School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China.
School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing 100081, China.
Sensors (Basel). 2024 Oct 27;24(21):6897. doi: 10.3390/s24216897.
In the field of medical imaging, microwave tomography (MWT) is based on the scattering and absorption characteristics of different tissues to microwaves and can reconstruct the electromagnetic property distribution of biological tissues non-invasively and without ionizing radiation. However, due to the inherently nonlinear and ill-posed characteristics of MWT calculations, actual imaging is prone to overfitting or artifacts. To address this, this paper proposes a two-step iterative imaging approach for rapid medical microwave tomography. This method establishes corresponding objective functions for microwave imaging across multiple frequencies and conducts iterative calculations on images at varying resolutions. This effectively enhances image clarity and accuracy while alleviating the issue of prolonged computational time associated with imaging complex structures at high resolution due to insufficient prior information during iterative processes. In the electromagnetic simulation section, we simulated a three-layer brain model and conducted imaging experiments. The results demonstrate that the algorithm significantly enhances imaging resolution, accurately pinpointing cerebral hemorrhages at different locations using an eight-antenna array and successfully reconstructs tomography images with a hemorrhage area radius of 1 cm. Lastly, experiments were conducted using a medical microwave tomography platform and four simplified human brain models, achieving millimeter-level accuracy in MWT.
在医学成像领域,微波层析成像(MWT)基于不同组织对微波的散射和吸收特性,可以非侵入性地、无电离辐射地重建生物组织的电磁特性分布。然而,由于 MWT 计算固有的非线性和不适定性,实际成像容易出现过拟合或伪影。为了解决这个问题,本文提出了一种两步迭代成像方法,用于快速医学微波层析成像。该方法为多个频率的微波成像建立了相应的目标函数,并对不同分辨率的图像进行迭代计算。这有效地提高了图像的清晰度和准确性,同时缓解了由于迭代过程中先验信息不足而导致对高分辨率复杂结构成像计算时间过长的问题。在电磁模拟部分,我们模拟了一个三层脑模型并进行了成像实验。结果表明,该算法显著提高了成像分辨率,使用八天线阵列准确地定位了不同位置的脑出血,并成功重建了出血区域半径为 1 厘米的层析图像。最后,我们在医学微波层析成像平台和四个简化的人脑模型上进行了实验,实现了 MWT 的毫米级精度。