Department of Anaesthesia, Critical Care, Emergency Care, Genk, Belgium.
BMC Med Imaging. 2010 Mar 18;10:7. doi: 10.1186/1471-2342-10-7.
Recently, digital photography in medicine is considered an acceptable tool in many clinical domains, e.g. wound care. Although ever higher resolutions are available, reproducibility is still poor and visual comparison of images remains difficult. This is even more the case for measurements performed on such images (colour, area, etc.). This problem is often neglected and images are freely compared and exchanged without further thought.
The first experiment checked whether camera settings or lighting conditions could negatively affect the quality of colorimetric calibration. Digital images plus a calibration chart were exposed to a variety of conditions. Precision and accuracy of colours after calibration were quantitatively assessed with a probability distribution for perceptual colour differences (dE_ab). The second experiment was designed to assess the impact of the automatic calibration procedure (i.e. chart detection) on real-world measurements. 40 Different images of real wounds were acquired and a region of interest was selected in each image. 3 Rotated versions of each image were automatically calibrated and colour differences were calculated.
1st
Colour differences between the measurements and real spectrophotometric measurements reveal median dE_ab values respectively 6.40 for the proper patches of calibrated normal images and 17.75 for uncalibrated images demonstrating an important improvement in accuracy after calibration. The reproducibility, visualized by the probability distribution of the dE_ab errors between 2 measurements of the patches of the images has a median of 3.43 dE* for all calibrated images, 23.26 dE_ab for all uncalibrated images. If we restrict ourselves to the proper patches of normal calibrated images the median is only 2.58 dE_ab! Wilcoxon sum-rank testing (p < 0.05) between uncalibrated normal images and calibrated normal images with proper squares were equal to 0 demonstrating a highly significant improvement of reproducibility. In the second experiment, the reproducibility of the chart detection during automatic calibration is presented using a probability distribution of dE_ab errors between 2 measurements of the same ROI.
The investigators proposed an automatic colour calibration algorithm that ensures reproducible colour content of digital images. Evidence was provided that images taken with commercially available digital cameras can be calibrated independently of any camera settings and illumination features.
最近,医学中的数字摄影被认为是许多临床领域的一种可接受的工具,例如伤口护理。尽管分辨率越来越高,但再现性仍然很差,并且图像的视觉比较仍然很困难。对于在这些图像上进行的测量(颜色,面积等)更是如此。这个问题经常被忽略,图像未经进一步思考就被自由比较和交换。
第一项实验检查了相机设置或照明条件是否会对比色校准的质量产生负面影响。将数字图像和校准图表暴露于各种条件下。使用感知色差的概率分布(dE_ab)定量评估校准后颜色的精度和准确性。第二项实验旨在评估自动校准程序(即图表检测)对实际测量的影响。采集了 40 张真实伤口的不同图像,并在每张图像中选择了一个感兴趣区域。每张图像的 3 个旋转版本都经过自动校准,并计算了颜色差异。
第一项实验:测量值与实际分光光度测量值之间的颜色差异表明,校准正常图像的适当补丁的中位数 dE_ab 值分别为 6.40,而未校准图像的中位数 dE_ab 值为 17.75,表明校准后准确性有了很大提高。通过图像补丁两次测量之间的 dE_ab 误差概率分布来可视化再现性,所有校准图像的中位数为 3.43 dE*,所有未校准图像的中位数为 23.26 dE_ab。如果我们将自己限制在正常校准图像的适当补丁上,则中位数仅为 2.58 dE_ab!未校准正常图像和具有适当正方形的校准正常图像之间的威尔科克森总和秩检验(p <0.05)等于 0,表明再现性得到了极大的提高。在第二项实验中,通过两次测量同一 ROI 之间的 dE_ab 误差概率分布来呈现自动校准过程中图表检测的可重复性。
研究人员提出了一种自动颜色校准算法,可确保数字图像的颜色再现性。有证据表明,可以独立于任何相机设置和照明特征对商业上可用的数码相机拍摄的图像进行校准。