Radtke, Michael Götz, et al.
Radiology, 2018
Paper
Early Postoperative Delineation of Residual Tumor after Low-Grade Glioma Resection by Probabilistic Quantification of Diffusion-Weighted Imaging
Moritz Scherer, Christine Jungk, Michael Götz, Philipp Kickingereder, David Reuss, Martin Bendszus, Klaus H. Maier-Hein, Andreas Unterberg
Journal of Neurosurgery, 2018
Paper
Results from the Image Biomarker Standardisation Initiative
Alex Zwanenburg, Mahmoud A. Abdalah, Aditya Apte, Saeed Ashrafinia, Jorn Beukinga, et al., Michael Götz, et al.
Radiotherapy and Oncology, 2018
Paper
Bi-institutioneller Vergleich manueller mit automatisch durch ein Adversarial Neural Network erstellten Prostatasegmentationen
David Bonekamp, Tobias Penzkofer, Simon Kohl, Alexander Baur, Jan Philipp Radtke, et al., Michael Götz, et al.
RöFo-Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, 2018
Paper
Correlation between Genomic Index Lesions, Multi-Parametric MRI and 68Ga-PSMA-PET/CT Imaging Features in Primary Prostate Cancer
Claudia Kesch, Jan P. Radtke, Axel Wintsche, Manuel Wiesenfarth, Mariska Luttje, Claudia Gasch, et al., Michael Götz, et al.
Journal of Urology, 2018
Paper
2017
Prediction of Malignancy by a Radiomic Signature from Contrast Agent‐Free Diffusion MRI in Suspicious Breast Lesions Found on Screening Mammography
Sebastian Bickelhaupt, Daniel Paech, Philipp Kickingereder, Franziska Steudle, Wolfgang Lederer, Heidi Daniel, Michael Götz, Nils Gählert, Diana Tichy, Manuel Wiesenfarth, Frederik B. Laun, Klaus H. Maier‐Hein, Heinz‐Peter Schlemmer, David Bonekamp
Journal of Magnetic Resonance Imaging, 2017
Paper
MiMSeg-An Algorithm for Automated Detection of Tumor Tissue on NMR Apparent Diffusion Coefficient Maps
Franciszek Binczyk, Bram Stjelties, Christian Weber, Michael Götz, Klaus Meier-Hein, Hans-Peter Meinzer, Barbara Bobek-Billewicz, Rafal Tarnawski, Joanna Polanska
Information Sciences, 2017
Paper
Vergleich von Radiomics, quantitativen ADC Messungen und PI-RADS zur Detektion des signifikanten Prostatakarzinoms
David Bonekamp, David Bonekamp, Boris Hadaschik, Manuel Wiesenfarth, Kathrin Wieczorek, Michael Götz, Heinz-Peter Schlemmer, Klaus H. Maier-Hein
RöFo-Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, 2017
Paper
ISLES 2015-A Public Evaluation Benchmark for Ischemic Stroke Lesion Segmentation from Multispectral MRI
Oskar Maier, Bjoern H. Menze, Janina von der Gablentz, Levin Häni, Mattias P. Heinrich, Matthias Liebrand, et al., Michael Götz, et al.
Medical Image Analysis, 2017
Paper
Physiological Parameter Estimation from Multispectral Images Unleashed
Sebastian J. Wirkert, Anant S. Vemuri, Hannes G. Kenngott, Sara Moccia, Michael Götz, Benjamin F. B. Mayer, Klaus H. Maier-Hein, Daniel S. Elson, Lena Maier-Hein
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2017
Paper
2016
Large-Scale Radiomic Profiling of Recurrent Glioblastoma Identifies an Imaging Predictor for Stratifying Anti-Angiogenic Treatment Response
Philipp Kickingereder, Michael Götz, John Muschelli, Antje Wick, Ulf Neuberger, Russell T. Shinohara, Martin Sill, Martha Nowosielski, Heinz-Peter Schlemmer, Alexander Radbruch, Wolfgang Wick, Martin Bendszus, Klaus H. Maier-Hein, David Bonekamp
Clinical Cancer Research, 2016
Paper
Development and Validation of an Automatic Segmentation Algorithm for Quantification of Intracerebral Hemorrhage
Moritz Scherer, Jonas Cordes, Alexander Younsi, Yasemin-Aylin Sahin, Michael Götz, Markus Möhlenbruch, Christian Stock, Julian Bösel, Andreas Unterberg, Klaus H. Maier-Hein, Berk Orakcioglu
Stroke, 2016
Paper
Crowd-Algorithm Collaboration for Large-Scale Endoscopic Image Annotation with Confidence
Lena Maier-Hein, Tobias Ross, Janek Gröhl, Ben Glocker, Sebastian Bodenstedt, Christian Stock, Eric Heim, Michael Götz, Sebastian Wirkert, Hannes Kenngott, Stefanie Speidel, Klaus H. Maier-Hein
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2016
Paper
Radiomic Profiling of Glioblastoma: Identifying an Imaging Predictor of Patient Survival with Improved Performance over Established Clinical and Radiologic Risk Models
Philipp Kickingereder, Sina Burth, Antje Wick, Michael Götz, Oliver Eidel, Heinz-Peter Schlemmer, Klaus H. Maier-Hein, Wolfgang Wick, Martin Bendszus, Alexander Radbruch, David Bonekamp
Radiology, 2016
Paper
Toward Cognitive Pipelines of Medical Assistance Algorithms
Patrick Philipp, Maria Maleshkova, Darko Katic, Christian Weber, Michael Götz, Achim Rettinger, Stefanie Speidel, Benedikt Kämpgen, Marco Nolden, Anna-Laura Wekerle, Rüdiger Dillmann, Hannes Kenngott, Beat Müller, Rudi Studer
International Journal of Computer Assisted Radiology and Surgery, 2016
Paper
Prostata-MRT vor radikaler Prostatektomie: Radiomics-Parameter zur Differenzierung von primärem Gleason Pattern 3 von hochgradigem Prostatakarzinom
David Bonekamp, Philipp Kickingereder, Boris Hadaschik, Jan Philipp Radtke, Michael Götz, Klaus H. Maier-Hein, Matthias Röthke, Markus Hohenfellner, Heinz-Peter Schlemmer
RöFo-Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, 2016
Paper
Machine-Learning Based Comparison of CT-Perfusion Maps and Dual Energy CT for Pancreatic Tumor Detection
Michael Götz, Stephan Skornitzke, Christian Weber, Franziska Fritz, Philipp Mayer, Marco Koell, Wolfram Stiller, Klaus H. Maier-Hein
SPIE Medical Imaging Conference (SPIE MI), 2016
Paper
A Learning-Based, Fully Automatic Liver Tumor Segmentation Pipeline Based on Sparsely Annotated Training Data
Michael Götz, Eric Heim, Keno Maerz, Tobias Norajitra, Mohammadreza Hafezi, Nassim Fard, Arianeb Mehrabi, Max Knoll, Christian Weber, Lena Maier-Hein, Klaus H. Maier-Hein
SPIE Medical Imaging Conference (SPIE MI), 2016
Paper
Fallspezifisches Lernen zur automatischen Läsionssegmentierung in multimodalen MR-Bildern
Michael Götz, Christoph Kolb, Christian Weber, Sebastian Regnery, Klaus H. Maier-Hein
BVM Workshop, 2016
Paper
Similarity Based Fusion of Multiple Regions of Interests for MR Sequence Evaluation
Michael Götz, Christian Weber, Klaus H. Maier-Hein
Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM), 2016
DALSA: Domain Adaptation for Supervised Learning from Sparsely Annotated MR Images
Michael Götz, Christian Weber, Franciszek Binczyk, Joanna Polanska, Rafal Tarnawski, Barbara Bobek-Billewicz, Ullrich Koethe, Jens Kleesiek, Bram Stieltjes, Klaus H. Maier-Hein
IEEE Transactions on Medical Imaging, 2016
Paper
2015
Input Data Adaptive Learning (IDAL) for Sub-Acute Ischemic Stroke Lesion Segmentation
Michael Götz, Christian Weber, Christoph Kolb, Klaus H. Maier-Hein
MICCAI Brainlesion Workshop (BrainLes), 2015
Paper
A Machine Learning Based Approach to Fiber Tractography Using Classifier Voting
Peter F. Neher, Michael Götz, Tobias Norajitra, Christian Weber, Klaus H. Maier-Hein
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2015
Paper
Automatisierung von Vorverarbeitungsschritten für medizinische Bilddaten mit semantischen Technologien
Patrick Philipp, Maria Maleshkova, Michael Götz, Christian Weber, Benedikt Kämpgen, Sascha Zelzer, Klaus H. Maier-Hein, Miriam Klauß, Achim Rettinger
BVM Workshop, 2015
Paper
Überwachtes Lernen zur Prädiktion von Tumorwachstum
Christian Weber, Michael Götz, Franciszek Binczyck, Joanna Polanska, Rafal Tarnawski, Barbara Bobek-Billewicz, Hans-Peter Meinzer, Bram Stieltjes, Klaus H. Maier-Hein
BVM Workshop, 2015
Paper
Automatische Tumorsegmentierung mit spärlich annotierter Lernbasis
Michael Götz, Christian Weber, Franciszek Binczyck, Joanna Polanska, Rafal Tarnawski, Barbara Bobek-Billewicz, Hans-Peter Meinzer, Bram Stieltjes, Klaus H. Maier-Hein
BVM Workshop, 2015
Paper
A Machine Learning Based Approach to Fiber Tractography
Peter F. Neher, Michael Götz, Tobias Norajitra, Christian Weber, Klaus H. Maier-Hein
Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM), 2015
2014
Using Linked Data and Web APIs for Automating the Pre-Processing of Medical Images
Philipp Gemmeke, Maria Maleshkova, Patrick Philipp, Michael Götz, Christian Weber, Benedikt Kämpgen, et al.
International Workshop on Consuming Linked Data (COLD), 2014
Paper
Analysis of Mitral Valve Motion in 4D Transesophageal Echocardiography for Transcatheter Aortic Valve Implantation
Frank M. Weber, Thomas Stehle, Irina Waechter-Stehle, Michael Götz, Jochen Peters, Sabine Mollus, et al.
MICCAI Workshop on Statistical Atlases and Computational Models of the Heart (STACOM), 2014
Paper
Brain Tumor Progression Modeling-A Data Driven Approach
Christian Weber, Michael Götz, Bram Stieltjes, Joanna Polanska, Franciszek Binczyk, Rafal Tarnawski, Barbara Bobek-Billewicz, Klaus H. Maier-Hein
The MIDAS Journal, 2014
Paper
Learning from Small Amounts of Labeled Data in a Brain Tumor Classification Task
Michael Götz, Christian Weber, Bram Stieltjes, Klaus H. Maier-Hein
NeurIPS Workshop on Transfer and Multi-Task Learning, 2014
Paper
Extremely Randomized Trees Based Brain Tumor Segmentation
Michael Götz, Christian Weber, J Bloecher, Bram Stieltjes, Hans-Peter Meinzer, Klaus H. Maier-Hein
MICCAI Brain Tumor Segmentation Challenge (BraTS), 2014
Paper