University of Connecticut, Department of Biomedical Engineering, Storrs, Connecticut, United States.
Washington University in St. Louis, Department of Biomedical Engineering, Missouri, United States.
J Biomed Opt. 2017 Feb 1;22(2):26002. doi: 10.1117/1.JBO.22.2.026002.
Ultrasound-guided diffuse optical tomography (DOT) is a promising imaging technique that maps hemoglobin concentrations of breast lesions to assist ultrasound (US) for cancer diagnosis and treatment monitoring. The accurate recovery of breast lesion optical properties requires an effective image reconstruction method. We introduce a reconstruction approach in which US images are encoded as prior information for regularization of the inversion matrix. The framework of this approach is based on image reconstruction package “NIRFAST.” We compare this approach to the US-guided dual-zone mesh reconstruction method, which is based on Born approximation and conjugate gradient optimization developed in our laboratory. Results were evaluated using phantoms and clinical data. This method improves classification of malignant and benign lesions by increasing malignant to benign lesion absorption contrast. The results also show improvements in reconstructed lesion shapes and the spatial distribution of absorption maps.
超声引导漫射光学断层成像（DOT）是一种很有前途的成像技术，可绘制乳腺病变的血红蛋白浓度图，以辅助超声（US）进行癌症诊断和治疗监测。准确恢复乳腺病变的光学特性需要有效的图像重建方法。我们引入了一种重建方法，其中将 US 图像编码为正则化逆矩阵的先验信息。该方法的框架基于我们实验室开发的基于 Born 近似和共轭梯度优化的“NIRFAST”图像重建包。使用体模和临床数据评估了该方法。该方法通过增加恶性病变与良性病变的吸收对比度来提高对良恶性病变的分类能力。结果还显示出重建病变形状和吸收图空间分布的改善。
