Walter Thomas, Klein Jean-Claude, Massin Pascale, Erginay Ali
Center of Mathematical Morphology, Paris School of Mines, 35 Rue. St. Honore, 77305 Fontainebleau cedex, France.
IEEE Trans Med Imaging. 2002 Oct;21(10):1236-43. doi: 10.1109/TMI.2002.806290.
In the framework of computer assisted diagnosis of diabetic retinopathy, a new algorithm for detection of exudates is presented and discussed. The presence of exudates within the macular region is a main hallmark of diabetic macular edema and allows its detection with a high sensitivity. Hence, detection of exudates is an important diagnostic task, in which computer assistance may play a major role. Exudates are found using their high grey level variation, and their contours are determined by means of morphological reconstruction techniques. The detection of the optic disc is indispensable for this approach. We detect the optic disc by means of morphological filtering techniques and the watershed transformation. The algorithm has been tested on a small image data base and compared with the performance of a human grader. As a result, we obtain a mean sensitivity of 92.8% and a mean predictive value of 92.4%. Robustness with respect to changes of the parameters of the algorithm has been evaluated.
在糖尿病视网膜病变的计算机辅助诊断框架下，提出并讨论了一种用于检测渗出物的新算法。黄斑区域内渗出物的存在是糖尿病性黄斑水肿的主要标志，并且能够以高灵敏度检测到它。因此，渗出物的检测是一项重要的诊断任务，计算机辅助在其中可能发挥主要作用。利用渗出物的高灰度变化来发现它们，并通过形态学重建技术确定其轮廓。对于这种方法，视盘的检测是必不可少的。我们通过形态学滤波技术和分水岭变换来检测视盘。该算法已在一个小图像数据库上进行了测试，并与人工分级的性能进行了比较。结果，我们获得了92.8%的平均灵敏度和92.4%的平均预测值。已评估了该算法相对于参数变化的稳健性。
