Medical Device Image Identification for Implanted Catheter Differentiation
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Solution Overview
Problem
Healthcare professionals face challenges in accurately identifying medical instruments once they are implanted in patients, leading to potential misuse and complications due to confusion between similar devices like PICC and midline catheters, resulting in risks such as incorrect drug administration and infections.
Innovation Solution
A method involving image collection, training of an identification model, and assignment of identifiers to medical devices using a computer-based process, coupled with a computer program product, to facilitate accurate identification and provide usage recommendations and structural characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If medical devices are implanted in patients, then the devices can perform their therapeutic function, but the devices become difficult to identify and increasing the risk of misidentification and misuse
Solution Approach 1:
The patent creates visual copies (photographs) of the external parts of medical devices and stores them in a database. These image copies serve as reference data that can be compared against new device images to identify implanted devices without physically examining them. This resolves the contradiction by making device identification possible through digital reproduction rather than direct observation.
Solution Approach 2:
The patent replaces manual visual inspection and physical examination of devices with an automated image recognition system using machine learning algorithms. The computer-based system automatically compares images and identifies devices, substituting the mechanical/manual process with an automated digital system that overcomes the limitations of human visual identification.
2Adaptability or versatility
If similar devices like PICC and midline catheters are used, then treatment options are expanded, but confusion between devices increases leading to injection errors and infections
Solution Approach 1:
The patent implements a feedback mechanism where the image recognition system provides identification results back to healthcare professionals. The system analyzes images of external device parts and returns definitive identification information, allowing professionals to confirm device type before administration. This feedback loop eliminates guesswork and ensures correct device identification even when multiple similar devices are in use.
Solution Approach 2:
The patent introduces an intermediary system (the image recognition and database system) between the healthcare professional and the medical device. Instead of directly observing and identifying the device, the professional uses the intermediary system to mediate the identification process. This intermediary provides objective, data-driven identification that removes ambiguity between similar-looking devices.
3Measurement precision
If healthcare personnel manually identify and track medical devices, then direct control is maintained, but time consumption increases and accuracy decreases
Solution Approach 1:
The patent performs preliminary actions by pre-collecting, pre-processing, and pre-storing images of medical devices in a database before they are needed for identification. The machine learning model is pre-trained on this data. When identification is needed, the system can quickly compare new images against the pre-prepared database, dramatically reducing identification time while maintaining high accuracy through the pre-established reference framework.
Solution Approach 2:
The patent substitutes manual identification processes with automated image recognition technology. The computer-based system performs rapid image comparison and device identification without human intervention, eliminating the time-consuming nature of manual inspection while providing more consistent and accurate results. The automated system processes images much faster than human professionals can visually examine devices.
Data Source
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AI summary
The present invention relates to a method for identifying medical devices, referred to as medical devices of interest (50), the method comprising the following steps: a. collecting images of the outer portions of the medical devices of interest (50), each image being labelled with an identifier of the medical device of interest (50), the images collected forming a training image database, b. training an identification model from the training image database in order to obtain an identification model trained to assign an identifier to a medical device of interest (50) to be identified according to an image of the outer portion (54) of the medical device (50), c. receiving an image of the outer portion (54) of a medical device of interest (50) to be identified, d. assigning, by the trained classification model, an identifier to the medical device of interest (50) captured on the received image, and e. characterising the medical device of interest (50) according to the assigned identifier.