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Published on: January 6, 2019
A Bi-objective Array Optimization Framework for Magnetocardiographic Source Imaging
IEEE Transactions on Bio-Medical Engineering
|June 25, 2026
Summary
A new bi-objective array optimization framework (BoAOF) optimizes sensor placement for magnetocardiographic source imaging (MCSI) systems. Optimized arrays improve accuracy and reduce deviation, advancing flexible OPM-based MCSI system design.
Area of Science:
- Biomedical Engineering
- Magnetoencephalography
- Sensor Technology
Background:
- Optically pumped magnetometers (OPMs) enable flexible magnetocardiographic source imaging (MCSI) systems.
- Sensor array configuration critically impacts MCSI cost and performance.
- Principled strategies for MCSI sensor array design are needed.
Purpose of the Study:
- Propose a novel sensor array design strategy for MCSI systems.
- Develop a bi-objective array optimization framework (BoAOF) for MCSI.
Main Methods:
- Modeled array design as a dual-objective optimization problem: maximizing sensitivity and minimizing spatial deviation.
- Integrated forward modeling with the non-dominated sorting genetic algorithm II (NSGA-II) to generate Pareto fronts.
- Employed a hybrid CRITIC-Entropy-VIKOR decision process to select optimal sensor configurations.
Main Results:
- BoAOF-optimized arrays outperformed baseline methods in simulations and phantom experiments.
- Achieved lower mean dipole localization error and reduced mean spatial deviation.
- Demonstrated higher mean source-reconstruction signal-to-noise ratio.
Conclusions:
- The proposed BoAOF offers a novel strategy for MCSI sensor array design.
- Provides a methodological foundation for designing flexible OPM-based MCSI systems.
