X-ray Image Correction Using Time-Series Detection History
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional X-ray diagnostic apparatuses face challenges in accurately correcting X-ray images due to phenomena like ghosting and burn-in, where detector sensitivity is temporarily lowered or becomes non-uniform, leading to image distortions and reduced accuracy.
Innovation Solution
The X-ray diagnostic apparatus employs processing circuitry to generate and correct X-ray images using first and second detection results, calculating correction coefficients based on time-series history information to address ghosting and burn-in, and incorporates a grid for scattered-ray correction, ensuring precise irradiated dose calculation and image refinement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional X-ray detection is used, then the apparatus can detect X-rays, but ghosting and burn-in phenomena occur causing image accuracy to deteriorate
Solution Approach 1:
The system performs preliminary detection of X-ray doses during the exposure period before the exposure is complete. This preliminary detection data is used to calculate correction coefficients that compensate for ghosting and burn-in effects in the final image, allowing correction to be applied based on early exposure information rather than waiting for complete exposure and subsequent calibration.
Solution Approach 2:
The system establishes a feedback loop where X-ray detection results obtained during exposure are fed back to calculate correction coefficients. These coefficients are then applied to correct the final X-ray image, creating a closed-loop system that continuously monitors and compensates for detector sensitivity changes throughout the exposure process.
2Measurement precision
If periodic calibration is performed to correct detector issues, then image accuracy can be maintained, but the frequency and time of calibration operations increase
Solution Approach 1:
The X-ray detection apparatus performs self-correction by automatically calculating correction coefficients from its own detection data during exposure. The system uses its internally captured X-ray dose information to generate correction values, eliminating the need for external calibration operations and enabling continuous autonomous correction without time loss to manual calibration procedures.
Solution Approach 2:
The correction process operates continuously throughout the X-ray exposure period rather than requiring intermittent calibration stops. The system continuously detects X-ray doses, calculates correction coefficients in real-time, and applies corrections, maintaining uninterrupted imaging operation while continuously improving image accuracy.
3Measurement precision
If correction coefficients are calculated using time-series history information, then correction accuracy improves, but processing complexity increases
Solution Approach 1:
The system introduces correction coefficients as an intermediary element that bridges the raw detection data and the final corrected image. These coefficients act as mediators that encapsulate the complex time-series analysis results, allowing the final image correction to be performed through a relatively simple multiplication operation rather than requiring complex processing at the final stage.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for high-accuracy correction of X-ray images by accounting for temporary sensitivity changes and detector deterioration, reducing the frequency of periodic calibrations and improving image quality by minimizing artifacts like ghosting and burn-in.
Implementation Method 1
an X-ray tube configured to expose, to a subject, X-rays
Implementation Method 2
a detector configured to detect the X-rays that have passed through the subject
Data Source
AI summary
An X-ray diagnostic apparatus according to an embodiment includes an X-ray tube, an X-ray detector, and processing circuitry. The X-ray tube exposes X-rays. The X-ray detector detects the X-rays exposed from the X-ray tube. The processing circuitry generates an X-ray image on the basis of a first detection result that is a detection result of the X-rays exposed for an irradiation period. The processing circuitry corrects the X-ray image on the basis of a second detection result that is a detection result of the X-rays until a point before the end of the irradiation period.