20 citations · 23 across the 6 of their papers we have counts for
6 papers
ProPLIKS: Probablistic 3D human body pose estimation
Karthik Shetty, Annette Birkhold, Bernhard Egger +4
We present a novel approach for 3D human pose estimation by employing probabilistic modeling. This approach leverages the advantages of normalizing flows in non-Euclidean geometrie…
BOSS: Bones, Organs and Skin Shape Model
Karthik Shetty, Annette Birkhold, Srikrishna Jaganathan +4
Objective: A digital twin of a patient can be a valuable tool for enhancing clinical tasks such as workflow automation, patient-specific X-ray dose optimization, markerless trackin…
PLIKS: A Pseudo-Linear Inverse Kinematic Solver for 3D Human Body Estimation
Karthik Shetty, Annette Birkhold, Srikrishna Jaganathan +4
We introduce PLIKS (Pseudo-Linear Inverse Kinematic Solver) for reconstruction of a 3D mesh of the human body from a single 2D image. Current techniques directly regress the shape,…
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…