[MICCAI'18] Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image Sequences
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Updated
Aug 21, 2020 - Python
[MICCAI'18] Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image Sequences
[MICCAI'20] Biomechanics-informed Neural Networks for Myocardial Motion Tracking in MRI
[STACOM-MICCAI 2019] Deep Learning Registration for Cardiac Motion Tracking
[MedIA'22] Generative myocardial motion tracking via latent space exploration with biomechanics-informed prior
An open-source python library for the processing of fluorescence video data
Self-supervised method for cardiac phase detection in 4D CMR. Model consists of a deformable registration part, the derivation of the per-voxel deformation angle and a rule-set based on the physiological properties of a contracting ventricle. Implemented in TF2.X. Koehler et al. 2022, STACOM workshop @ MICCAI
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