Implant Identification System Using Multi-Perspective Imaging
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Solution Overview
Problem
The rapid growth of medical implant revisions is hindered by inadequate identification methods, often relying on guesswork due to incomplete or missing records, leading to potential delays, increased surgical complexity, morbidity, and costs.
Innovation Solution
A computer-implemented method and system that acquires internal medical images from multiple perspectives and receives descriptive information to accurately identify medical implants, determining their operational characteristics and transmitting this information for precise identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If implant identification relies on x-ray images and expert guessing, then identification can be obtained, but identification accuracy is low and surgical time increases
Solution Approach 1:
The system performs preliminary actions by acquiring multiple images from different perspectives and storing them in a database before surgery. During surgery, the system quickly retrieves and compares these pre-acquired images with current images to identify the implant, eliminating the need for time-consuming expert guessing during the surgical procedure.
Solution Approach 2:
The system creates multiple copies of implant images from different perspectives (anterior, posterior, lateral views) and stores them in a database. During identification, these stored image copies are retrieved and compared with current surgical images to determine implant identity, replacing the need for expert visual guessing.
2Loss of information
If implant records are incomplete or missing, then patient records may indicate device implantation, but specific model and lot information is lost
Solution Approach 1:
The system replaces the manual mechanical process of record-keeping and expert visual inspection with an automated image recognition system. The system acquires images from multiple perspectives, stores them in a database, and uses automated comparison algorithms to identify implants and retrieve their specifications, eliminating reliance on incomplete paper records or human guessing.
Solution Approach 2:
The system changes the parameters of identification from relying on text records (which may be incomplete) to using multiple image parameters (anterior, posterior, lateral views) with different levels of information. By combining these multiple image parameters, the system can positively identify implants even when traditional records are missing or inaccurate.
3Measurement precision
If multiple images from different perspectives are acquired, then identification accuracy improves, but data acquisition complexity increases
Solution Approach 1:
The system uses a universal image acquisition approach that captures images in multiple standard perspectives (anterior, posterior, lateral views). These same multi-perspective images serve multiple functions: they are stored in the database for future reference, used for automated comparison during identification, and can be reused across different patients and procedures, reducing the need for specialized acquisition equipment.
Data Source
AI summary
Objects implanted in a being are identified by acquiring a first internal medical image of the object from a first perspective; acquiring a second internal medical image of the object from a second perspective different than the first perspective; and receiving descriptive information about the object that is in addition to the first and second internal medical images. The object is identified based on the first internal medical image, the second internal medical image, and the descriptive information; one or more operational characteristics of the object are then determined and transmitted to a remote requestor that provided the first and second internal medical images.