Brightness, contrast, and color balance of digital versus film retinal images in the age-related eye disease study 2
Brightness, contrast, and color balance of digital versus film retinal images in the age-related eye disease study 2
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DOI：
10.1167/iovs.07-1267
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发表时间：
2008-08-01
影响因子：
4.4
通讯作者：
Pugliese, Michael F.
中科院分区：
文献类型：
--
作者：
Hubbard, Larry D.;Danis, Ronald P.;Pugliese, Michael F.
目的。在一项多中心临床试验中，分析数字视网膜图像和胶片视网膜图像的亮度、对比度和色彩平衡，从样本中提出一个模型图像，并优化这两种图像类型以评估年龄相关性黄斑变性(AMD)。方法：年龄相关眼病研究2(AREDS2)从90家诊所招募受试者，其中四分之三使用数码相机，四分之一使用胶片相机。用三色亮度直方图测量图像亮度(B)、对比度(C)和色彩平衡(CB)。首先，对来自专家小组的样本(胶片和数字)进行了分析，并构建了面向AMD的模型。其次，分析B/C/CB对AMD典型异常表现的影响。第三，比较胶片(156只眼)和数码相机(605只眼)的AREDS2图像的B/C/CB，并与模型进行比较。结果：样本图像具有相似的亮度、对比度和色彩平衡，支持图像模型。通过改变大范围的B/C/CB的样本图像，在模型参数下显示出与正常视网膜色素上皮相比，玻璃体和色素异常的最大对比。AREDS2数字图像比胶片更易变，与我们的模型的一致性较低。10%的数码相机太暗，19%的相机太亮(过饱和)，而胶片的这两个比例分别为1%和4%。平均而言，数码相机的绿色通道对比度比胶片低(提供的视网膜细节较少)。在23%的数码相机中观察到过红的色彩平衡(淡绿色)，而在胶片中只有8%。在AMD分级之前，大约有一半的数字图像(但胶片较少)需要增强。经过两种图像类型的优化后，AREDS2的图像质量与AREDS(全胶片)的图像质量一样好。结论：基于样本的直方图模型为图像分析和增强提供了实用的指导。在AREDS2中，最好的数字图像与最好的胶片相匹配。然而，总的来说，数码相机提供的视网膜细节对比度较低。高G-R比拍摄的数字图像显示出更好的亮度和对比度管理。多中心研究中图像的优化有助于AMD(临床试验)文件的标准化。GOV NCT00345176)。
PURPOSE. To analyze brightness, contrast, and color balance of digital versus film retinal images in a multicenter clinical trial, to propose a model image from exemplars, and to optimize both image types for evaluation of age-related macular degeneration (AMD).METHODS. The Age-Related Eye Disease Study 2 (AREDS2) is enrolling subjects from 90 clinics, with three quarters of them using digital and one quarter using film cameras. Image brightness (B), contrast (C), and color balance (CB) were measured with three-color luminance histograms. First, the exemplars (film and digital) from expert groups were analyzed, and an AMD-oriented model was constructed. Second, the impact of B/C/CB on the appearance of typical AMD abnormalities was analyzed. Third, B/C/CB in AREDS2 images were compared between film (156 eyes) and digital (605 eyes), and against the model. Fourth, suboptimal images were enhanced by adjusting B/C/CB to bring them into accord with model parameters.RESULTS. Exemplar images had similar brightness, contrast, and color balance, supporting an image model. Varying a specimen image through a wide range of B/C/CB revealed greatest contrast of drusen and pigment abnormalities against normal retinal pigment epithelium with the model parameters. AREDS2 digital images were more variable than film, with lower correspondence to our model. Ten percent of digital were too dim and 19% too bright (oversaturated), versus 1% and 4% of film, respectively. On average, digital had lower green channel contrast (giving less retinal detail) than film. Overly red color balance (weaker green) was observed in 23% of digital versus 8% of film. About half of digital (but fewer film) images required enhancement before AMD grading. After optimization of both image types, AREDS2 image quality was judged as good as that in AREDS (all film).CONCLUSIONS. A histogram-based model, derived from exemplars, provides a pragmatic guide for image analysis and enhancement. In AREDS2, the best digital images matched the best film. Overall, however, digital provided lower contrast of retinal detail. Digital images taken with higher G-to-R ratio showed better brightness and contrast management. Optimization of images in the multicenter study helps standardize documentation of AMD (ClinicalTrials. gov NCT00345176).