Tsikata Edem, Laíns Inês, Gil João, Marques Marco, Brown Kelsey, Mesquita Tânia, Melo Pedro, da Luz Cachulo Maria, Kim Ivana K, Vavvas Demetrios, Murta Joaquim N, Miller John B, Silva Rufino, Miller Joan W, Chen Teresa C, Husain Deeba
Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, Boston, MA, USA ; Glaucoma Service of Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, Boston, MA, USA ; University of Coimbra, Faculty of Medicine, University of Coimbra, Coimbra, Portugal ; Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal ; Association for Biomedical Research and Innovation on Light and Image, Coimbra, Portugal ; Retina Service of Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Transl Vis Sci Technol. 2017 Mar 13;6(2):3. doi: 10.1167/tvst.6.2.3. eCollection 2017 Mar.
The purpose of this study was to develop an algorithm to automatically standardize the brightness, contrast, and color balance of digital color fundus photographs used to grade AMD and to validate this algorithm by determining the effects of the standardization on image quality and disease grading.
Seven-field color photographs of patients (>50 years) with any stage of AMD and a control group were acquired at two study sites, with either the Topcon TRC-50DX or Zeiss FF-450 Plus cameras. Field 2 photographs were analyzed. Pixel brightness values in the red, green, and blue (RGB) color channels were adjusted in custom-built software to make the mean brightness and contrast of the images equal to optimal values determined by the Age-Related Eye Disease Study (AREDS) 2 group.
Color photographs of 370 eyes were analyzed. We found a wide range of brightness and contrast values in the images at baseline, even for those taken with the same camera. After processing, image brightness variability (brightest image-dimmest image in a color channel) was reduced 69-fold, 62-fold, and 96-fold for the RGB channels. Contrast variability was reduced 6-fold, 8-fold, and 13-fold, respectively, after adjustment. Of the 23% images considered nongradable before adjustment, only 5.7% remained nongradable.
This automated software enables rapid and accurate standardization of color photographs for AMD grading.
This work offers the potential to be the future of assessing and grading AMD from photos for clinical research and teleimaging.
本研究的目的是开发一种算法，以自动标准化用于年龄相关性黄斑变性（AMD）分级的数字彩色眼底照片的亮度、对比度和色彩平衡，并通过确定标准化对图像质量和疾病分级的影响来验证该算法。
在两个研究地点，使用拓普康TRC-50DX或蔡司FF-450 Plus相机，采集了患有任何阶段AMD的患者（年龄>50岁）和对照组的七视野彩色照片。对第2视野照片进行分析。在定制软件中调整红色、绿色和蓝色（RGB）颜色通道中的像素亮度值，使图像的平均亮度和对比度等于年龄相关性眼病研究（AREDS）2组确定的最佳值。
分析了370只眼睛的彩色照片。我们发现，即使是使用同一台相机拍摄的图像，基线时的亮度和对比度值也有很大差异。处理后，RGB通道的图像亮度变异性（彩色通道中最亮图像与最暗图像之差）分别降低了69倍、62倍和96倍。调整后，对比度变异性分别降低了6倍、8倍和13倍。在调整前被认为不可分级的23%的图像中，只有5.7%仍然不可分级。
这种自动化软件能够快速、准确地标准化用于AMD分级的彩色照片。
这项工作有可能成为未来用于临床研究和远程成像的通过照片评估和分级AMD的方法。
