Search Results for author:
Found 6 papers, 1 papers with code
Transformer-Based Local Feature Matching for Multimodal Image Registration
Ultrasound imaging is a cost-effective and radiation-free modality for visualizing anatomical structures in real-time, making it ideal for guiding surgical interventions.
Double-Uncertainty Guided Spatial and Temporal Consistency Regularization Weighting for Learning-based Abdominal Registration
Such convention has two limitations: (i) Besides the laborious grid search for the optimal fixed weight, the regularization strength of a specific image pair should be associated with the content of the images, thus the "one value fits all" training scheme is not ideal; (ii) Only spatially regularizing the transformation may neglect some informative clues related to the ill-posedness.
Noisy Labels are Treasure: Mean-Teacher-Assisted Confident Learning for Hepatic Vessel Segmentation
Manually segmenting the hepatic vessels from Computer Tomography (CT) is far more expertise-demanding and laborious than other structures due to the low-contrast and complex morphology of vessels, resulting in the extreme lack of high-quality labeled data.
Unsupervised Multimodal Image Registration with Adaptative Gradient Guidance
Multimodal image registration (MIR) is a fundamental procedure in many image-guided therapies.
Unimodal Cyclic Regularization for Training Multimodal Image Registration Networks
The loss function of an unsupervised multimodal image registration framework has two terms, i. e., a metric for similarity measure and regularization.
Adversarial Uni- and Multi-modal Stream Networks for Multimodal Image Registration
Deformable image registration between Computed Tomography (CT) images and Magnetic Resonance (MR) imaging is essential for many image-guided therapies.
