Ye Jinzuo, Du Yang, An Yu, Chi Chongwei, Tian Jie
Chinese Academy of Sciences, Key Laboratory of Molecular Imaging of Chinese Academy of Sciences, Institute of Automation, No.95 Zhongguancun East Road, Haidian District, Beijing 100190, China.
Beijing Jiaotong University, School of Computer and Information Technology, Department of Biomedical Engineering, No.3 Shangyuancun, Haidian District, Beijing 100044, China.
J Biomed Opt. 2014 Dec;19(12):126013. doi: 10.1117/1.JBO.19.12.126013.
Fluorescence molecular tomography (FMT) is a promising imaging technique in preclinical research, enabling three-dimensional location of the specific tumor position for small animal imaging. However, FMT presents a challenging inverse problem that is quite ill-posed and ill-conditioned. Thus, the reconstruction of FMT faces various challenges in its robustness and efficiency. We present an FMT reconstruction method based on nonmonotone spectral projected gradient pursuit (NSPGP) with /₁-norm optimization. At each iteration, a spectral gradient-projection method approximately minimizes a least-squares problem with an explicit one-norm constraint. A nonmonotone line search strategy is utilized to get the appropriate updating direction, which guarantees global convergence. Additionally, the Barzilai-Borwein step length is applied to build the optimal step length, further improving the convergence speed of the proposed method. Several numerical simulation studies, including multisource cases as well as comparative analyses, have been performed to evaluate the performance of the proposed method. The results indicate that the proposed NSPGP method is able to ensure the accuracy, robustness, and efficiency of FMT reconstruction. Furthermore, an in vivo experiment based on a heterogeneous mouse model was conducted, and the results demonstrated that the proposed method held the potential for practical applications of FMT.
荧光分子断层扫描(FMT)是临床前研究中一种很有前景的成像技术,能够对小动物成像中的特定肿瘤位置进行三维定位。然而,FMT存在一个具有挑战性的反问题,该问题是严重不适定和病态的。因此,FMT的重建在其鲁棒性和效率方面面临各种挑战。我们提出了一种基于非单调谱投影梯度追踪(NSPGP)并结合₁范数优化的FMT重建方法。在每次迭代中,谱梯度投影方法通过显式的一范数约束近似最小化一个最小二乘问题。利用非单调线搜索策略来获得合适的更新方向,这保证了全局收敛。此外,应用Barzilai - Borwein步长来构建最优步长,进一步提高了所提方法的收敛速度。已经进行了多项数值模拟研究,包括多源情况以及对比分析,以评估所提方法的性能。结果表明,所提的NSPGP方法能够确保FMT重建的准确性、鲁棒性和效率。此外,基于异质小鼠模型进行了一项体内实验,结果表明所提方法在FMT的实际应用中具有潜力。