Korzynska Anna, Roszkowiak Lukasz, Pijanowska Dorota, Kozlowski Wojciech, Markiewicz Tomasz
Diagn Pathol. 2014;9 Suppl 1(Suppl 1):S13. doi: 10.1186/1746-1596-9-S1-S13. Epub 2014 Dec 19.
The aim of this study is to compare the digital images of the tissue biopsy captured with optical microscope using bright field technique under various light conditions. The range of colour's variation in immunohistochemically stained with 3,3'-Diaminobenzidine and Haematoxylin tissue samples is immense and coming from various sources. One of them is inadequate setting of camera's white balance to microscope's light colour temperature. Although this type of error can be easily handled during the stage of image acquisition, it can be eliminated with use of colour adjustment algorithms. The examination of the dependence of colour variation from microscope's light temperature and settings of the camera is done as an introductory research to the process of automatic colour standardization.
Six fields of view with empty space among the tissue samples have been selected for analysis. Each field of view has been acquired 225 times with various microscope light temperature and camera white balance settings. The fourteen randomly chosen images have been corrected and compared, with the reference image, by the following methods: Mean Square Error, Structural SIMilarity and visual assessment of viewer.
For two types of backgrounds and two types of objects, the statistical image descriptors: range, median, mean and its standard deviation of chromaticity on a and b channels from CIELab colour space, and luminance L, and local colour variability for objects' specific area have been calculated. The results have been averaged for 6 images acquired in the same light conditions and camera settings for each sample.
The analysis of the results leads to the following conclusions: (1) the images collected with white balance setting adjusted to light colour temperature clusters in certain area of chromatic space, (2) the process of white balance correction for images collected with white balance camera settings not matched to the light temperature moves image descriptors into proper chromatic space but simultaneously the value of luminance changes. So the process of the image unification in a sense of colour fidelity can be solved in separate introductory stage before the automatic image analysis.
本研究的目的是比较在不同光照条件下，使用明场技术通过光学显微镜拍摄的组织活检数字图像。用3,3'-二氨基联苯胺和苏木精免疫组织化学染色的组织样本颜色变化范围极大，且来源多样。其中一个原因是相机白平衡与显微镜光色温设置不当。尽管这类错误在图像采集阶段很容易处理，但可通过使用颜色调整算法将其消除。研究显微镜光温度和相机设置对颜色变化的依赖性，作为自动颜色标准化过程的前期研究。
选择六个组织样本间有空隙的视野进行分析。每个视野在不同显微镜光温度和相机白平衡设置下采集225次。通过以下方法对随机选择的14张图像与参考图像进行校正和比较：均方误差、结构相似性和观察者视觉评估。
针对两种背景和两种物体类型，计算了统计图像描述符：CIELab颜色空间中a和b通道的色度范围、中位数、均值及其标准差，以及亮度L，还有物体特定区域的局部颜色变异性。对每个样本在相同光照条件和相机设置下采集的6张图像的结果进行了平均。
对结果的分析得出以下结论：（1）白平衡设置调整到光色温时采集的图像在色度空间的特定区域聚类；（2）相机白平衡设置与光温度不匹配时采集的图像进行白平衡校正的过程，会将图像描述符移至合适的色度空间，但同时亮度值会发生变化。因此，在自动图像分析之前的单独前期阶段，可以解决颜色保真度意义上的图像统一问题。
