MIDL 2021

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

Home | Publications | back
Export 125 results:
Sort by: Author Title [ Year (Desc)]
Filters: Author is Heinrich, Mattias P.  [Clear All Filters]
In Press
Bigalke A., Hansen L., Heinrich M.P.
End-to-end learning of body weight prediction from point clouds with basis point sets
In: Bildverarbeitung für die Medizin 2021, In Press
Hansen L., Heinrich M.P.
PDD networks for medical image registration - Contributions to the Learn2Reg challenge
In: Bildverarbeitung für die Medizin 2021, In Press
Kruse C., Hansen L., Heinrich M.P.
Multi-modal unsupervised domain adaptation for deformable registration based on maximum classifier discrepancy
In: Bildverarbeitung für die Medizin 2021, In Press
Schumacher M., Frey D., Ha I.Y., Genz A., Bade R., Heinrich M.P.
Semantically Guided 3D Abdominal Image Registration with Deep Pyramid Feature Learning
In: Bildverarbeitung für die Medizin 2021, In Press
Siebert H., Hansen L., Heinrich M.P.
Architecture matters: evaluating design choices for deep learning registration networks
In: Bildverarbeitung für die Medizin 2021, In Press
Siebert H., Rajamani K.T., Heinrich M.P.
Learning inverse consistent 3D groupwise registration with deforming autoencoders
In: SPIE Medical Imaging 2021, In Press
2021
Blendowski M., Hansen L., Heinrich M.P.
Weakly-supervised learning of multi-modal features for regularised iterative descent in 3D image registration
Medical Image Analysis, 67, 101822, 2021
2020
Bartram L., Dedersen B., Heinrich M.P.
Development of a Deep Learning based classification of respirator masks for a mobile application
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, 193-196, 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., 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.
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
Boudnik L., Hochreiter J., Müllegger G., Heinrich M.P.
Removal of ECG artifacts caused by mechanical CPR using externally recorded compression markers
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, 323-326, 2020
Buzug T.M., Handels H., Klein S., Mertins A. (eds.)
Student Conference Proceedings 2020: 9th Conference on Medical Engineering Science and 5th Conference on Medical Informatics and 3rd Conference on Biomedical Engineering and 2nd Conference on Auditory Technology
Infinite Science Publishing, Lübeck, 2020
Gillner M.L., Hansen L., Heinrich M.P.
Fast Pulmonary Fissure Detection in CT Scans using Deep Learning on Point Clouds
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, 201-204, 2020
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
Ha I.Y., Wilms M., Heinrich M.P.
Semantically Guided Large Deformation Estimation with Deep Networks
Sensors, 20, 5, 1392, 2020
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., Hansen L.
Highly Accurate and Memory Efficient Unsupervised Learning-Based Discrete CT Registration Using 2.5D Displacement Search
In: Medical Image Computing and Computer Assisted Intervention – MICCAI 2020, Cham, Springer, 12263, 190-200, 2020
Heinrich M.P., Papież B.W.
Image registration with sliding motion
In: Handbook of Medical Image Computing and Computer Assisted Intervention, The Elsevier and MICCAI Society Book Series, 293-318, 2020
Heinrich M.P., Hansen L.
Unsupervised learning of multimodal image registration using domain adaptation with projected Earth Mover’s discrepancies
In: International Conference on Medical Imaging with Deep Learning, 2020
Herrmann S., Schneider D., Mrongowius J., Heinrich M.P.
Aortic Detection in Image Sequences of Electrical Impedance Tomography
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, 335-338, 2020
Kepp T., Sudkamp H., von der Burchard C., Schenke H., Koch P., Hüttmann G., Roider J., Heinrich M.P., Handels H.
Segmentation of Retinal Low-Cost Optical Coherence Tomography Images Using Deep Learning
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, 183, 2020
Kepp T., Sudkamp H., von der Burchard C., Schenke H., Koch P., Hüttmann G., Roider J., Heinrich M.P., Handels H.
Segmentation of Retinal Low-Cost Optical Coherence Tomography Images using Deep Learning
In: SPIE Medical Imaging 2020, Houston, USA, 2020
Keuth R., Hansen L., Heinrich M.P.
Der Einfluss von Segmentierung auf die Genauigkeit eines CNN-Klassifikators zur Mimik-Steuerung
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, 294-300, 2020
Lucas C., Aulmann L.F., Kemmling A., Mamlouk A.M., Heinrich M.P.
Estimation of the Principal Ischaemic Stroke Growth Directions for Predicting Tissue Outcomes
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, 143, 2020
Lucas C., Aulmann L.F., Kemmling A., Mamlouk A.M., Heinrich M.P.
Estimation of the Principal Ischaemic Stroke Growth Directions for Predicting Tissue Outcomes
In: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2019, 69-79, 2020
Rüttgers S., Hocke J., Heinrich M.P.
Automatic segmentation of prostate zones in MRI data using different variants of the U-Net
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, 169-172, 2020
Schumacher M., Genz A., Heinrich M.P.
Weakly supervised pancreas segmentation based on class activation maps
In: SPIE Medical Imaging 2020: Image Processing, Houston, United States, 11313, 1131314, 2020
Siebert H., Heinrich M.P.
Deep Groupwise Registration of MRI Using Deforming Autoencoders
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, 236-241, 2020
Sirocko J., Diesel J., Heinrich M.P.
Frequency based detection of regions of interest in videodata to estimate human breathing frequency
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, 177-180, 2020
2019
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., 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
Bockelmann N., Graßhoff J., Hansen L., Bellani G., Heinrich M.P., Rostalski P.
Deep Learning for Prediction of Diaphragm Activity from the Surface Electromyogram
Current Directions in Biomedical Engineering, 5, 1, 17-20, 2019
Bockelmann N., Krüger D., Moosmann J., Heinrich M.P.
U-Net-based Segmentation of Biodegradable Bone Implants in Synchrotron Radiation Microtomograms with Sparse Annotations
In: Buzug T.M., Handels H., Klein S., Mertins A. (eds.), Student Conference 2019, Medical Engineering Science, Medical Informatics, Biomedical Engineering and Auditory Technology, Lübeck, Infinite Science Publishing, 145-148, 2019
Bouteldja N., Merhof D., Ehrhardt J., Heinrich M.P.
Deep Multi-Modal Encoder-Decoder Networks for Shape Constrained Segmentation and Joint Representation Learning
In: Handels H., Deserno T.M., Maier A., Maier-Hein K.H., Palm C., Tolxdorff T. (eds.), Bildverarbeitung für die Medizin 2019, Lübeck, Informatik aktuell, Springer Vieweg, Wiesbaden, 23-28, 2019
Buzug T.M., Handels H., Klein S., Mertins A. (eds.)
Student Conference Proceedings 2019: 8th Conference on Medical Engineering Science and 4th Conference on Medical Informatics and 2nd Conference on Biomedical Engineering and 1st Conference on Auditory Technology
Infinite Science Publishing, Lübeck, 2019
Ha I.Y., Wilms M., Handels H., Heinrich M.P.
Model-based Sparse-to-dense Image Registration for Realtime Respiratory Motion Estimation in Image-guided Interventions
IEEE Transactions on Biomedical Engineering, 66, 2, 302-310, 2019
PDF
Hagenah J., Heinrich M.P., Ernst F.
Deep Transfer Learning for Aortic Root Dilation Identification in 3D Ultrasound Images
In: Handels H., Deserno T.M., Maier A., Maier-Hein K.H., Palm C., Tolxdorff T. (eds.), Bildverarbeitung für die Medizin 2019, Lübeck, Informatik aktuell, Springer Vieweg, Wiesbaden, 198, 2019
Hansen L., Siebert M., Diesel J., Heinrich M.P.
Fusing information from multiple 2D depth cameras for 3D human pose estimation in the operating room
International Journal of Computer Assisted Radiology and Surgery, 14, 11, 1871-1879, 2019
Hansen L., Dittmer D., Heinrich M.P.
Learning Deformable Point Set Registration with Regularized Dynamic Graph CNNs for Large Lung Motion in COPD Patients
In: Graph Learning in Medical Imaging. GLMI 2019, Cham, Lecture Notes in Computer Science, Springer, 11849, 53-61, 2019
Hansen L., Diesel J., Heinrich M.P.
Multi-Kernel Diffusion CNNs for Graph-Based Learning on Point Clouds
In: Computer Vision – ECCV 2018 Workshops, Cham, Lecture Notes in Computer Science, Springer, 11131, 4413, 456-469, 2019
Hansen L., Diesel J., Heinrich M.P.
Regularized Landmark Detection with CAEs for Human Pose Estimation in the Operating Room
In: Handels H., Deserno T.M., Maier A., Maier-Hein K.H., Palm C., Tolxdorff T. (eds.), Bildverarbeitung für die Medizin 2019, Lübeck, Informatik aktuell, Springer Vieweg, Wiesbaden, 178-183, 2019
Hansen L., Heinrich M.P.
Sparse Structured Prediction for Semantic Edge Detection in Medical Images
In: International Conference on Medical Imaging with Deep Learning, PMLR, 102, 250-259, 2019
Heinrich M.P.
Closing the Gap Between Deep and Conventional Image Registration Using Probabilistic Dense Displacement Networks
In: Medical Image Computing and Computer Assisted Intervention – MICCAI 2019, Cham, LNCS, Springer, 11769, 50-58, 2019
Heinrich M.P., Oktay O., Bouteldja N.
OBELISK-Net: Fewer layers to solve 3D multi-organ segmentation with sparse deformable convolutions
Medical Image Analysis, 54, 1-9, 2019
Hering A., Kuckertz S., Heldmann S., Heinrich M.P.
Enhancing Label-Driven Deep Deformable Image Registration with Local Distance Metrics for State-of-the-Art Cardiac Motion Tracking
In: Handels H., Deserno T.M., Maier A., Maier-Hein K.H., Palm C., Tolxdorff T. (eds.), Bildverarbeitung für die Medizin 2019, Lübeck, Informatik aktuell, Springer Vieweg, Wiesbaden, 309-314, 2019
Hering A., Kuckertz S., Heldmann S., Heinrich M.P.
Memory-efficient 2.5D convolutional transformer networks for multi-modal deformable registration with weak label supervision applied to whole-heart CT and MRI scans
International Journal of Computer Assisted Radiology and Surgery, 14, 11, 1901-1912, 2019
Kepp T., Droigk C., Casper M., Evers M., Hüttmann G., Salma N., Manstein D., Heinrich M.P., Handels H.
Segmentation of Mouse Skin Layers in Optical Coherence Tomography Image Data using Deep Convolutional Neural Networks
Biomedical Optics Express, 10, 7, 3484-3496, 2019
Kepp T., Ehrhardt J., Heinrich M.P., Hüttmann G., Handels H.
Topology-Preserving Shape-Based Regression of Retinal Layers in OCT Image Data Using Convolutional Neural Networks
In: IEEE International Symposium on Biomedical Imaging, ISBI 2019, Venedig, Italien, 1437-1440, 2019
PDF
Lucas C., Schöttler J.J., Kemmling A., Aulmann L.F., Heinrich M.P.
Automatic Detection and Segmentation of the Acute Vessel Thrombus in Cerebral CT
In: Handels H., Deserno T.M., Maier A., Maier-Hein K.H., Palm C., Tolxdorff T. (eds.), Bildverarbeitung für die Medizin 2019, Lübeck, Informatik aktuell, Springer Vieweg, Wiesbaden, 74-79, 2019

Languages

Program of Study

Study Medical Informatics
at the University of Lübeck

read more ...

Address

Office
Susanne Petersen

Tel+49 451 3101 5601
Fax+49 451 3101 5604


Ratzeburger Allee 160
23538 Lübeck
Germany
Contact · Impress · Log-In
Copyright © Institut für Medizinische Informatik. All Rights Reserved.

Powered by Drupal and Drupal Theme created with Artisteer by Dr. Wrage.