Bioluminescence tomography with Gaussian prior.
Bioluminescence tomography with Gaussian prior.
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DOI：
10.1364/boe.1.001259
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发表时间：
2010-10-29
影响因子：
3.4
通讯作者：
Wang G
中科院分区：
文献类型：
--
作者：
Gao H;Zhao H;Cong W;Wang G
在高斯中全局地参数化生物发光源提供了优于生物发光断层摄影中的体素表示的若干优点。在数学上恢复高斯是唯一的[Med.Phys.31（8），2289（2004）]，并且实际上足以在扩散介质中通过高斯近似各种形状。由于需要更少的未知数，计算负担显著降低。此外，有生理证据表明，源可以用高斯模型。仿真结果表明，该模型和算法在高斯或非高斯源、噪声数据或光学背景失配的情况下显著提高了精度和稳定性。它也通过在体内的实验数据进行了验证。
Parameterizing the bioluminescent source globally in Gaussians provides several advantages over voxel representation in bioluminescence tomography. It is mathematically unique to recover Gaussians [Med. Phys. 31(8), 2289 (2004)] and practically sufficient to approximate various shapes by Gaussians in diffusive medium. The computational burden is significantly reduced since much fewer unknowns are required. Besides, there are physiological evidences that the source can be modeled by Gaussians. The simulations show that the proposed model and algorithm significantly improves accuracy and stability in the presence of Gaussian or non- Gaussian sources, noisy data or the optical background mismatch. It is also validated through in vivo experimental data.