Surgical Tool Video Tracking for Accurate OR Inventory Management
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Solution Overview
Problem
Current methods for tracking and managing surgical tool inventory in operating rooms are labor-intensive and prone to errors due to manual data collection, which is inefficient and inaccurate.
Innovation Solution
A machine-learning and computer-vision-based system that processes surgical videos to automatically detect and track surgical tools, count their usage, and generate alerts for tool expiration, utilizing modules for tool engagement detection, usage counting, and parameter extraction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual methods are used to track surgical tool usage, then the system complexity is low, but the productivity and accuracy are poor
Solution Approach 1:
The patent replaces manual mechanical tracking methods with an automated computer vision system that uses video processing and machine learning algorithms to detect and track surgical tools, eliminating the need for manual counting and recording operations
Solution Approach 2:
The system enables self-service tracking by automatically monitoring tool usage without requiring surgical staff intervention, where the automated system independently performs detection, tracking, and inventory management tasks
2Measurement precision
If manual tracking methods are used, then the device complexity is low, but the measurement precision and reliability are insufficient
Solution Approach 1:
The patent replaces imprecise manual tracking with automated computer vision technology that uses video analysis, object detection algorithms, and machine learning models to accurately identify and count surgical tool usage with high measurement precision
Solution Approach 2:
The system implements feedback mechanisms where the automated tracking system continuously monitors tool usage, provides real-time inventory updates, and generates alerts when tools need replacement, ensuring accurate and reliable measurement throughout the surgical procedure
3Loss of time
If manual data collection is performed, then the system complexity is low, but the loss of time is high
Solution Approach 1:
The patent implements self-service automation where the system independently performs all tracking tasks without requiring surgical staff time, automatically monitoring tool usage throughout the procedure and eliminating the need for manual data collection activities
Solution Approach 2:
The system provides continuous automated monitoring throughout the entire surgical procedure, continuously detecting and tracking tool usage without interruption, whereas manual methods require intermittent staff intervention and are not continuous
Data Source
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AI summary
Embodiments described herein provide various examples of automatically processing surgical videos to detect surgical tools and tool-related events, and extract surgical-tool usage information. In one aspect, a process for automatically detecting a new surgical tool engagement during a recorded surgical procedure is disclosed. This process can begin by receiving a surgical procedure video and then segmenting the surgical video into sequences of video frames. Next, for each sequence of video frames, the video frames are processed to detect one or more surgical tools and one or more surgical tool engagements associated with the detected surgical tools. If a surgical tool engagement is detected in the sequence of video frames, the process then determines if a detected surgical tool associated with the detected surgical tool engagement is associated with a previously identified surgical tool engagement. If not, the process identifies the detected surgical tool engagement as a new surgical tool engagement.