X-ray Imaging System with AI View Name Generation
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Solution Overview
Problem
Traditional x-ray imaging systems for breast mammography are prone to human error in image labeling and require significant human input for adjusting parameters, especially when imaging biopsy samples or detecting accessories, leading to inefficiencies and potential errors.
Innovation Solution
An x-ray imaging system equipped with an optical camera and a controller using artificial intelligence to automatically acquire image acquisition factors, generate view names, and adjust imaging parameters based on these factors, including detection of biopsy samples and accessories, thereby reducing human intervention and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inspection and labeling of x-ray images is performed by medical personnel, then labeling can be performed with human judgment, but the process is time-consuming and prone to human error
Solution Approach 1:
The system enables self-service by having the x-ray imaging system automatically label its own images using an optical camera and AI subsystem, eliminating the need for medical personnel to manually inspect and label images. The system captures optical images, processes them through AI, and generates view names automatically during the imaging process.
Solution Approach 2:
The patent replaces the mechanical manual labeling process with an automated optical and AI-based system. The optical camera captures images of the patient's breast, the AI subsystem processes these images to identify view names, and this digital processing replaces the manual mechanical inspection and labeling performed by medical personnel.
2Reliability
If preconfigured selectable options with exemplary graphics are provided, then human error can be reduced, but the system still requires human input and selection
Solution Approach 1:
The system transitions from requiring human selection from preconfigured options to self-service automation where the AI subsystem independently analyzes optical images, determines view names, and labels images without human intervention. The system serves itself by automatically completing the labeling task that previously required human judgment.
Solution Approach 2:
The patent replaces the mechanical process of human selection from preconfigured options with an automated optical recognition and AI processing system. The optical camera captures images, the AI subsystem analyzes them to identify view names, and this digital automation replaces the human mechanical selection process.
3Adaptability or versatility
If human input is required to inform the machine about biopsy samples, then imaging parameters can be adjusted manually, but the process is time-consuming and error-prone
Solution Approach 1:
The system enables self-service by automatically detecting biopsy samples through the optical camera and AI subsystem. The system captures optical images, processes them to identify biopsy samples, and automatically adjusts imaging parameters without requiring human input to inform the machine about the sample type.
Solution Approach 2:
The patent applies preliminary action by having the optical camera and AI subsystem analyze images before the actual imaging process begins. The system pre-identifies the sample type (biopsy sample) and pre-adjusts imaging parameters in advance, eliminating the need for post-detection manual parameter adjustment.
4Productivity
If the system images biopsy samples immediately after acquisition, then productivity is improved, but different imaging parameters are required that must be manually adjusted
Solution Approach 1:
The system achieves self-service automation where the optical camera and AI subsystem automatically detect biopsy samples and adjust imaging parameters in real-time during immediate imaging. The system serves itself by autonomously adapting to different sample types without requiring manual parameter adjustment, enabling rapid imaging of biopsy samples immediately after acquisition.
Solution Approach 2:
The patent applies dynamics by making the imaging parameters dynamic and automatically adjustable based on real-time detection of sample types. The system continuously monitors the imaging process, detects biopsy samples through optical imaging, and dynamically adjusts parameters on the fly to optimize imaging for each specific sample type, enabling immediate imaging with appropriate parameters.
5Extent of automation
If the system is unable to detect imaging accessories, then the system remains simple, but automatic detection capability is lost
Solution Approach 1:
The patent replaces any potential mechanical detection systems with an optical camera and AI-based recognition system. The optical camera captures images of the imaging environment, the AI subsystem processes these images to automatically detect and identify imaging accessories, and this digital processing replaces any mechanical or manual detection methods.
Data Source
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AI summary
An x-ray imaging system is provided. The system includes an x-ray emitter and an x-ray detector. The system further includes a sensor operative to acquire one or more image acquisition factors, and a controller in electronic communication with the x-ray emitter, the x-ray detector, and the sensor. The controller is operative to: acquire an x-ray image of a patient via the x-ray emitter and the x-ray detector; receive the one or more image acquisition factors from the sensor; and generate a view name of the x-ray image based at least in part on the one or more image acquisition factors.