Lv Yujie, Tian Jie, Cong Wenxiang, Wang Ge, Kumar Durairaj
Medical Image Processing Group, Chinese Academy of Science, Beijing, China.
Conf Proc IEEE Eng Med Biol Soc. 2006;2006:381-4. doi: 10.1109/IEMBS.2006.260762.
Molecular imaging is an emerging imaging technique in biological and medical field. Thereinto, bioluminescence tomography (BLT) plays a significant role. In view of the ill-posedness of the BLT problem, a priori knowledge is indispensable to reconstruct bioluminescent source uniquely and quantitatively. In this paper, the anatomical information of a real mouse is obtained with the microCT scanner to represent different macroscopic biological tissues. The proposed tomographic algorithm based on the adaptive finite element methods (FEMs) employs the microCT slices based coarse volumetric mesh to reconstruct source distribution quantitatively according to a posteriori error estimation techniques. In order to avoid the inverse crime, a Monte Carlo (MC) method based virtual optical environment, molecular optical simulation environment (MOSE), is also adopted for producing the measurement data. Finally, simulation results with the above framework demonstrate the effectiveness and potential of the proposed adaptive tomographic algorithm.
分子成像是生物和医学领域中一种新兴的成像技术。其中,生物发光断层扫描(BLT)发挥着重要作用。鉴于BLT问题的不适定性,先验知识对于唯一且定量地重建生物发光源是必不可少的。在本文中,使用微型计算机断层扫描(microCT)扫描仪获取真实小鼠的解剖信息,以表征不同的宏观生物组织。所提出的基于自适应有限元方法(FEM)的断层扫描算法采用基于microCT切片的粗体素网格,根据后验误差估计技术定量重建源分布。为了避免反问题误差,还采用基于蒙特卡罗(MC)方法的虚拟光学环境,即分子光学模拟环境(MOSE)来生成测量数据。最后,上述框架的模拟结果证明了所提出的自适应断层扫描算法的有效性和潜力。