@InProceedings{Parbs2022,
   author    = {Tim J. Parbs and Philipp Koch and Alfred Mertins},
   booktitle = {Proc. European Signal Processing Conference},
   title     = {Convolutive Attention for Image Registration},
   year      = {2022},
   address   = {Belgrade, Serbia},
   month     = sep,
   pages     = {1348--1352},
   publisher = {IEEE},
   abstract  = {Elastic registration of deformed images is a vitalcomponent of many computer vision tasks, especially whenconsidering medical image data. Deep learning techniques, particularlyU-Nets, offer state-of-the-art performance, but do notyet use the rich spatial information context available in naturalimages. We propose an augmentation based on the recentlyintroduced attention mechanism to allow a U-Net to use spatialimage context. A dedicated convolutive attention scheme hasbeen developed by calculating local similarity scores of themultidimensional inputs. Additionally, a dedicated compositeerror function based on common image similarity measures isintroduced in order to further improve the registration results.To evaluate our approach, we conducted several experiments onan augmented real-world dataset containing cardiac cine MRIscans. The comparison with state-of-the-art registration schemeshighlights the potential of our approach.}, }

@InProceedings{Koch2021,
  author    = {Koch, Philipp and Mohammad-Zadeh, Kamran and Maass, Marco and Dreier, Mark and Thomsen, Ole and Parbs, Tim J. and Phan, Huy and Mertins, Alfred},
  title     = {sEMG-Based Hand Movement Regression by Prediction of Joint Angles With Recurrent Neural Networks},
  booktitle = {43nd Annual International Conference of the IEEE Engineering in Medicine \& Biology Society (EMBC)},
  year      = {2021},
  pages     = {6519--6523},
doi = {10.1109/EMBC46164.2021.9630042},
}

@InProceedings{Koch2020a,
  author    = {Koch, Philipp and Dreier, Mark and Larsen, Anna and Parbs, Tim J. and Maass, Marco and Phan, Huy and Mertins, Alfred},
  title     = {Regression of Hand Movements from sEMG Data with Recurrent Neural Networks},
  booktitle = {42nd Annual International Conference of the IEEE Engineering in Medicine \& Biology Society (EMBC)},
  year      = {2020},
  pages     = {3783--3787},
}

@INPROCEEDINGS{moeller2019,
author = {Möller, Anita and Maass, Marco and Parbs, Tim Jeldrik and Mertins, Alfred},
title = {Blind Sparsity Based Motion Estimation and Correction Model for Arbitrary MRI Sampling Trajectories},
booktitle = {Proceedings of the 27th {Joint} {Annual} {Meeting} of {ISMRM}},
pages = {4496},
year = {2019},
address = {Montreal, Canada},
month = {May},
url ={https://index.mirasmart.com/ISMRM2019/PDFfiles/4496.html}
}

@inproceedings{koch2019a,
Author = {Koch, P.  and Maass, M. and Bruhns, M. and Droigk, C.  and Parbs, T. J. and Mertins, A.}, 
Title = {Neural Network for Reconstruction of MPI Images}, 
Year = {2019}, 
Pages = {39--40}, 
Booktitle = {9th International Workshop on Magnetic Particle Imaging (IWMPI 2019)}, 
publisher = {Infinite Science Publishing},
address = {New York, USA}, 
month = {March},
}

@InProceedings{MoellerBVM_2019,
author="Möller, Anita and Maass, Marco and Parbs, Tim Jeldrik and Mertins, Alfred",
editor="Handels, Heinz and Deserno, Thomas M. and Maier, Andreas and Maier-Hein, Klaus Hermann and Palm, Christoph
and Tolxdorff, Thomas",
title="Blind Rigid Motion Estimation for Arbitrary MRI Sampling Trajectories",
booktitle="Bildverarbeitung für die Medizin 2019",
year="2019",
publisher="Springer Fachmedien Wiesbaden",
address="Wiesbaden",
pages="128--133",
abstract="In this publication, a new blind motion correction algorithm for magnetic resonance imaging for arbitrary sampling trajectories is presented. Patient motion during partial measurements is estimated. Exploiting the image design, a sparse approximation of the reconstructed image is calculated with the alternating direction method of multipliers. The approximation is used with gradient descent methods with derivatives of a rigid motion model to estimate the motion and extract it from the measured data. Adapted gridding is performed in the end to receive reconstruction images without motion artifacts.",
isbn="978-3-658-25326-4",
doi="10.1007/978-3-658-25326-4_28",
}

@InCollection{parbs2019a,
  author       = {Parbs, Tim J., and M{\"o}ller, Anita and Mertins, Alfred},
  title        = {Retrospective Blind MR Image Recovery with Parameterised Motion Models},
  booktitle    = {Bildverarbeitung f{\"u}r die Medizin 2019},
  publisher    = {Springer Vieweg, Wiesbaden},
  year         = {2019},
  editor       = {Handels, Heinz and Deserno, Thomas Martin and Maier, A. and Maier-Hein, K.H. and Palm, Christoph and Tolxdorff, Thomas},
  series       = {Informatik aktuell},
  pages        = {140 - 145},
  doi          = {10.1007/978-3-658-25326-4_30},
  organization = {Springer Vieweg, Wiesbaden},
}