Processual Reasoning over Sequences of Situations in Endoscopic Surgery

Area of Science:

• Medical Technology
• Computer Science
• Ontology Engineering

Background:

• Minimally invasive surgery (MIS) offers faster patient recovery but presents navigation challenges due to limited direct visualization.
• Current surgical navigation systems rely on external markers, leading to inaccuracies and extensive technical requirements.
• The BIOPASS project seeks to develop marker-less navigation for enhanced surgical precision.

Purpose of the Study:

• To develop an ontology-based approach for real-time surgical navigation in minimally invasive procedures.
• To address the limitations of Web Ontology Language in modeling temporal conditions for comprehensive situational descriptions.
• To create a system that infers movement, actions, and risks using multimodal sensor data and process models.

Main Methods:

• Development of an ontology to describe surgical situations and temporal relationships.
• Integration of dynamic ontological classes to model temporal conditions, overcoming Web Ontology Language limitations.
• Relating real-time multimodal sensor data with static surgical process models for inferential capabilities.

Main Results:

• A novel ontology design pattern enabling the modeling of temporal relations within surgical scenarios.
• A framework for inferring surgical actions, movement directions, and identifying at-risk anatomical structures.
• A potential solution for marker-less surgical navigation, reducing inaccuracies associated with current systems.

Conclusions:

• The proposed ontology design pattern effectively addresses the temporal modeling limitations of Web Ontology Language for surgical navigation.
• This approach enhances situational awareness for surgeons, improving safety and precision in minimally invasive procedures.
• The BIOPASS project's methodology offers a promising advancement in marker-less surgical navigation technology.