Digital Imager Calibration via Iterative Self-Service
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Solution Overview
Problem
Conventional calibration methods for digital imagers, such as X-ray imagers, require significant downtime and human intervention, are often unstable over time, and incur additional costs due to unavailability and the need for frequent recalibrations, which can lead to degraded image quality if not performed frequently enough.
Innovation Solution
A method for calibrating digital imagers that estimates a representative calibration image through successive iterations using current and previous images acquired during normal use, without requiring special intervention or controlled calibration images, allowing for frequent recalibrations and reducing costs by maintaining the imager's availability and eliminating the need for human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional calibration methods are used to ensure accurate image quality, then image quality is maintained, but the imager becomes unavailable for extended periods requiring frequent recalibration
Solution Approach 1:
The system performs automatic self-calibration using clinical images acquired during normal operation. The microprocessor automatically detects calibration parameters and adjusts the transfer function without requiring external intervention or specialized calibration equipment, enabling the system to maintain itself during routine use.
Solution Approach 2:
Calibration is performed continuously in the background during normal clinical imaging operations. The system processes clinical images to extract calibration information and updates the transfer function iteratively, ensuring calibration maintenance without interrupting the useful imaging action.
2Reliability
If frequent recalibration is performed to maintain image quality, then image quality is preserved, but operational costs increase due to downtime and human intervention
Solution Approach 1:
The automatic self-calibration system eliminates the need for operator intervention in calibration procedures. The microprocessor autonomously performs all calibration steps including parameter detection, transfer function calculation, and application, removing labor costs and enabling unattended operation.
Solution Approach 2:
The system recovers calibration information from routinely acquired clinical images that would otherwise be used solely for patient diagnostics. By extracting calibration parameters from these existing images, the system eliminates the need for separate calibration acquisitions, maximizing resource utilization.
3Measurement precision
If specialized calibration procedures are used to ensure accuracy, then calibration precision is improved, but device complexity and operational difficulty increase
Solution Approach 1:
The system uses clinical images serving dual purposes: both for patient diagnostics and for calibration. The same imaging hardware and data processing pipelines are utilized for both diagnostic and calibration functions, eliminating the need for specialized calibration equipment and procedures.
Solution Approach 2:
The method extracts calibration parameters directly from clinical images by analyzing known structures or patterns within the images. This extraction approach retrieves calibration information from routine operational data without requiring separate calibration measurements or specialized tools.
4Measurement precision
If manual calibration procedures are used to ensure accuracy, then calibration precision is improved, but the need for human intervention increases operational costs
Solution Approach 1:
The microprocessor-based system automatically performs all calibration operations including parameter detection, transfer function calculation, and application. The system monitors its own performance and initiates calibration when needed, completely eliminating manual intervention while maintaining calibration accuracy through algorithmic processing.
Solution Approach 2:
The system continuously monitors image quality parameters and automatically triggers calibration when degradation is detected. Calibration results are fed back into the transfer function, which is then applied to subsequent images, creating a closed-loop system that maintains accuracy through automated feedback control.
Data Source
Figure 1a~1b
Figure 2
AI summary
The invention relates to a method for calibrating a digital imager from a sequence of P input images (An), to which a calibration image (C_REF) is applied in order to obtain a sequence of P output images (Yn). According to the invention, the calibration is carried out by updating the calibration image (C_REF) by estimation, with n iterations, of an image (Cn) representative of the calibration image (C_REF), n being a whole number higher than or equal to 1.