Suppr超能文献

由背景光学特性的不确定性导致的系统性漫射光学图像误差。

Systematic diffuse optical image errors resulting from uncertainty in the background optical properties.

作者信息

Cheng X, Boas D

出版信息

Opt Express. 1999 Apr 12;4(8):299-307. doi: 10.1364/oe.4.000299.

Abstract

We investigated the diffuse optical image errors resulting from systematic errors in the background scattering and absorption coefficients, Gaussian noise in the measurements, and the depth at which the image is reconstructed when using a 2D linear reconstruction algorithm for a 3D object. The fourth Born perturbation approach was used to generate reflectance measurements and k-space tomography was used for the reconstruction. Our simulations using both single and dual wavelengths show large systematic errors in the absolute reconstructed absorption coefficients and corresponding hemoglobin concentrations, while the errors in the relative oxy- and deoxy- hemoglobin concentrations are acceptable. The greatest difference arises from a systematic error in the depth at which an image is reconstructed. While an absolute reconstruction of the hemoglobin concentrations can deviate by 100% for a depth error of ñ1 mm, the error in the relative concentrations is less than 5%. These results demonstrate that while quantitative diffuse optical tomography is difficult, images of the relative concentrations of oxy- and deoxy-hemoglobin are accurate and robust. Other results, not presented, confirm that these findings hold for other linear reconstruction techniques (i.e. SVD and SIRT) as well as for transmission through slab geometries.

摘要

我们研究了由背景散射和吸收系数的系统误差、测量中的高斯噪声以及使用二维线性重建算法对三维物体进行图像重建时的重建深度所导致的扩散光学图像误差。采用第四玻恩微扰法生成反射率测量值,并使用k空间断层扫描进行重建。我们使用单波长和双波长进行的模拟表明,绝对重建吸收系数和相应血红蛋白浓度存在较大的系统误差,而相对氧合血红蛋白和脱氧血红蛋白浓度的误差是可以接受的。最大的差异源于图像重建深度的系统误差。对于深度误差为±1 mm的情况,血红蛋白浓度的绝对重建偏差可能达到100%,而相对浓度的误差小于5%。这些结果表明,虽然定量扩散光学断层扫描具有难度,但氧合血红蛋白和脱氧血红蛋白相对浓度的图像是准确且稳健的。未展示的其他结果证实,这些发现适用于其他线性重建技术(即奇异值分解和同时迭代重建技术)以及平板几何形状的透射情况。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验