A reference-free method for brightness compensation and contrast enhancement of micrographs of serial sections.
A reference-free method for brightness compensation and contrast enhancement of micrographs of serial sections.
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连续切片显微照片亮度补偿和对比度增强的无参考方法
DOI：
10.1371/journal.pone.0127855
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发表时间：
2015
期刊：
影响因子：
3.7
通讯作者：
Zhai XY
中科院分区：
文献类型：
--
作者：
Chang SJ;Li S;Andreasen A;Sha XZ;Zhai XY
从一堆组织学连续切片对器官或组织进行三维（3D）重建提供了有价值的形态学信息。该过程包括器官或组织的切片准备、显微照片采集、图像配准、3D重建和可视化。然而，由于染色过程的不完善，通过图像堆栈的亮度和对比度可能不一致，这可能会导致使用虚拟切片的微结构识别，区域分割，自动目标跟踪等困难。在本研究中，无参考方法，顺序直方图拟合算法（SHFA），因此，开发了用于调整图像堆栈内亮度和对比度的严重和不规则变化。为了应用SHFA，首先在整个图像堆栈上计算各个图像的灰度值直方图，并选择一组地标灰度值。然后，直方图被变换，使得在通过堆栈的过程中没有突然的变化。最后，根据原始直方图和变换后直方图之间的关系，将原始图像的像素灰度值变换为所需的像素灰度值。在来自用甲苯胺蓝染色的小鼠肾切片的图像堆叠上测试SHFA，并通过载玻片扫描仪捕获。结果，整个堆栈的图像显示出均匀的亮度和一致的对比度。此外，组织中细微的颜色差异得到了很好的保留，因此即使在虚拟切片中也可以识别形态细节。与现有的基于直方图的方法相比，本研究提供了一种实用的亮度补偿方法，适用于大量生物器官连续切片图像的亮度补偿和对比度提高。
Three-dimensional (3D) reconstruction of an organ or tissue from a stack of histologic serial sections provides valuable morphological information. The procedure includes section preparation of the organ or tissue, micrographs acquisition, image registration, 3D reconstruction, and visualization. However, the brightness and contrast through the image stack may not be consistent due to imperfections in the staining procedure, which may cause difficulties in micro-structure identification using virtual sections, region segmentation, automatic target tracing, etc. In the present study, a reference-free method, Sequential Histogram Fitting Algorithm (SHFA), is therefore developed for adjusting the severe and irregular variance of brightness and contrast within the image stack. To apply the SHFA, the gray value histograms of individual images are first calculated over the entire image stack and a set of landmark gray values are chosen. Then the histograms are transformed so that there are no abrupt changes in progressing through the stack. Finally, the pixel gray values of the original images are transformed into the desired ones based on the relationship between the original and the transformed histograms. The SHFA is tested on an image stacks from mouse kidney sections stained with toluidine blue, and captured by a slide scanner. As results, the images through the entire stack reveal homogenous brightness and consistent contrast. In addition, subtle color differences in the tissue are well preserved so that the morphological details can be recognized, even in virtual sections. In conclusion, compared with the existing histogram-based methods, the present study provides a practical method suitable for compensating brightness, and improving contrast of images derived from a large number of serial sections of biological organ.
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