Magnetorelaxometry imaging is a highly sensitive technique enabling noninvasive, quantitative detection of magnetic nanoparticles. Electromagnetic coils are sequentially energized, aligning the nanoparticles’ magnetic moments. Relaxation signals are recorded after turning off the coils. The forward model describing this measurement process is reformulated into a severely ill-posed inverse problem that is solved for estimating the particle distribution. Typically, many activation sequences employing different magnetic fields are required to obtain reasonable imaging quality. We seek to improve the imaging quality and accelerate the imaging process using fewer activation sequences by optimizing the applied magnetic fields. Minimizing the Frobenius condition number of the system matrix, we stabilize the inverse problem solution toward model uncertainties and measurement noise. Furthermore, our sensitivity-weighted reconstruction algorithms improve imaging quality in lowly sensitive areas. The optimization approach is employed to real measurement data and yields improved reconstructions with fewer activation sequences compared to non-optimized measurements.

中文翻译：

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优化励磁线圈电流以进行高级磁弹性成像

磁弹性成像是一种高度敏感的技术，可以对磁性纳米粒子进行无创，定量检测。电磁线圈被顺序通电，以对齐纳米粒子的磁矩。关闭线圈后记录松弛信号。将描述此测量过程的前向模型重新构造为严重不适定的逆问题，可以解决该问题以估算粒子分布。通常，需要许多采用不同磁场的激活序列以获得合理的成像质量。我们力求通过优化施加的磁场来提高成像质量并使用更少的激活序列来加快成像过程。最小化系统矩阵的Frobenius条件数，我们针对模型不确定性和测量噪声稳定反问题解决方案。此外，我们的灵敏度加权重建算法可提高低灵敏度区域的成像质量。与未优化的测量相比，该优化方法用于真实的测量数据，并以更少的激活序列产生了改进的重构。