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Automatic Correspondence Detection in Mammogram and Breast Tomosynthesis Images
In: Image Processing, SPIE Medical Imaging 2012, San Diego, California, USA, SPIE, 8314, 831421-1-831421-8, 2012

Automatische Bestimmung von 2D/3D-Korrespondenzen in Mammographie- und Tomosynthese-Bilddaten
In: (eds.), Bildverarbeitung für die Medizin 2012, Informatik aktuell, Berlin, Springer, Berlin Heidelberg, 99-104, 2012
Bayesian Inference for Uncertainty Quantification in Point-based Deformable Image Registration
In: SPIE 10949, Medical Imaging 2019: Image Processing, San Diego, USA, 10949, 109491S-1-109491S-8, 2019
Breast Compression Simulation Using ICP-Based B-Spline Deformation for Correspondence Analysis in Mammography and MRI Datasets
In: (eds.), Image Processing, SPIE Medical Imaging 2013, Orlando, USA, SPIE, 8669-48,1D1-1D8, 2013

An Efficient Implementation of an Affine Point-based Registration using the Expectation Maximization-ICP in C++
In: (eds.), Student Conference 2015, Medical Engineering Science, Lübeck, 211-214, 2015
Estimation of corresponding locations in ipsilateral mammograms: a comparison of different methods
In: (eds.), SPIE Medical Imaging 2015: Computer-Aided Diagnosis, Orlando, Florida, United States, SPIE, 9414, 94142B, 2015

Evaluation of a B-Spline-Based Breast Compression Simulation for Correspondence Analysis between MRI and Mammographic Image Data
In: Workshop on Breast Image Analysis - In conjunction with the 16th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2013), Nagoya, Japan, 17-24, 2013
Mammo3D - Automatic Determination of Corresponding Structures in 2D/3D Image Data of the Female Breast for Multimodal Breast Cancer Diagnosis
In: 15th Korea-Germany Workshop on Advanced Medical Image Analysis and Cognition-Guided Surgery, Ajou University, Suwon, Korea, 30, 2014
A Maximum-A-Posteriori Framework for Statistical Appearance Models with Probabilistic Correspondences
In: Bayesian an grAphical Models for Biomedical Imaging 2015 (MICCAI 2015), 2015
Multi-level approach for statistical appearance models with probabilistic correspondences
In: (eds.), SPIE Medical Imaging 2016: Image Processing, San Diego, California, United States, SPIE, 9784, 978433-978433-6, 2016
Probabilistic Appearance Models for Medical Image Analysis
In: (eds.), Bildverarbeitung für die Medizin 2018, Erlangen, Informatik aktuell, Springer Vieweg, Berlin Heidelberg, 37-38, 2018
Probabilistic Appearance Models for Segmentation and Classification
In: International Conference on Computer Vision - ICCV 2015, Santiago de Chile, Chile, 1698-1706, 2015
A Probabilistic Approach for the Registration of Images with Missing Correspondences
In: SPIE 10949, Medical Imaging 2019: Image Processing, San Diego, USA, 10949, 1094925-1-10949251-8, 2019
Probabilistic Shape and Appearance Models without One-to-One Correspondences
In: 1st Symposium on Statistical Shape Models and Applications, Shape 2014, Delemont, Switzerland, Proceedings, 22, 2014
Registration with probabilistic correspondences — Accurate and robust registration for pathological and inhomogeneous medical data
Computer Vision and Image Understanding, 190, 102839, 2020
Simulation mammographischer Brustkompression zur Generierung von MRT-Projektionsbildern
In: (eds.), Bildverarbeitung für die Medizin, BVM 2013, Heidelberg, Informatik aktuell, Springer Verlag, Berlin, 146-151, 2013

Simulation of Mammographic Breast Compression in 3D MR Images Using ICP-Based B-Spline Deformation for Multimodality Breast Cancer Diagnosis
International Journal of Computer Assisted Radiology and Surgery, 9, 3, 367-377, 2014
Statistical appearance models based on probabilistic correspondences
Medical Image Analysis, 37, 146-159, 2017
Statistical Shape and Appearance Models without One-to-One Correspondences
In: (eds.), SPIE Medical Imaging 2014, Image Processing, San Diego, USA, 9034, 90340U, 2014