LIBS Diagnostic Device Using Neural Network for Tissue Analysis
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Solution Overview
Problem
Conventional spectrum analysis methods, such as Raman spectroscopy and laser-induced breakdown spectroscopy (LIBS), face limitations in accuracy when analyzing biological tissues due to their complex composition and environmental variability, leading to inconsistent results and patient specificity issues.
Innovation Solution
A diagnostic device and method utilizing LIBS that includes a pulsed laser projection module, a light receiving module, a spectral member, and a sensor array to collect and analyze plasma ablation spectra, with an artificial neural network to minimize environmental and mechanical offset influences, thereby enhancing diagnostic accuracy and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional spectrum analysis methods (Raman spectroscopy, LIBS) are used to analyze biological tissue, then the analysis can be performed, but the accuracy is insufficient due to complex composition and environmental variability
Solution Approach 1:
The patent transforms raw spectrum data into feature vectors by extracting specific spectral features and parameters. This parameter transformation process converts the complex, variable spectral data into standardized diagnostic parameters that are less sensitive to environmental variations and patient-specific differences, thereby improving measurement precision while maintaining adaptability
Solution Approach 2:
The patent introduces an intermediary processing layer between spectrum acquisition and diagnosis that includes noise filtering, feature extraction, and normalization steps. This intermediary process acts as a mediator that eliminates environmental interference and patient-specific variations before the data reaches the diagnostic algorithm, resolving the contradiction between accuracy and adaptability
2Measurement precision
If LIBS is used to obtain spectrum data, then composition analysis can be performed, but damage to the patient occurs due to laser-induced plasma ablation
Solution Approach 1:
The patent uses only a portion of the plasma emission spectrum for diagnosis rather than requiring complete plasma ablation. By selecting specific spectral regions and features that provide sufficient diagnostic information, the system achieves accurate composition analysis with reduced laser energy input, thereby minimizing tissue damage while maintaining measurement precision
Solution Approach 2:
The patent extracts only the necessary spectral features and compositional information required for diagnosis from the plasma emission spectrum, rather than requiring complete spectral analysis. This selective extraction approach allows accurate composition analysis with reduced plasma generation, thereby reducing tissue damage while maintaining diagnostic accuracy
3Loss of information
If spectrum analysis is performed on biological tissue, then diagnostic information can be obtained, but environmental factors and mechanical offsets affect the spectrum data quality
Solution Approach 1:
The patent implements feedback mechanisms that monitor environmental conditions and mechanical parameters during spectrum acquisition. This feedback information is used to dynamically adjust the spectral analysis process and compensate for environmental influences, ensuring reliable and consistent spectrum data while maintaining complete diagnostic information
Solution Approach 2:
The patent performs preliminary calibration and environmental characterization before actual diagnosis. By establishing baseline data and correction factors in advance, the system can compensate for environmental factors and mechanical offsets during the diagnostic process, ensuring data consistency without losing diagnostic information
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
The approach enables non-invasive, accurate disease diagnosis by collecting comprehensive patient data, reducing damage and user-induced errors, and improving consistency across various patients, while effectively mitigating environmental and mechanical offset impacts on spectrum data.
Implementation Method 1
laser induced breakdown spectroscopy (LIBS) which analyzes a spectrum of a plasma induced by a high-power laser
Implementation Method 2
a spectrum of a plasma induced by a high-power laser
Data Source
AI summary
Disclosed herein are a method for diagnosing a disease of a body tissue by using LIBS (Laser-Induced Breakdown Spectroscopy) comprising: preparing a laser device including: a laser projection module, outputting the laser to a suspicious region of the body tissue, a light receiving module, receiving a plurality of light, a spectrum measurement module, and a guide unit; and projecting the laser to generate plasma by inducing tissue ablation in the suspicious region; wherein the laser projected to the suspicious region has a target area, and wherein the target area has smaller size than the suspicious region such that the target area is located inside the suspicious region.