Biomedical Engineering Branch, Division of Basic & Applied Sciences, National Cancer Center, 111 Jungbalsan-ro, Ilsandong-gu, Goyang-si, Gyeonggi-do, South Korea.
J Digit Imaging. 2011 Jun;24(3):394-404. doi: 10.1007/s10278-010-9274-9.
Image processing of a fundus image is performed for the early detection of diabetic retinopathy. Recently, several studies have proposed that the use of a morphological filter may help extract hemorrhages from the fundus image; however, extraction of hemorrhages using template matching with templates of various shapes has not been reported. In our study, we applied hue saturation value brightness correction and contrast-limited adaptive histogram equalization to fundus images. Then, using template matching with normalized cross-correlation, the candidate hemorrhages were extracted. Region growing thereafter reconstructed the shape of the hemorrhages which enabled us to calculate the size of the hemorrhages. To reduce the number of false positives, compactness and the ratio of bounding boxes were used. We also used the 5 × 5 kernel value of the hemorrhage and a foveal filter as other methods of false positive reduction in our study. In addition, we analyzed the cause of false positive (FP) and false negative in the detection of retinal hemorrhage. Combining template matching in various ways, our program achieved a sensitivity of 85% at 4.0 FPs per image. The result of our research may help the clinician in the diagnosis of diabetic retinopathy and might be a useful tool for early detection of diabetic retinopathy progression especially in the telemedicine.
眼底图像处理可用于早期发现糖尿病性视网膜病变。最近，有几项研究提出，使用形态滤波器可能有助于从眼底图像中提取出血；然而，使用各种形状的模板进行模板匹配来提取出血尚未有报道。在我们的研究中，我们对眼底图像应用了色调饱和度值亮度校正和对比度限制自适应直方图均衡。然后，使用归一化互相关的模板匹配，提取候选出血。之后，通过区域生长重建出血的形状，从而可以计算出血的大小。为了减少假阳性的数量，我们使用了紧凑度和边界框的比例。我们还使用了出血的 5×5 核值和中央凹滤波器作为我们研究中减少假阳性的其他方法。此外，我们分析了视网膜出血检测中假阳性（FP）和假阴性的原因。通过组合各种方式的模板匹配，我们的程序在每张图像 4.0 FP 的情况下达到了 85%的灵敏度。我们的研究结果可能有助于临床医生诊断糖尿病性视网膜病变，并且可能成为糖尿病性视网膜病变进展早期检测的有用工具，特别是在远程医疗中。
