mlsanityData to 14 Oct 2026

Dynamic Interactive Relation Capturing via Scene Graph Learning for Robotic Surgical Report Generation

arXiv 2306.02651 ↗First posted 5 Jun 2023cs.CV cs.LGcited by 14

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Abstract (arXiv)

For robot-assisted surgery, an accurate surgical report reflects clinical operations during surgery and helps document entry tasks, post-operative analysis and follow-up treatment. It is a challenging task due to many complex and diverse interactions between instruments and tissues in the surgical scene. Although existing surgical report generation methods based on deep learning have achieved large success, they often ignore the interactive relation between tissues and instrumental tools, thereby degrading the report generation performance. This paper presents a neural network to boost surgical report generation by explicitly exploring the interactive relation between tissues and surgical instruments. We validate the effectiveness of our method on a widely-used robotic surgery benchmark dataset, and experimental results show that our network can significantly outperform existing state-of-the-art surgical report generation methods (e.g., 7.48% and 5.43% higher for BLEU-1 and ROUGE).

Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). Builds on 20 of its 31 references that are in the map. First posted on arXiv 5 Jun 2023.

Builds on

20 of 31 references.

References · 20

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8 more
  1. 20202018 Robotic Scene Segmentation Challengecited by 124
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 7; 2025: 5; 2026: 1.

14 papers.

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  1. 2024RainMamba: Enhanced Locality Learning with State Space Models for Video Derainingcited by 56
  2. 2025Multimodal Large Language Models for Medicine: A Comprehensive Surveycited by 16
  3. 2024HFGS: 4D Gaussian Splatting with Emphasis on Spatial and Temporal High-Frequency Components for Endoscopic Scene Reconstructioncited by 13
  4. 2024Deep Learning for Surgical Instrument Recognition and Segmentation in Robotic-Assisted Surgeries: A Systematic Reviewcited by 13
  5. 2024Semi-Supervised Video Desnowing Network via Temporal Decoupling Experts and Distribution-Driven Contrastive Regularizationcited by 11
  6. 2024Language-Driven Interactive Shadow Detectioncited by 7
  7. 2024Timeline and Boundary Guided Diffusion Network for Video Shadow Detectioncited by 6
  8. 2024Non-Invasive to Invasive: Enhancing FFA Synthesis from CFP with a Benchmark Dataset and a Novel Networkcited by 6
  9. 2025Decoding the Surgical Scene: A Scoping Review of Scene Graphs in Surgerycited by 3
  10. 2025CoC: Chain-of-Cancer based on Cross-Modal Autoregressive Traction for Survival Predictioncited by 2
  11. 2025More than Segmentation: Benchmarking SAM 3 for Segmentation, 3D Perception, and Reconstruction in Robotic Surgerycited by 1
  12. 2023Video-Instrument Synergistic Network for Referring Video Instrument Segmentation in Robotic Surgerycited by 0
2 more
  1. 2025Can DeepSeek Reason Like a Surgeon? An Empirical Evaluation for Vision-Language Understanding in Robotic-Assisted Surgerycited by 0
  2. 2026SAGE-OR: Semi-supervised Adaptive Scene Graph Generation for Operating Roomscited by 0