Fiber Optic Imaging Calibration via Object Signal Analysis
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Solution Overview
Problem
Fiber-based imaging systems face challenges in compensating for non-uniform, time-varying fiber transfer functions, leading to sub-optimal image quality due to biased approximations of transfer functions and the need for burdensome calibration procedures, especially in clinical contexts where acquiring reference images is problematic.
Innovation Solution
A method for continuous and real-time optimization of fiber transfer function calibration using object images acquired during use, which does not require prior calibration data, by estimating relationship functions between neighbor fibers and inverting them to adaptively calibrate the imaging system, allowing for handling of complex gain factors and irregular spatial arrangements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If prior calibration procedures are used to compensate for non-uniform fiber transfer functions, then image quality can be improved, but the calibration process becomes burdensome and may compromise sterility in clinical settings
Solution Approach 1:
The system performs self-calibration by automatically computing fiber transfer function relationships from image data acquired during normal operation. The processor identifies corresponding pixels across multiple images and calculates calibration parameters without requiring external reference images or manual intervention, enabling the system to calibrate itself while maintaining sterility.
Solution Approach 2:
The calibration computation is performed in advance during the normal imaging procedure rather than requiring a separate calibration step. By processing multiple images acquired during routine operation, the system prepares calibration data that can be applied to subsequent images, eliminating the need for pre-procedure calibration that would compromise sterility.
2Measurement precision
If reference images are acquired during calibration procedures, then fiber transfer function compensation can be achieved, but sterility is compromised in clinical contexts
Solution Approach 1:
Instead of acquiring reference images during calibration, the system uses copies of image data from normal operational imaging. By analyzing corresponding pixels across multiple copies of clinically acquired images, the system derives calibration parameters without requiring the fiber bundle to be exposed to external calibration media that would compromise sterility.
Solution Approach 2:
The same imaging procedure serves dual purposes: both acquiring diagnostic/clinical information and collecting data for calibration computation. The images taken during normal operation are simultaneously used for their primary clinical purpose and for deriving fiber transfer function relationships, eliminating the need for separate calibration imaging that would breach sterility.
3Measurement precision
If traditional calibration methods are used, then fiber transfer function compensation is possible, but the procedure time and complexity increase
Solution Approach 1:
The calibration process operates continuously during normal imaging procedures. Rather than pausing clinical work for separate calibration steps, the system continuously accumulates image data and computes calibration parameters in the background, maintaining uninterrupted clinical imaging while progressively improving calibration accuracy.
Solution Approach 2:
The calibration computation is merged with the normal imaging workflow. By combining the acquisition of clinical images with the collection of calibration data, and by performing computational analysis during routine operations, the system integrates two previously separate processes into one unified flow, eliminating dedicated calibration time.
Data Source
AI summary
A method for processing images acquired by image detectors with non-uniform transfer functions and irregular spatial locations includes the steps of accumulating data from multiple images, defining an affinity graph which edges define pairs of detectors that measure related signal, performing statistical analysis on the accumulated data with respect to each pair of detectors, and solving a system of equations constructed from the results of the statistical analysis to estimate each detector transfer function, a set of solutions to the system of equations comprising a calibration of an imaging system.