Quantitative phase imaging andcomputational specificity (Popescu)

摘要 TRD 1的目标是将QPI技术转化为体内和深层组织成像，并通过 计算和深度学习。定量相位成像(QPI)是一种强大的、无标记的方法 成像细胞和组织，特别是因为它结合了显微镜、全息照相和光的特性 散射技术：纳米级对形态和动力学的敏感性，2D、3D和4D(即时间分辨 层析成像)对完全透明的结构进行无损成像，以及基于 内在的对比。这些能力已经使QPI成功地应用于许多生物医学 应用领域，包括组织病理学和细胞治疗中的癌症诊断。最近，我们将QPI扩展为 首次通过发展渐变光干涉来处理厚结构，如胚胎和球体 显微镜(GLIM，2018年今日显微镜年度方法)。然而，尽管取得了巨大的进展， 目前的QPI技术几乎不存在于体内和POC应用中。 我们将把QPI技术提升到共焦反射几何结构，从而增强离焦光 拒绝和改进厚组织结构的高分辨率3D成像。具体地说，我们将首先针对 活体成像皮肤胶原蛋白的3D取向。我们将开发一种无标记内窥镜系统(EGLIM) 能够实现亚微米空间和毫秒级的时间分辨率，同时保持纳米路径长度 敏感度。我们将把具有计算特异性的相位成像(PICS)推进到活体的实时操作 来自CPT(目标1)和eGLIM(目标2)的数据。具体地说，我们将与Trd3密切合作，开发 用于分割球体中的细胞和亚细胞结构、识别胶原纤维的计算工具 从体内CPT皮肤数据，开发快速无标记病毒检测，无损活/死细胞分析，标记- 游离细胞周期时相识别。

SUMMARY TRD 1 aims to translate QPI technology to in-vivo and deep-tissue imaging with specific markers developed via computation and deep-learning. Quantitative phase imaging (QPI) is emerging as a powerful, label-free approach to imaging cells and tissues, especially because it combines qualities found in microscopy, holography, and light scattering techniques: nanoscale sensitivity to morphology and dynamics, 2D, 3D, and 4D (i.e., time-resolved tomography) nondestructive imaging of completely transparent structures, and quantitative signals based on intrinsic contrast. These capabilities have allowed QPI to be successfully applied in numerous biomedical applications, including cancer diagnosis in histopathology and cell therapy. Recently, we have expanded QPI for the first time to thick structures, such as embryos and spheroids, by developing gradient light interference microcopy (GLIM, the 2018 Microscopy Today Method of the Year). However, despite enormous progress, current QPI techniques are virtually absent from in-vivo and POC applications. We will advance the QPI technology to a confocal reflection geometry, thus, boosting the out of focus light rejection and improving high-resolution 3D imaging of thick tissue structures. Specifically, we will target first imaging the 3D orientation of skin collagen in-vivo. We will develop a label-free endoscopic system (eGLIM) capable of sub-micron spatial and millisecond temporal resolution, while maintaining nanometer pathlength sensitivity. We will advance phase imaging with computational specificity (PICS) to real-time operation on in-vivo data from CPT (Aim 1) and eGLIM (Aim 2). Specifically, in close collaboration with TRD 3, we will develop computational tools for segmenting cellular and subcellular structures in spheroids, identifying collagen fibers from in-vivo CPT skin data, developing rapid label-free viral testing, nondestructive live/dead cell assays, label- free cell cycle phase identification.