Department of Mechanical Engineering, University of Washington, Seattle, Washington, United States of America.
Department of Pathology, University of Washington, Seattle, Washington, United States of America.
PLoS One. 2020 Oct 1;15(10):e0233198. doi: 10.1371/journal.pone.0233198. eCollection 2020.
Slide-free digital pathology techniques, including nondestructive 3D microscopy, are gaining interest as alternatives to traditional slide-based histology. In order to facilitate clinical adoption of these fluorescence-based techniques, software methods have been developed to convert grayscale fluorescence images into color images that mimic the appearance of standard absorptive chromogens such as hematoxylin and eosin (H&E). However, these false-coloring algorithms often require manual and iterative adjustment of parameters, with results that can be inconsistent in the presence of intensity nonuniformities within an image and/or between specimens (intra- and inter-specimen variability). Here, we present an open-source (Python-based) rapid intensity-leveling and digital-staining package that is specifically designed to render two-channel fluorescence images (i.e. a fluorescent analog of H&E) to the traditional H&E color space for 2D and 3D microscopy datasets. However, this method can be easily tailored for other false-coloring needs. Our package offers (1) automated and uniform false coloring in spite of uneven staining within a large thick specimen, (2) consistent color-space representations that are robust to variations in staining and imaging conditions between different specimens, and (3) GPU-accelerated data processing to allow these methods to scale to large datasets. We demonstrate this platform by generating H&E-like images from cleared tissues that are fluorescently imaged in 3D with open-top light-sheet (OTLS) microscopy, and quantitatively characterizing the results in comparison to traditional slide-based H&E histology.
无滑动物镜技术，包括无损 3D 显微镜，正作为传统载玻片组织学的替代方法受到关注。为了促进这些基于荧光的技术在临床中的应用，已经开发了软件方法将灰度荧光图像转换为模仿标准吸收性染料（如苏木精和伊红（H&E））外观的彩色图像。然而，这些伪彩色算法通常需要手动和迭代调整参数，并且在图像内和/或标本之间存在强度不均匀性的情况下，结果可能不一致（标本内和标本间变异性）。在这里，我们提出了一个开源（基于 Python）的快速强度均衡和数字染色包，专门用于将双通道荧光图像（即 H&E 的荧光类似物）渲染到传统的 H&E 彩色空间，用于 2D 和 3D 显微镜数据集。然而，这种方法可以很容易地适应其他伪彩色需求。我们的软件包提供了（1）即使在大厚标本内存在不均匀染色的情况下也能实现自动和均匀的伪彩色，（2）对不同标本之间染色和成像条件变化具有稳健的一致颜色空间表示，以及（3）GPU 加速的数据处理，以使这些方法能够扩展到大型数据集。我们通过从用开放式顶光片（OTLS）显微镜荧光成像的 3D 透明组织生成 H&E 样图像来展示该平台，并与传统的基于载玻片的 H&E 组织学相比对结果进行定量表征。
