A learning-driven framework with spatial optimization for surgical suture thread reconstruction and autonomous grasping under multiple topologies and environmental noises

Keyphrases

• Environmental Noise 100%
• Surgical Suture 100%
• Spatial Optimization 100%
• Suture Thread 100%
• Autonomous Grasping 100%
• Multiple Topologies 100%
• Knot Tying 66%
• Surgical Knot 66%
• Search Strategy 33%
• Training Model 33%
• Wound Closure 33%
• Vision-based 33%
• Pixel Level 33%
• Surgeons 33%
• Postoperative Recovery 33%
• Three-dimensional Information 33%
• Transfer Learning Model 33%
• Shortest Path Approach 33%
• Robot Experiment 33%
• 2D Segmentation 33%
• Grasping Points 33%
• Three-dimensional Shape Reconstruction 33%
• V-REP 33%
• Grasping Operation 33%
• 2D Ordering 33%
• Da Vinci Research Kit 33%
• Surgical Data 33%
• Universal Robots 33%
• Surgical Images 33%

Engineering

• Environmental Noise 100%
• Obtained Image 50%
• Dimensional Shape 50%
• Pixel Level 50%
• Approach Path 50%
• Shape Reconstruction 50%
• Robot Experiment 50%
• Transfer Learning 50%

Computer Science

• Driven Framework 100%
• Inference Sequence 100%
• Transfer Learning 50%
• Intermediate Step 50%
• Pre-Trained Model 50%