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Depth-correction algorithm that improves optical quantification of large breast lesions imaged by diffuse optical tomography

机译:深度校正算法,可改善通过弥散光学层析成像成像的大型乳腺病变的光学定量

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摘要

Optical quantification of large lesions imaged with diffuse optical tomography in reflection geometry is depth dependence due to the exponential decay of photon density waves. We introduce a depth-correction method that incorporates the target depth information provided by coregistered ultrasound. It is based on balancing the weight matrix, using the maximum singular values of the target layers in depth without changing the forward model. The performance of the method is evaluated using phantom targets and 10 clinical cases of larger malignant and benign lesions. The results for the homogenous targets demonstrate that the location error of the reconstructed maximum absorption coefficient is reduced to the range of the reconstruction mesh size for phantom targets. Furthermore, the uniformity of absorption distribution inside the lesions improve about two times and the median of the absorption increases from 60 to 85% of its maximum compared to no depth correction. In addition, nonhomogenous phantoms are characterized more accurately. Clinical examples show a similar trend as the phantom results and demonstrate the utility of the correction method for improving lesion quantification.
机译:由于光子密度波呈指数衰减,因此用反射几何学中的漫射光学层析成像成像的大病变的光学定量与深度相关。我们引入一种深度校正方法,该方法结合了由共同注册的超声提供的目标深度信息。它基于平衡权重矩阵,在不更改前向模型的情况下使用目标层深度的最大奇异值。使用幻影靶标和10例较大的恶性和良性病变临床病例评估该方法的性能。均匀目标的结果表明,重建的最大吸收系数的位置误差减小到幻影目标的重建网格大小的范围。此外,与未进行深度矫正相比,病变内部吸收分布的均匀性提高了约两倍,吸收的中值从其最大值的60%增加到了85%。此外,非均质体模的特征也更精确。临床实例显示出与幻像结果相似的趋势,并证明了校正方法可用于改善病变定量。

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