Miao Zhenzhuang, Kosmas Panagiotis, Ahsan Syed
Faculty of Natural and Mathematical Sciences, King's College London, Strand, London WC2R 2LS, UK.
Diagnostics (Basel). 2018 Aug 14;8(3):52. doi: 10.3390/diagnostics8030052.
This paper studies how limited information in data acquired by a wideband microwave tomography (MWT) system can affect the quality of reconstructed images. Limitations can arise from experimental errors, mismatch between the system and its model in the imaging algorithm, or losses in the immersion and coupling medium which are required to moderate this mismatch. We also present a strategy for improving reconstruction performance by discarding data that is dominated by experimental errors. The approach relies on recording transmitted signals in a wide frequency range, and then correlating the data in different frequencies. We apply this method to our wideband MWT prototype, which has been developed in our previous work. Using this system, we present results from simulated and experimental data which demonstrate the practical value of the frequency selection approach. We also propose a -neighbour method to identify low quality data in a robust manner. The resulting enhancement in imaging quality suggests that this approach can be useful for various medical imaging scenarios, provided that data from multiple frequencies can be acquired and used in the reconstruction process.
本文研究宽带微波断层扫描（MWT）系统采集的数据中的有限信息如何影响重建图像的质量。局限性可能源于实验误差、成像算法中系统与其模型之间的不匹配，或缓和这种不匹配所需的浸没和耦合介质中的损耗。我们还提出了一种通过丢弃受实验误差主导的数据来提高重建性能的策略。该方法依赖于在宽频率范围内记录传输信号，然后对不同频率的数据进行关联。我们将此方法应用于我们在之前工作中开发的宽带MWT原型。使用该系统，我们展示了模拟和实验数据的结果，这些结果证明了频率选择方法的实用价值。我们还提出了一种k近邻方法，以稳健的方式识别低质量数据。成像质量的提升表明，只要能够采集多个频率的数据并用于重建过程，这种方法对于各种医学成像场景可能是有用的。
