Publikationen | Institute of Medical Informatics

MIDL 2021

International Conference on
Medical Imaging with Deep Learning
5. bis 7. Juli 2021

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Blendowski M., Wilms M., Werner R., Handels H.
Simulation of Range-Imaging-Based Prediction of Respiratory Organ and Tumor Motion Using 4D CT Data: Influence of Signal Dimensionality and Sampling Patterns
In: Handels H., Ingenerf J. (eds.), 58. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS), Lübeck, Abstractband GMDS 2013, ID118:216-217, 2013

Blendowski M., Heinrich M.P.
Self-Supervised 3D Context Feature Learning on Unlabeled Volume Data
In: Tolxdorff T., Deserno T.M., Handels H., Maier A., Maier-Hein K.H., Palm C. (eds.), Bildverarbeitung für die Medizin 2020, Berlin, Informatik aktuell, Springer Vieweg, Wiesbaden, 192, 2020

Blendowski M., Bouteldja N., Heinrich M.P.
Multimodal 3D medical image registration guided by shape encoder–decoder networks
International Journal of Computer Assisted Radiology and Surgery, 15, 269-276, 2020

Blendowski M., Heinrich M.P.
Learning to map between ferns with differentiable binary embedding networks
In: International Conference on Medical Imaging with Deep Learning, PMLR, 2020

Blendowski M., Heinrich M.P.
Kombination binärer Kontextfeatures mit Vantage Point Forests zur Multi-Organ-Segmentierung
In: Maier-Hein K.H., Deserno T.M., Handels H., Tolxdorff T. (eds.), Bildverarbeitung für die Medizin 2017, Heidelberg, Informatik aktuell, Springer Vieweg, Berlin Heidelberg, 24-24, 2017

Blendowski M., Heinrich M.P.
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

Blendowski M., Wilms M., Werner R., Handels H.
Simulation und Evaluation tiefenbildgebender Verfahren zur Prädiktion atmungsbedingter Organ- und Tumorbewegungen
In: Meinzer H.-P., Deserno T.M., Handels H., Tolxdorff T. (eds.), Bildverarbeitung für die Medizin, BVM 2013, Heidelberg, Informatik aktuell, Springer Verlag, Berlin, 350-355, 2013

Blendowski M., Heinrich M.P.
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

Blendowski M., Heinrich M.P.
3D-CNNs for Deep Binary Descriptor Learning in Medical Volume Data
In: Maier A., Deserno T.M., Handels H., Maier-Hein K.H., Palm C., Tolxdorff T. (eds.), Bildverarbeitung für die Medizin 2018, Erlangen, Informatik aktuell, Springer Vieweg, Berlin, Heidelberg, 23-28, 2018

F

Fleitmann M., Seebaß M., Westerhoff M., Stalling D., Heinrich M.P., Blendowski M.
Classification of axial CT Images using Deep Learning for determining a Standard Coordinate System
In: Buzug T.M., Handels H., Klein S. (eds.), Student Conference 2018, Medical Engineering Science, Medical Informatics and Biomediacal Engineering, Lübeck, Infinite Science Publishing, 247-250, 2018

G

Großbröhmer C., Blendowski M., Heinrich M.P.
Efficient Self-Supervised Context Learning on MRI data
In: Buzug T.M., Handels H., Klein S., Mertins A. (eds.), Student Conference 2020, Medical Engineering Science, Medical Informatics, Biomedical Engineering and Auditory Technology, Lübeck, Infinite Science Publishing, 189-192, 2020

H

Hansen L., Blendowski M., Heinrich M.P.
Defence of Mathematical Models for Deep Learning based Registration
In: Tolxdorff T., Deserno T.M., Handels H., Maier A., Maier-Hein K.H., Palm C. (eds.), Bildverarbeitung für die Medizin 2020, Berlin, Informatik aktuell, Springer Vieweg, Wiesbaden, 32, 2020

Heinrich M.P., Blendowski M., Oktay O.
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

Heinrich M.P., Blendowski M.
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

W

Weller D., Hansen L., Blendowski M., Heinrich M.P.
Transferring a Deep Cityscape Synthesis Approach to the Medical Domain
In: Buzug T.M., Handels H., Klein S. (eds.), Student Conference 2018, Medical Engineering Science, Medical Informatics and Biomediacal Engineering, Lübeck, Infinite Science Publishing, 91-94, 2018

Werner R., Ehrhardt J., Schmidt-Richberg A., Wilms M., Blendowski M., Handels H.
A Diffeomorphic Framework for Surrogate-based Motion Estimation in Radiation Therapy: Concept and First Evaluation
In: Goltz U., Magnor M., Matthies H., Balke W.T., Wolf L. (eds.), Informatik 2012, Lecture Notes in Informatics, Braunschweig, 1774-1782, 2012

Werner R., Wilms M., Ehrhardt J., Schmidt-Richberg A., Blendowski M., Handels H.
A Diffeomorphic MLR Framework for Surrogate-Based Motion Estimation and Situation-Adapted Dose Accumulation
In: Birkfellner W., Mcclelland J., Rit S., Schlaefer A. (eds.), MICCAI Workshop on Image-Guidance and Multimodal Dose Planning in Radiation Therapy, MICCAI 2012, Nizza, Frankreich, 42-49, 2012

Wilms M., Werner R., Ehrhardt J., Schmidt-Richberg A., Blendowski M., Handels H.
Surrogate-Based Diffeomorphic Motion Estimation for Radiation Therapy: Comparison of Multivariate Regression Approaches
In: Ourselin S., Haynor D.R. (eds.), SPIE Medical Imaging 2013, Image Processing, Orlando, USA, 8669-40,151-158, 2013

Wilms M., Werner R., Blendowski M., Ortmüller J., Handels H.
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

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