Han Dong, Zhang Bo, Gao Qiujuan, Liu Kai, Tian Jie
Medical Image Processing Group, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:1966-9. doi: 10.1109/IEMBS.2010.5627582.
Fluorescence molecular tomography has become a promising technique for in vivo small animal imaging, and has many potential applications. Due to the ill-posed and the ill-conditioned nature of the problem, Tikhonov regularization is generally adopted to stabilize the solution. However, the result is usually over-smoothed. In this study, the sparsity of the fluorescent source is used as a priori information. We replace Tikhonov method with an iteratively reweighted scheme. By dynamically updating the weight matrix, L0- or L1-norm regularization can be approximated which can promote the sparsity of the solution. Simulation study shows that this method can preserve the sparsity of the fluorescent source within heterogeneous medium, even with very limited measurement data.
荧光分子断层成像已成为一种用于活体小动物成像的有前景的技术，并且有许多潜在应用。由于该问题的不适定性和病态性质，通常采用蒂霍诺夫正则化来稳定解。然而，结果通常过度平滑。在本研究中，荧光源的稀疏性被用作先验信息。我们用迭代加权方案取代蒂霍诺夫方法。通过动态更新权重矩阵，可以近似L0或L1范数正则化，这可以促进解的稀疏性。模拟研究表明，即使测量数据非常有限，该方法也能在异质介质中保持荧光源的稀疏性。
