Golnabi Amir H, Meaney Paul M, Geimer Shireen D, Paulsen Keith D
Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire, USA.
J Med Phys. 2011 Jul;36(3):159-70. doi: 10.4103/0971-6203.83482.
Microwave imaging for medical applications is attractive because the range of dielectric properties of different soft tissues can be substantial. Breast cancer detection and monitoring of treatment response are areas where this technology could be important because of the contrast between normal and malignant tissue. Unfortunately, the technique is unable to achieve the high spatial resolution at depth in tissue which is available from other conventional modalities such as x-ray computed tomography (CT) or magnetic resonance imaging (MRI). We have incorporated a soft-prior regularization strategy within our microwave reconstruction algorithm and compared it with the images obtained with traditional no-prior (Levenberg-Marquardt) regularization. Initial simulation and phantom results show a significant improvement of the recovered electrical properties. Specifically, errors in the microwave property estimates were improved by as much as 95%. The effects of a false-inclusion region were also evaluated and the results show that a small residual property bias of 6% in permittivity and 15% in conductivity can occur that does not otherwise degrade the property recovery accuracy of inclusions that actually exist. The work sets the stage for integrating microwave imaging with MR for improved resolution and functional imaging of the breast in the future.
用于医学应用的微波成像具有吸引力，因为不同软组织的介电特性范围可能很大。乳腺癌检测和治疗反应监测是这项技术可能很重要的领域，因为正常组织和恶性组织之间存在对比度。不幸的是，该技术无法在组织深度实现像X射线计算机断层扫描（CT）或磁共振成像（MRI）等其他传统模态那样高的空间分辨率。我们在微波重建算法中纳入了软先验正则化策略，并将其与传统无先验（Levenberg-Marquardt）正则化获得的图像进行了比较。初步模拟和体模结果显示，恢复的电学特性有显著改善。具体而言，微波特性估计中的误差改善了多达95%。还评估了假包含区域的影响，结果表明，在介电常数中可能会出现6%、电导率中可能会出现15%的小残余特性偏差，否则不会降低实际存在的包含物的特性恢复精度。这项工作为未来将微波成像与磁共振成像相结合以提高乳腺的分辨率和功能成像奠定了基础。
