Object Tracking Across Body Wall Using Dual Image Sensors
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Solution Overview
Problem
Current systems for tracking objects moving across a body wall, particularly in medical procedures, lack effective methods to accurately monitor and report the status of object movement, which can lead to inefficiencies and reduced procedural success.
Innovation Solution
An object tracking system that utilizes a combination of exterior and interior image sensors, with a processing unit to determine registration between sensors and generate tracking results, indicating the status of object movement across the body wall based on received image data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If single image sensor tracking is used, then device complexity is reduced, but measurement precision of object movement status deteriorates
Solution Approach 1:
The tracking system is segmented into multiple independent image sensors positioned at different locations (exterior and interior to the body). Each sensor captures movement from its own perspective, and the system processes these segmented views separately before integrating them to achieve comprehensive tracking accuracy.
Solution Approach 2:
Multiple image sensors and their respective image data are merged into a unified tracking framework. The system combines data from exterior sensors (monitoring object approach to body wall) and interior sensors (monitoring object penetration and movement within body) to produce integrated tracking results that overcome the limitations of any single sensor.
2Measurement precision
If multiple image sensors are used, then measurement precision of object movement status is improved, but device complexity increases
Solution Approach 1:
A processing unit acts as an intermediary that receives image data from multiple image sensors, performs registration to align the different sensor perspectives, and generates unified tracking results. This intermediary component manages the complexity of multiple sensors by providing a centralized coordination layer.
Solution Approach 2:
The system implements feedback mechanisms where tracking results from multiple sensors are continuously monitored and used to adjust and refine the registration and tracking algorithms. This feedback loop improves measurement precision while managing system complexity through adaptive optimization.
3Measurement precision
If registration between sensors is performed, then tracking accuracy is improved, but processing time increases
Solution Approach 1:
Registration between image sensors is performed as a preliminary action before actual tracking begins. The system pre-aligns the coordinate systems and calibration parameters of multiple sensors, so that during the tracking process, data from different sensors can be directly integrated without real-time registration computations, reducing processing time.
4Reliability
If comprehensive tracking status is generated, then procedural effectiveness is improved, but information processing requirements increase
Solution Approach 1:
The system extracts only the critical tracking status information needed for procedural success from the comprehensive image data. Rather than processing all raw image data, the system identifies and extracts key movement parameters (object position, velocity, penetration status) to generate concise tracking results that maintain reliability while reducing information processing requirements.
Data Source
AI summary
A system includes a memory and a processing unit coupled to the memory. The processing unit is configured to receive first image data from a first image sensor exterior to a body, the first image data including data of an object; receive second image data from a second image sensor interior to the body, the second image data including data of the object; track the object moving across a body wall of the body based on the first and second image data to generate a tracking result to indicate a status of movement of the object across the body wall.