Filters: Author is Maximilian Blendowski [Clear All Filters]
A Diffeomorphic Framework for Surrogate-based Motion Estimation in Radiation Therapy: Concept and First Evaluation
In: (eds.), Informatik 2012, Lecture Notes in Informatics, Braunschweig, 1774-1782, 2012
A Diffeomorphic MLR Framework for Surrogate-Based Motion Estimation and Situation-Adapted Dose Accumulation
In: (eds.), MICCAI Workshop on Image-Guidance and Multimodal Dose Planning in Radiation Therapy, MICCAI 2012, Nizza, Frankreich, 42-49, 2012
Simulation of Range-Imaging-Based Prediction of Respiratory Organ and Tumor Motion Using 4D CT Data: Influence of Signal Dimensionality and Sampling Patterns
In: (eds.), 58. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS), Lübeck, Abstractband GMDS 2013, ID118:216-217, 2013
Simulation und Evaluation tiefenbildgebender Verfahren zur Prädiktion atmungsbedingter Organ- und Tumorbewegungen
In: (eds.), Bildverarbeitung für die Medizin, BVM 2013, Heidelberg, Informatik aktuell, Springer Verlag, Berlin, 350-355, 2013

Surrogate-Based Diffeomorphic Motion Estimation for Radiation Therapy: Comparison of Multivariate Regression Approaches
In: (eds.), SPIE Medical Imaging 2013, Image Processing, Orlando, USA, 8669-40,151-158, 2013

Simulation of Range Imaging-Based Estimation of Respiratory Lung Motion: Influence of Noise, Signal Dimensionality and Sampling Patterns
Methods of Information in Medicine, 53, 4, 257-263, 2014
Multi-Organ Segmentation using Vantage Point Forests and Binary Context Features
In: 19th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2016, Athen, Springer, 598-606, 2016

Kombination binärer Kontextfeatures mit Vantage Point Forests zur Multi-Organ-Segmentierung
In: (eds.), Bildverarbeitung für die Medizin 2017, Heidelberg, Informatik aktuell, Springer Vieweg, Berlin Heidelberg, 24-24, 2017
3D-CNNs for Deep Binary Descriptor Learning in Medical Volume Data
In: (eds.), Bildverarbeitung für die Medizin 2018, Erlangen, Informatik aktuell, Springer Vieweg, Berlin, Heidelberg, 23-28, 2018
Classification of axial CT Images using Deep Learning for determining a Standard Coordinate System
In: (eds.), Student Conference 2018, Medical Engineering Science, Medical Informatics and Biomediacal Engineering, Lübeck, Infinite Science Publishing, 247-250, 2018
TernaryNet: Faster Deep Model Inference without GPUs for Medical 3D Segmentation using Sparse and Binary Convolutions
International Journal of Computer Assisted Radiology and Surgery, 13, 9, 1311-1320, 2018
Transferring a Deep Cityscape Synthesis Approach to the Medical Domain
In: (eds.), Student Conference 2018, Medical Engineering Science, Medical Informatics and Biomediacal Engineering, Lübeck, Infinite Science Publishing, 91-94, 2018
Combining MRF-based Deformable Registration and Deep Binary 3D-CNN Descriptors for Large Lung Motion Estimation in COPD Patients
International Journal of Computer Assisted Radiology and Surgery, 14, 1, 43-52, 2019
Learning Interpretable Multi-modal Features for Alignment with Supervised Iterative Descent
In: International Conference on Medical Imaging with Deep Learning, PMLR, 102, 73-83, 2019
Learning to map between ferns with differentiable binary embedding networks
In: International Conference on Medical Imaging with Deep Learning, PMLR, 2020
Multimodal 3D medical image registration guided by shape encoder–decoder networks
International Journal of Computer Assisted Radiology and Surgery, 15, 269-276, 2020
Self-Supervised 3D Context Feature Learning on Unlabeled Volume Data
In: (eds.), Bildverarbeitung für die Medizin 2020, Berlin, Informatik aktuell, Springer Vieweg, Wiesbaden, 192, 2020
Efficient Self-Supervised Context Learning on MRI data
In: (eds.), Student Conference 2020, Medical Engineering Science, Medical Informatics, Biomedical Engineering and Auditory Technology, Lübeck, Infinite Science Publishing, 189-192, 2020
Defence of Mathematical Models for Deep Learning based Registration
In: (eds.), Bildverarbeitung für die Medizin 2020, Berlin, Informatik aktuell, Springer Vieweg, Wiesbaden, 32, 2020