Surgical Imaging System with 3D Object Tracking and Ranking
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Solution Overview
Problem
Current surgical imaging systems face challenges in providing comprehensive, real-time, three-dimensional tracking of objects within surgical spaces, especially in high-activity regions like prep and operating tables, with limited resolution and accuracy, leading to potential object loss and inefficiencies in surgical operations.
Innovation Solution
A surgical imaging system comprising a combination of fixed optical sensors and a mobile camera, integrated with a computer system that constructs a three-dimensional representation of the surgical space, detects and ranks objects based on type and status, and dynamically adjusts camera positions to maintain high-resolution tracking, using a truss system for mounting and routing power/data lines to ensure reliability and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single fixed camera is used to image the surgical space, then the device complexity is low, but the measurement precision and tracking accuracy of objects are insufficient
Solution Approach 1:
The imaging system is divided into multiple fixed optical sensors positioned at different locations around the surgical space, each capturing images from its own perspective. This segmentation allows the system to achieve comprehensive coverage and high tracking accuracy without requiring a single complex mobile camera system.
2Reliability
If mobile cameras are deployed to track objects dynamically, then the object tracking capability improves, but the device complexity and difficulty of detecting and measuring objects increases
Solution Approach 1:
Surgical objects are pre-equipped with machine-readable indicators (such as fiducial markers or barcodes) before the surgical procedure begins. This preliminary action allows the fixed optical sensors to easily detect and track objects throughout the surgery without requiring complex real-time object recognition algorithms, thereby improving tracking reliability while reducing detection difficulty.
3Measurement precision
If multiple sensors and mobile cameras are used to improve tracking, then the object tracking precision improves, but the ease of operation and system setup becomes more difficult
Solution Approach 1:
The fixed optical sensors are designed to perform multiple functions: capturing images for object detection, tracking object positions, and providing spatial references for three-dimensional reconstruction. This multi-functionality allows the system to achieve high spatial resolution with a relatively simple setup, as the same sensors serve multiple purposes rather than requiring specialized equipment for each function.
4Loss of information
If comprehensive three-dimensional representation is constructed in real-time, then the information completeness improves, but the loss of time for data processing increases
Solution Approach 1:
The system creates a three-dimensional digital replica (virtual model) of the physical surgical space and objects within it. This virtual model is updated in real-time by processing images from fixed optical sensors, allowing comprehensive spatial information to be maintained without requiring continuous complex image analysis during the surgery, thereby reducing processing time while maintaining information completeness.
Data Source
AI summary
A method includes accessing a three-dimensional representation of a surgical space and based on the three-dimensional representation, for each object in a first constellation of objects: extracting a first location of the object; detecting a first object type of the object; deriving a first surgical status of the object; calculating a first ranking score of the object based on the first object type and the first surgical status; and storing the first location, the first object type, the first surgical status, and the first ranking score in an object container in a set of object containers. The method also includes selecting a first target object at a first time based on a first target ranking score; articulating a mobile camera to locate a first target location of the first target object; and deriving a trajectory of the first target object based on the set of object containers.