X-Ray Diagnostic Imaging With Dual-Model Exposure Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing fluoroscopy systems face challenges in achieving optimal image quality and reducing radiation exposure by setting low exposure doses, which complicates downstream image denoising and restoration processes.
Innovation Solution
An X-ray diagnosis apparatus that utilizes a first model to adjust exposure parameters based on informative frames, followed by a second model for image restoration, trained to minimize radiation dose and improve image quality using neural networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If low exposure dose is set during fluoroscopy procedures, then radiation exposure is reduced, but image quality deteriorates and downstream image denoising or restoration processes become more challenging
Solution Approach 1:
The system performs preliminary determination of optimized exposure parameters for each frame before actual image acquisition. The determination unit analyzes frame contents (such as histograms) and pre-calculates the optimal exposure parameters (mA, ms, kV, filters) that will maximize image quality while controlling radiation dose, thereby preparing the best possible acquisition settings in advance of each fluoroscopy frame capture
Solution Approach 2:
The system dynamically adjusts exposure parameters on a per-frame basis during fluoroscopy procedures. Rather than using fixed exposure settings, the determination unit continuously evaluates each frame's content characteristics and adapts the exposure parameters accordingly, allowing the system to optimize image quality for each specific frame while managing overall radiation exposure throughout the procedure
2Manufacturing precision
If exposure parameters are optimized for each frame to maximize image quality, then image quality improves, but radiation exposure increases
Solution Approach 1:
The system changes multiple exposure parameters simultaneously (mA, ms, kV, and filter settings) based on frame content analysis. By adjusting these parameters in combination rather than singly, the system can achieve optimal image quality for each frame's specific requirements while managing the cumulative radiation dose throughout the fluoroscopy procedure
3Manufacturing precision
If varying customized acquisition parameters are used during fluoroscopy procedures, then image quality improves, but device complexity increases
Solution Approach 1:
The system implements a feedback loop where the determination unit continuously analyzes the content of each fluoroscopy frame (such as histogram data) and uses this information to determine optimized exposure parameters for the next frame. This real-time feedback mechanism allows automatic adaptation of acquisition parameters based on actual image content, improving image quality without requiring complex manual intervention
Solution Approach 2:
The determination unit autonomously performs the task of optimizing exposure parameters without requiring external intervention or complex manual configuration. By automatically analyzing frame contents and determining optimal parameters independently, the system simplifies operation while achieving customized acquisition settings for each frame
Data Source
Figure 1
Figure 2
Figure 3
AI summary
An X-ray diagnostic apparatus (100) of an embodiment includes a setting unit (212) that inputs an X-ray image acquired using a first set of exposure parameters into a first model to obtain a second set of exposure parameters, an acquisition unit (211) that inputs the X-ray image acquired using the second set of exposure parameters into a second model trained together with the first model to obtain a restored image, and a control unit (213) that outputs the restored image.