mlsanityData to 14 Oct 2026

Multimodal Semantic Scene Graphs for Holistic Modeling of Surgical Procedures

arXiv 2106.15309 ↗First posted 9 Jun 2021cs.CVcited by 6

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Abstract (arXiv)

From a computer science viewpoint, a surgical domain model needs to be a conceptual one incorporating both behavior and data. It should therefore model actors, devices, tools, their complex interactions and data flow. To capture and model these, we take advantage of the latest computer vision methodologies for generating 3D scene graphs from camera views. We then introduce the Multimodal Semantic Scene Graph (MSSG) which aims at providing a unified symbolic, spatiotemporal and semantic representation of surgical procedures. This methodology aims at modeling the relationship between different components in surgical domain including medical staff, imaging systems, and surgical devices, opening the path towards holistic understanding and modeling of surgical procedures. We then use MSSG to introduce a dynamically generated graphical user interface tool for surgical procedure analysis which could be used for many applications including process optimization, OR design and automatic report generation. We finally demonstrate that the proposed MSSGs could also be used for synchronizing different complex surgical procedures. While the system still needs to be integrated into real operating rooms before getting validated, this conference paper aims mainly at providing the community with the basic principles of this novel concept through a first prototypal partial realization based on MVOR dataset.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 15 of its 30 references that are in the map. First posted on arXiv 9 Jun 2021.

Builds on

15 of 30 references.

References · 15

  1. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,639
  2. 2017ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenescited by 3,117
  3. 2018Image Generation from Scene Graphscited by 324
  4. 20193D Scene Graph: A Structure for Unified Semantics, 3D Space, and Cameracited by 281
  5. 2019Action Genome: Actions as Composition of Spatio-temporal Scene Graphscited by 250
  6. 2020Learning 3D Semantic Scene Graphs from 3D Indoor Reconstructionscited by 208
  7. 20203D Dynamic Scene Graphs: Actionable Spatial Perception with Places, Objects, and Humanscited by 144
  8. 2020TeCNO: Surgical Phase Recognition with Multi-Stage Temporal Convolutional Networkscited by 141
  9. 2017Surgical Data Science: Enabling Next-Generation Surgerycited by 126
  10. 2020Semantic Image Manipulation Using Scene Graphscited by 82
  11. 2018Weakly Supervised Convolutional LSTM Approach for Tool Tracking in Laparoscopic Videoscited by 35
  12. 2020Automatic Operating Room Surgical Activity Recognition for Robot-Assisted Surgerycited by 34
3 more
  1. 2017A Multi-view RGB-D Approach for Human Pose Estimation in Operating Roomscited by 17
  2. 2020A Robotic 3D Perception System for Operating Room Environment Awarenesscited by 13
  3. 2018Active Learning using Deep Bayesian Networks for Surgical Workflow Analysiscited by 6

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 2; 2025: 1; 2026: 2.

6 papers.