El-Shenawee Magda, Miller Eric L
Department of Electrical Engineering, University of Arkansas, Fayetteville, AR 72701, USA.
IEEE Trans Med Imaging. 2006 Oct;25(10):1258-71. doi: 10.1109/tmi.2006.881377.
A reconstruction algorithm to simultaneously estimate the shape and location of three-dimensional breast cancer tumor is presented and its utility is analyzed. The approach is based on a spherical harmonic decomposition to capture the shape of the tumor. We combine a gradient descent optimization method with a direct electromagnetic solver to determine the coefficients in the harmonic expansion as well as the coordinates of the center of the tumor. The results demonstrate the potential advantage of collecting data using a multiple-view/tomographic-type strategy. We show how the order of the harmonic expansion must be increased to capture increasingly "irregularly" shaped tumors and explore the resulting increase in the central processing unit (CPU) time required by the algorithm. Our approach shows accurate reconstruction of the tumor image regardless of the source polarization. This work demonstrates the promise of the algorithm when used on data corrupted with Gaussian noise and when perfect knowledge of the tumor electrical properties is not available.
提出了一种用于同时估计三维乳腺癌肿瘤形状和位置的重建算法，并分析了其效用。该方法基于球谐分解来捕捉肿瘤的形状。我们将梯度下降优化方法与直接电磁求解器相结合，以确定谐波展开中的系数以及肿瘤中心的坐标。结果证明了使用多视图/断层扫描类型策略收集数据的潜在优势。我们展示了必须如何增加谐波展开的阶数以捕捉形状越来越“不规则”的肿瘤，并探讨算法所需的中央处理器（CPU）时间的相应增加。无论源极化如何，我们的方法都能准确重建肿瘤图像。这项工作证明了该算法在处理受高斯噪声干扰的数据以及肿瘤电学特性不完全已知时的前景。
