Medical Procedure 3D Point Cloud Replay for Deidentified Activity
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Solution Overview
Problem
Conventional surgery replay systems fail to provide a realistic and flexible view of practitioner activity during medical procedures, often revealing sensitive information and requiring high processing power.
Innovation Solution
A medical procedure visualization system that utilizes 3D point clouds to depict practitioner activity, accessed from depth data, offering customizable and low-processing extended reality content that automatically deidentifies sensitive information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional surgery replay systems are used to capture and display practitioner activity, then visibility of practitioner activity is improved, but sensitive information is exposed and processing power requirements increase
Solution Approach 1:
The system extracts only the essential geometric information (depth data) from the operating room environment while deliberately excluding identifiable features such as faces, names, and unique visual characteristics. This extraction approach captures practitioner activity patterns without retaining sensitive personal information, resolving the contradiction between visibility and sensitivity protection.
Solution Approach 2:
The system transforms visual information from high-detail video data to simplified depth maps and point cloud representations. This parameter change reduces the information content to essential spatial and temporal patterns of practitioner activity while automatically removing sensitive details, achieving both visibility and deidentification simultaneously.
2Loss of information
If detailed video content is captured to show practitioner activity, then realism and detail are improved, but processing power requirements increase
Solution Approach 1:
The system uses lightweight depth data representations (point clouds and simplified geometric models) instead of heavy video files. These simplified representations require minimal processing power to capture, store, transmit, and replay, while still effectively conveying practitioner activity patterns and spatial relationships.
Solution Approach 2:
The system replaces complex video processing mechanisms with simpler depth data processing. Instead of capturing and processing high-resolution video frames, the system uses depth sensors to directly capture spatial information, which requires significantly less computational power while maintaining the ability to analyze practitioner activity.
3Power
If 3D point cloud representation is used to depict practitioner activity, then processing requirements are reduced, but visual realism may be compromised
Solution Approach 1:
The system transitions from 2D video representations to 3D point cloud representations, adding spatial depth information while maintaining processing efficiency. This dimensional enhancement provides more accurate spatial relationships and practitioner positioning without requiring the high processing power needed for photorealistic 3D rendering.
Data Source
AI summary
A medical procedure visualization system may be configured to access depth data captured by one or more depth capture devices during a medical procedure. The depth data may be representative of practitioner activity associated with the medical procedure. As such, the medical procedure visualization system may be further configured to render, based on the depth data, extended reality content for presentation to a user. The extended reality content may include a 3D point cloud depicting the practitioner activity associated with the medical procedure. Corresponding methods and systems are also disclosed.