20 citations · 21 across the 3 of their papers we have counts for
4 papers
Self-Supervised 2D/3D Registration for X-Ray to CT Image Fusion
Srikrishna Jaganathan, Maximilian Kukla, Jian Wang +2
Deep Learning-based 2D/3D registration enables fast, robust, and accurate X-ray to CT image fusion when large annotated paired datasets are available for training. However, the nee…
Deep Iterative 2D/3D Registration
Srikrishna Jaganathan, Jian Wang, Anja Borsdorf +2
Deep Learning-based 2D/3D registration methods are highly robust but often lack the necessary registration accuracy for clinical application. A refinement step using the classical…
Deep Learning compatible Differentiable X-ray Projections for Inverse Rendering
Karthik Shetty, Annette Birkhold, Norbert Strobel +4
Many minimally invasive interventional procedures still rely on 2D fluoroscopic imaging. Generating a patient-specific 3D model from these X-ray projection data would allow to impr…
Learning the Update Operator for 2D/3D Image Registration
Srikrishna Jaganathan, Jian Wang, Anja Borsdorf +1
Image guidance in minimally invasive interventions is usually provided using live 2D X-ray imaging. To enhance the information available during the intervention, the preoperative v…