Landmark Tracking
4 papers with code • 0 benchmarks • 1 datasets
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Most implemented papers
DeepTag: An Unsupervised Deep Learning Method for Motion Tracking on Cardiac Tagging Magnetic Resonance Images
Cardiac tagging magnetic resonance imaging (t-MRI) is the gold standard for regional myocardium deformation and cardiac strain estimation.
Breaking Shortcut: Exploring Fully Convolutional Cycle-Consistency for Video Correspondence Learning
Previous cycle-consistency correspondence learning methods usually leverage image patches for training.
Reasoning Structural Relation for Occlusion-Robust Facial Landmark Localization
Moreover, the SRN augments the training data by synthesizing occluded faces.
WarpPINN: Cine-MR image registration with physics-informed neural networks
In this work, we introduce WarpPINN, a physics-informed neural network to perform image registration to obtain local metrics of the heart deformation.