标题： 从光学相干断层扫描数据中进行定量参数重建 显示英文标题

标题： Quantitative Parameter Reconstruction from Optical Coherence Tomographic Data

摘要： 定量组织信息，如光散射特性，在医学诊断中被认为是检测癌细胞的关键因素。 一种获得这些数据有前途的方法是光学相干断层扫描（OCT）。 在本文中，我们将讨论从OCT数据中重建折射率，采用基于高斯束的正向模型。 我们特别考虑具有分层结构的样品，这意味着折射率作为深度的函数可以很好地用分段常数函数近似。 对于重建，我们提出了一种逐层方法，在每一步中通过离散化最小二乘法最小化来获得折射率。 对于最小化问题的一种近似形式，我们提出了一个存在性和唯一性结果。 然后通过从模拟和实验OCT数据中重建分层介质的折射率来验证所提出方法的适用性。 显示英文摘要

摘要： Quantitative tissue information, like the light scattering properties, is considered as a key player in the detection of cancerous cells in medical diagnosis. A promising method to obtain these data is optical coherence tomography (OCT). In this article, we will therefore discuss the refractive index reconstruction from OCT data, employing a Gaussian beam based forward model. We consider in particular samples with a layered structure, meaning that the refractive index as a function of depth is well approximated by a piece-wise constant function. For the reconstruction, we present a layer-by-layer method where in every step the refractive index is obtained via a discretized least squares minimization. For an approximated form of the minimization problem, we present an existence and uniqueness result. The applicability of the proposed method is then verified by reconstructing refractive indices of layered media from both simulated and experimental OCT data.