Wang Lin, He Xiaowei, Yu Jingjing
School of Information Sciences and Technology, Northwest University, Xi'an, China.
School of Computer Science and Engineering, Xi'an University of Technology, Xi'an, China.
Front Oncol. 2021 Sep 23;11:749889. doi: 10.3389/fonc.2021.749889. eCollection 2021.
Cerenkov luminescence tomography (CLT) has attracted much attention because of the wide clinically-used probes and three-dimensional (3D) quantification ability. However, due to the serious morbidity of 3D optical imaging, the reconstructed images of CLT are not appreciable, especially when single-view measurements are used. Single-view CLT improves the efficiency of data acquisition. It is much consistent with the actual imaging environment of using commercial imaging system, but bringing the problem that the reconstructed results will be closer to the animal surface on the side where the single-view image is collected. To avoid this problem to the greatest extent possible, we proposed a prior compensation algorithm for CLT reconstruction based on depth calibration strategy. This method takes full account of the fact that the attenuation of light in the tissue will depend heavily on the depth of the light source as well as the distance between the light source and the detection plane. Based on this consideration, a depth calibration matrix was designed to calibrate the attenuation between the surface light flux and the density of the internal light source. The feature of the algorithm was that the depth calibration matrix directly acts on the system matrix of CLT reconstruction, rather than modifying the regularization penalty items. The validity and effectiveness of the proposed algorithm were evaluated with a numerical simulation and a mouse-based experiment, whose results illustrated that it located the radiation sources accurately by using single-view measurements.
切伦科夫发光断层扫描(CLT)因其临床广泛使用的探针和三维(3D)定量能力而备受关注。然而,由于3D光学成像的严重病态性,CLT的重建图像并不理想,特别是在使用单视图测量时。单视图CLT提高了数据采集效率。它与使用商业成像系统的实际成像环境非常一致,但带来了重建结果在收集单视图图像一侧会更接近动物表面的问题。为了尽可能最大程度地避免这个问题,我们提出了一种基于深度校准策略的CLT重建先验补偿算法。该方法充分考虑了组织中光的衰减将严重依赖于光源深度以及光源与检测平面之间距离这一事实。基于此考虑,设计了一个深度校准矩阵来校准表面光通量与内部光源密度之间的衰减。该算法的特点是深度校准矩阵直接作用于CLT重建的系统矩阵,而不是修改正则化惩罚项。通过数值模拟和基于小鼠的实验对所提算法的有效性和准确性进行了评估,结果表明该算法通过单视图测量能够准确地定位辐射源。