Digital Imaging Sharpness Monitoring via Quantum Noise Analysis
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Solution Overview
Problem
Existing digital imaging systems face challenges in reliably and automatically measuring sharpness without requiring specialized phantoms or procedures, which disrupts daily operations and is costly.
Innovation Solution
A method to calculate the point spread function (PSF) of a digital image detector system using Transfer function modulated quantum-noise measurements from standard images acquired during daily operations, eliminating the need for dedicated image acquisitions or phantoms, and allowing continuous, automatic monitoring of image sharpness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If dedicated image acquisition with specialized phantoms is used to measure sharpness, then measurement precision is improved, but device complexity and operational disruption increase
Solution Approach 1:
The imaging system measures its own sharpness characteristics by analyzing quantum noise patterns in images acquired during normal operation. The system uses its regular imaging function to generate measurement data, eliminating the need for separate measurement devices and specialized phantoms. The quantum noise inherently present in the images serves as the measurement signal, allowing the system to self-diagnose its sharpness performance.
Solution Approach 2:
The imaging system performs dual functions: acquiring diagnostic images for patient care and simultaneously measuring sharpness parameters from the same images. The quantum noise analysis method allows the system to extract sharpness information from routine clinical images without requiring separate measurement procedures, making the system both diagnostically useful and self-characterizing.
2Measurement precision
If dedicated image acquisition with specialized phantoms is used to measure sharpness, then measurement precision is improved, but productivity decreases due to operational disruptions
Solution Approach 1:
The sharpness measurement process operates continuously in the background during normal imaging operations. The system analyzes quantum noise patterns in real-time or near-real-time as images are acquired for diagnostic purposes, maintaining continuous monitoring of sharpness performance without interrupting the imaging workflow. This allows uninterrupted diagnostic imaging while simultaneously characterizing system performance.
Solution Approach 2:
The system performs self-monitoring of sharpness during routine operation, eliminating the need for external measurement interventions. By using quantum noise from regular clinical images, the system maintains its productivity while automatically tracking its own performance degradation over time.
3Measurement precision
If traditional sharpness measurement methods are used, then measurement precision is improved, but ease of operation deteriorates due to user intervention requirements
Solution Approach 1:
The system automatically performs sharpness measurements by analyzing quantum noise patterns in acquired images without requiring user intervention. The processing algorithm autonomously identifies and analyzes the quantum noise signal, calculates sharpness parameters, and monitors performance trends, freeing operators from manual measurement tasks while maintaining high measurement precision.
Solution Approach 2:
The system provides automatic feedback on sharpness performance by continuously analyzing quantum noise in clinical images. This feedback mechanism operates without user input, automatically detecting sharpness degradation and alerting operators when performance thresholds are exceeded, simplifying operation while maintaining measurement accuracy.
4Measurement precision
If specialized measurement procedures are used, then measurement precision is improved, but loss of time increases due to dedicated acquisition requirements
Solution Approach 1:
The same imaging acquisition serves dual purposes: obtaining diagnostic images for patient care and collecting data for sharpness measurement. The quantum noise present in every clinical image provides the measurement signal, eliminating the need for separate measurement acquisitions and the associated time loss.
Solution Approach 2:
Sharpness measurement occurs continuously during normal imaging operations rather than requiring dedicated measurement time slots. The system extracts sharpness information from the quantum noise in routinely acquired images, maintaining continuous performance monitoring without adding time to the imaging workflow.
Data Source
AI summary
The invention is related to a method for automatic selection and pre-processing of digital images that comprise the necessary amount of Transfer function modulated quantum-noise to apply a mathematical sharpness calculation method for calculation of a sharpness parameter of the digital imaging system. Suitable images for the method are selected from the pool of available images acquired by the digital imaging system during daily operation.