Method for Tomographic Reconstruction of a Measured Quantity from an Auxiliary Quantity Accessible to Measurement

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This invention presents a new method for tomographic reconstruction—the process of reconstructing the internal distribution of a measurement variable in a sample (such as electrical current density inside a fuel cell) from more easily measurable auxiliary variables (such as magnetic fields). Unlike traditional techniques that require a large number of measurements at many locations, this method uses a 'relevance measure' to prioritize and weight measurement points, focusing data collection and computational effort where it will have the greatest impact on image quality. Optimized algorithms select the best measurement locations, leading to improved reconstruction accuracy with fewer data points, reducing the need for extensive hardware or lengthy measurement times.

Use CasesContent extracted from patent full text and abstract with AI.

• Non-invasive imaging of electrical current densities in fuel cells or batteries without disassembly.
• Enhanced medical imaging (such as MRI, CT, or impedance tomography) with fewer scans or detectors.
• Material testing and quality inspections where direct measurement is destructive or impractical.
• Security scanning (e.g., luggage or cargo inspection) where detailed internal distributions must be inferred from external measurements.
• Geophysical exploration (e.g., oil, mineral, or water detection) via external measurements and tomographic reconstruction.

BenefitsContent extracted from patent full text and abstract with AI.

• Reduces the number of measurement points needed for high-quality tomographic reconstructions, saving time and resources.
• Enables optimization of detector placement for maximal information gain, improving image accuracy and resolution.
• Minimizes hardware or sensor costs by focusing on the most informative measurement locations.
• Allows for faster imaging or monitoring, beneficial for dynamic or time-sensitive processes.
• Can improve accuracy and robustness of reconstructions by discarding low-value or noisy measurements.
• Applicable to a wide range of fields—including medical diagnostics, industrial inspection, security, and scientific research—where non-invasive internal imaging is required.

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Patent Abstract

The invention relates to a method for the tomographic reconstruction of the distribution of a measurement variable within a sample from values of an auxiliary variable, a method for determining the optimum measurement points for the auxiliary variable, as well as apparatuses for carrying out the methods. According to the invention, when determining the distribution of the measurement variable, the values of the auxiliary variable are weighted on the basis of a relevance measure. Relevance measures can, for example, measure how strongly the value of the auxiliary variable measured at the assessed location reacts to changes in the measurement variable, how large the resolveable structures in the reconstructed distribution of the measurement variable are which are changed in the event of a change in the value of the auxiliary variable measured at the assessed point, or how much information about the overall distribution of the measurement variable is contained in the value of the auxiliary variable measured at the assessed point. It is thus possible to obtain better information, from far fewer recorded values of the auxiliary variable, about the distribution of the measurement variable in the sample than according to the prior art.