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Found 8 papers, 5 papers with code
EndoGSLAM: Real-Time Dense Reconstruction and Tracking in Endoscopic Surgeries using Gaussian Splatting
Precise camera tracking, high-fidelity 3D tissue reconstruction, and real-time online visualization are critical for intrabody medical imaging devices such as endoscopes and capsule robots.
Efficient Deformable Tissue Reconstruction via Orthogonal Neural Plane
Intraoperative imaging techniques for reconstructing deformable tissues in vivo are pivotal for advanced surgical systems.
SeamlessNeRF: Stitching Part NeRFs with Gradient Propagation
To fill this gap, we propose SeamlessNeRF, a novel approach for seamless appearance blending of multiple NeRFs.
Neural LerPlane Representations for Fast 4D Reconstruction of Deformable Tissues
Reconstructing deformable tissues from endoscopic stereo videos in robotic surgery is crucial for various clinical applications.
RecolorNeRF: Layer Decomposed Radiance Fields for Efficient Color Editing of 3D Scenes
We present RecolorNeRF, a novel user-friendly color editing approach for the neural radiance fields.
Human-in-the-loop Embodied Intelligence with Interactive Simulation Environment for Surgical Robot Learning
We showcase the improvement of our simulation environment with the designed new features, and validate effectiveness of incorporating human factors in embodied intelligence through the use of human demonstrations and reinforcement learning as a representative example.
Neural Rendering for Stereo 3D Reconstruction of Deformable Tissues in Robotic Surgery
Reconstruction of the soft tissues in robotic surgery from endoscopic stereo videos is important for many applications such as intra-operative navigation and image-guided robotic surgery automation.
SoGCN: Second-Order Graph Convolutional Networks
Graph Convolutional Networks (GCN) with multi-hop aggregation is more expressive than one-hop GCN but suffers from higher model complexity.
