4.7 Article

Fluorescence Diffusion in the Presence of Optically Clear Tissues in a Mouse Head Model

期刊

IEEE TRANSACTIONS ON MEDICAL IMAGING
卷 36, 期 5, 页码 1086-1093

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMI.2016.2646518

关键词

Biomedical imaging; Cerebral spinal fluid; Clear tissues; Diffuse optics tomography; Diffusion equation; Forward modelling; Fluorescence; Monte Carlo methods; Neuroimaging

资金

  1. European Social Fund (ESF)
  2. EU Marie Curie Initial Training Network [PITN-GA-2012-317526]
  3. EC CIG
  4. MINECO [FIS2013-41802-R MESOIMAGING.]

向作者/读者索取更多资源

Diffuse Optical Tomography commonly neglects or assumes as insignificant the presence of optically clear regions in biological tissues, estimating their contribution as a small perturbation to light transport. The inaccuracy introduced by this practice is examined in detail in the context of a complete, based on realistic geometry, virtual fluorescence Diffuse Optical Tomography experiment where a mouse head is imaged in the presence of cerebral spinal fluid. Despite the small thickness of such layer, we point out that an error is introduced when neglecting it from the model with possibly reduction in the accuracy of the reconstruction and localization of the fluorescence distribution within the brain. The results obtained in the extensive study presented here suggest that fluorescence diffuse neuroimaging studies can be improved in terms of quantitative and qualitative reconstruction by accurately taking into account optically transparent regions especially in the cases where the reconstruction is aided by the prior knowledge of the structural geometry of the specimen. Thus, this has only recently become an affordable choice, thanks to novel computation paradigms that allow to run Monte Carlo photon propagation on a simple graphic card, hence speeding up the process a thousand folds compared to CPU-based solutions.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据