Optoacoustic Signal Preprocessing for Sinogram Noise Reduction
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Solution Overview
Problem
Current optoacoustic imaging systems face challenges in accurately processing and presenting data due to unwanted information and maladies in sinogram data, such as transducer failures, noise, and external interference, which affect the quality of images used for tissue analysis.
Innovation Solution
The system employs preprocessing techniques like bad transducer detection, common mode stripe filtering, band pass filtering, normalization of dynamic range, and selective channel sensitivity to remove unwanted data and enhance the accuracy of optoacoustic return signals, ultimately generating clearer parametric images of oxygenation and hemoglobin levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If preprocessing techniques are applied to remove unwanted information from sinogram data, then image quality and measurement precision improve, but device complexity and processing time increase
Solution Approach 1:
The patent applies preliminary action by performing preprocessing operations on sinogram data before image reconstruction. Bad transducer detection identifies and flags defective transducers beforehand, common mode stripe filtering removes systematic noise patterns, and band pass filtering eliminates frequency components outside the useful range. These preprocessing steps prepare the data in advance, ensuring that the subsequent reconstruction algorithm receives clean, high-quality input data, thereby improving measurement precision without requiring changes to the reconstruction process itself
2Reliability
If multiple preprocessing filters and detection methods are applied to sinogram data, then noise and artifacts are reduced, but processing time and computational resources increase
Solution Approach 1:
The patent applies segmentation by dividing the preprocessing workflow into distinct, modular stages: bad transducer detection, common mode stripe filtering, band pass filtering, and normalization. Each stage addresses a specific type of data quality issue independently. This segmented approach allows the system to apply only the necessary processing steps to each dataset, avoiding redundant computations and enabling parallel processing where possible, thereby maintaining high data accuracy while optimizing processing time
3Measurement precision
If normalization of dynamic range is applied to enhance signal quality, then tissue composition analysis accuracy improves, but computational complexity increases
Solution Approach 1:
The patent applies parameter changes by normalizing the dynamic range of the sinogram data through scaling operations. This process adjusts the amplitude values to a standardized range, ensuring that signals from different transducers and depth ranges are comparable. The normalization enhances the visibility of subtle tissue composition variations by optimizing the contrast between different signal intensities, thereby improving tissue analysis accuracy while using computationally efficient scaling algorithms
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
These preprocessing methods improve the quality of optoacoustic images by reducing artifacts and noise, allowing for more accurate tissue analysis and better representation of tissue composition, specifically oxygenation and hemoglobin levels.
Implementation Method 1
a pulsed light source 130 for emitting light pulses
Implementation Method 2
a sensor 140 to detect light transmitted along the light path
Data Source
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AI summary
An optoacoustic system includes first and second light sources capable of generating pulse of light at first and second wavelengths, first and second electrically controlled optical attenuators, first and second light sync detectors, and a combiner. A power meter that is calibrated to determine power at the first and second predominant wavelength measures power at the first wavelength after the first light sync is detected and measures power at the second wavelength after the second light sync is detected. The system includes a calibration mode wherein it electrically attenuates the first optical attenuator when the power measured by the power meter at the first wavelength after the first light sync is detected is above a first level, and electrically attenuated the second optical attenuator when the power measured by the power meter at the second wavelength after the second light sync is detected is above a second level.