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Determination of tissue optical properties from spatially resolved relative diffuse reflectance

机译:从空间分辨的相对漫射反射率测定组织光学性质

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Noninvasive determination of μ_s' and μ_a is essential for clinical applications in medical diagnostics and therapeutics. Spatially resolved diffuse reflectance method is more advantageous than other techniques because of its simplicity and low-cost. The methods for solving the nonlinear inverse problem of estimates of μ_s' and μ_a from spatially resolved diffuse reflectance R_d(r) can be classified into the algorithms based on absolute or relative reflectance measurements in nature. Since absolute reflectance measurements are technically more difficult to perform than the relative one, study on the methods based on the relative reflectance has a more important meaning for real applications. Considering that there were several normalizations of R_d(r), in this paper we discussed the varieties of prediction rms errors of μ_s' and μ_a extracted from relative reflectance data of different normalization forms including R_d(r)/R_d(r)_(max), r~2(R_d(r)/R_d(r)_(max)), ln(R_d(r)/R_d(r)_(max)) and ln(r~2(R_d(r)/R_d(r)_(max)). Additionally, we compared the accuracies of μ_s' and μ_a determined from absolute reflectance data R_d(r) and ln(R_d(r)) with that from relative reflectance data to study the loss of accuracy due to normalization. Rather than the traditional neural network methods, we used a new method -PCA-NN trained with diffuse reflectance data from Monte Carlo simulations to derive μ_s' and μ_a. All the PCA-NNs were trained and tested on the space with ft/ between 0.1 and 2.0 mm~(-1) and μ_a between 0.01 and 0.1 mm~(-1). The test results indicate that the rms errors in μ_s' and μ_a are 0.72% and 2.57% for R_d(r), 0.28% and 0.55% for ln(R_d(r)), 2.98% and 5.44% for R_d(r)/R_d(r)_(max), 2.22% and 3.21% for ln(R_d(r)/R_d(r)_(max)), 6.52% and 20.7% for r~2(R_d(r)/R_d(r)_(max)), and 2.22% and 3.21% for ln(r~2(R_d(r)/R_d(r)_(max))), suggesting that the normalization form ln(R_d(r)/R_d(r)_(max)) would be the first choice for the estimates of μ_s' and μ_a from relative reflectance data by PCA-NN. Although the loss of accuracy due to normalization is considerable, the preliminary results provide a guideline for relative reflectance measurements.
机译:无血迹测定μ_s'和μ_a对于医学诊断和治疗药中的临床应用至关重要。由于其简单性和低成本,空间分辨的漫反射方法比其他技术更有利。求解从空间分辨的漫反射率R_D(R)的μ_和μ_a估计的非线性逆问题的方法可以基于自然界中的绝对或相对反射率测量来分类为算法。由于绝对反射测量在技术上更难以执行,因此对基于相对反射率的方法的研究具有对真实应用的更重要的意义。考虑到r_d(r)有几个常规趋势,在本文中,我们讨论了从不同归一化形式的相对反射率数据中提取的μ_s'和μ_a的μ_a的品种,包括r_d(r)/ r_d(r)_(max ),r〜2(r_d(r)/ r_d(r)_(max)),ln(r_d(r)/ r_d(r)_(max))和ln(r〜2(r_d(r)/ r_d (r)_(max))。另外,我们将μ_'和μ_a的精度与来自相对反射率数据的绝对反射数据r_d(r)和ln(r_d(r))进行了比较,以研究到期的准确性损失归一化。而不是传统的神经网络方法,我们使用了来自蒙特卡罗模拟的漫射反射数据训练的新方法-PCA-NN,从而衍生μ_s'和μ_a。所有PCA-NNS都培训并在空间上用FT培训并在空间上进行测试/ 0.01和0.1mm〜(-1)和μ_a之间的0.01和0.1mm〜(-1)。测试结果表明μ_'和μ_a的rms误差为0.72%和2.57%,对于r_d(r),0.28 LN(R_D(R))的%和0.55%,R_D(R)/ R的2.98%和5.44% _d(r)_(max),Ln的2.22%和3.21%(r_d(r)/ r_d(r)_(max)),r〜2的6.52%和20.7%(R_D(R)/ R_D(r )_(max))和2.22%和3.21%的ln(r〜2(r_d(r)/ r_d(r)_(max))),建议归一化表格ln(r_d(r)/ r_d( r)_(max))将是PCA-NN相对反射数据估计的第一选择μ_和μ_a。虽然归一化引起的准确性损失相当大,但初步结果提供了相对反射率测量的指导。

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