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Globally Optimal Deformable Registration on a Minimum Spanning Tree Using Dense Displacement Sampling.

M. Heinrich, M. Jenkinson, M. Brady, and J. Schnabel. MICCAI (3), volume 7512 of Lecture Notes in Computer Science, page 115-122. Springer, (2012)

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Mattias Krüger

Mattias Kreutz

Mattias Martinson

Heinrich P Dröge

Heinrich P Koch

Other publications of authors with the same name

GraphRegNet: Deep Graph Regularisation Networks on Sparse Keypoints for Dense Registration of 3D Lung CTs.L. Hansen, and M. Heinrich. IEEE Trans. Medical Imaging, 40 (9): 2246-2257 (2021)Anatomy-guided domain adaptation for 3D in-bed human pose estimation.A. Bigalke, L. Hansen, J. Diesel, C. Hennigs, P. Rostalski, and M. Heinrich. Medical Image Anal., (October 2023)Attention gated networks: Learning to leverage salient regions in medical images.J. Schlemper, O. Oktay, M. Schaap, M. Heinrich, B. Kainz, B. Glocker, and D. Rueckert. Medical Image Anal., (2019)Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge.X. Zhuang, L. Li, C. Payer, D. Stern, M. Urschler, M. Heinrich, J. Oster, C. Wang, Ö. Smedby, C. Bian and 9 other author(s). Medical Image Anal., (2019)Multimodal 3D medical image registration guided by shape encoder-decoder networks.M. Blendowski, N. Bouteldja, and M. Heinrich. Int. J. Comput. Assist. Radiol. Surg., 15 (2): 269-276 (2020)Evaluation of Six Registration Methods for the Human Abdomen on Clinically Acquired CT.Z. Xu, C. Lee, M. Heinrich, M. Modat, D. Rueckert, S. Ourselin, R. Abramson, and B. Landman. IEEE Trans. Biomed. Eng., 63 (8): 1563-1572 (2016)Self-supervised Learning of Dense Hierarchical Representations for Medical Image Segmentation.E. Kats, J. Hirsch, and M. Heinrich. CoRR, (2024)Automatic Generation of Synthetic Colonoscopy Videos for Domain Randomization.A. Jagtap, M. Heinrich, and M. Himstedt. CoRR, (2022)DeepSTAPLE: Learning to Predict Multimodal Registration Quality for Unsupervised Domain Adaptation.C. Weihsbach, A. Bigalke, C. Kruse, H. Hempe, and M. Heinrich. WBIR, volume 13386 of Lecture Notes in Computer Science, page 37-46. Springer, (2022)Chasing clouds: Differentiable volumetric rasterisation of point clouds as a highly efficient and accurate loss for large-scale deformable 3D registration.M. Heinrich, A. Bigalke, C. Großbröhmer, and L. Hansen. ICCV, page 7992-8002. IEEE, (2023)

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Disambiguation of "Heinrich, Mattias P."

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Globally Optimal Deformable Registration on a Minimum Spanning Tree Using Dense Displacement Sampling.

Please choose a person to relate this publication to

Mattias Krüger

Mattias Kreutz

Mattias Martinson

Heinrich P Dröge

Heinrich P Koch

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Heinrich, Mattias P."

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Globally Optimal Deformable Registration on a Minimum Spanning Tree Using Dense Displacement Sampling.

Please choose a person to relate this publication to

Mattias Krüger

Mattias Kreutz

Mattias Martinson

Heinrich P Dröge

Heinrich P Koch

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
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Globally Optimal Deformable Registration on a Minimum Spanning Tree Using Dense Displacement Sampling.