Automated Microchannel Cross-Section Measurement via Tomography
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Solution Overview
Problem
Conventional imaging analysis techniques for microfluidic channels and internal structures are manual, leading to inaccuracies and subjectivity, which can result in misinterpretation of scan data and detrimental consequences in medical and industrial applications.
Innovation Solution
An automated method and system for analyzing microchannel cross-sections using tomography scan data, involving alignment, extraction of channels, determination of surface voxels, and calculation of their contribution to cross-sections, with weighting based on voxel gray values, to provide accurate and consistent results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual analysis of tomography scan data is performed, then human expertise and judgment can be applied, but the analysis is subjective and prone to misinterpretation
Solution Approach 1:
The patent replaces manual visual inspection and mechanical analysis processes with an automated image processing system that uses computational algorithms to analyze tomography scan data. The system automatically segments channels, calculates cross-sectional areas, and generates measurements, eliminating subjective human interpretation while maintaining objective analysis standards.
Solution Approach 2:
The analysis system performs self-service by automatically processing tomography data without requiring manual intervention. The algorithm independently identifies channels, extracts cross-sections, calculates areas, and produces results, making the system self-sufficient in performing the complete analysis workflow that previously required human operators.
2Measurement precision
If manual inspection methods are used, then flexibility in interpretation is maintained, but measurement precision and consistency are reduced
Solution Approach 1:
The patent applies segmentation by dividing the complex analysis task into distinct computational steps: image preprocessing, channel identification, cross-section extraction, area calculation, and result generation. This segmentation of the analysis process enables precise measurement at each stage while managing system complexity through modular processing steps.
Solution Approach 2:
The system utilizes parameter changes by adjusting imaging and analysis parameters to optimize measurement precision. The tomography scan parameters, image processing thresholds, and calculation parameters are optimized to achieve accurate cross-sectional measurements, demonstrating how parameter optimization resolves the contradiction between precision and complexity.
3Difficulty of detecting and measuring
If conventional imaging analysis is performed, then general overview can be obtained, but accurate detection of channel irregularities is limited
Solution Approach 1:
The patent replaces conventional visual inspection methods with automated image processing algorithms that can detect subtle channel irregularities more effectively. The computational system analyzes pixel intensity variations, edge detection, and cross-sectional geometry to identify irregularities that would be difficult to detect manually, resolving the contradiction between detection capability and analysis time.
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 automated analysis significantly increases the reliability and consistency of microchannel cross-section measurements, enabling precise detection of irregularities and improving the accuracy of fluidic properties assessment.
Implementation Method 1
CT uses an x-ray source which projects a beam onto an imaging plane. The x-ray beam passes through the object being imaged, such as a patient or a microfluidic device. The beam is attenuated by the object and received by an array of radiation detectors.
Implementation Method 2
MRI detects magnetic resonance signals from nuclei (e.g. proton) in an object and can be used to reconstruct a tomographic image of a desired slice or position of the object.
Data Source
AI summary
Provided are embodiments of a method for performing automatic analysis of cross-sections of micro-channels. Embodiments includes receiving tomography scan data, aligning the tomography scan data, and extracting channels from a slice of the tomography scan data to create an isolated slice of the extracted channel. Embodiments also include determining surface voxels for the extracted channels, and determining an area defined within the surface voxels for each of the extracted channels. Embodiments include determining a contribution of the surface voxels for each of the extracted channels to the cross-section of the extracted channels, and outputting cross-section information based on the contribution of the surface voxels. Also provided are embodiments of a system for performing automatic analysis of cross-sections of micro-channels.