Al-Rawi Mohammed, Karajeh Huda
Computer Science Department, King Abdullah II School for Information Technology, University of Jordan, Amman, Jordan.
Comput Methods Programs Biomed. 2007 Sep;87(3):248-53. doi: 10.1016/j.cmpb.2007.05.012. Epub 2007 Jul 3.
Due to the importance of the matched filter in the automated detection of blood vessels in digital retinal images, improving its response is highly desirable. This filter may vary in many ways depending on the parameters that govern its response. In this paper, new parameters to optimize the sensitivity of the matched filter are found using genetic algorithms on the test set of the DRIVE databases. The area under the receiver operating curve (ROC) is used as a fitness function for the genetic algorithm. To evaluate the improved matched filter, the maximum average accuracy (MAA) is calculated to be 0.9422 and the average area under ROC is 0.9582.
由于匹配滤波器在数字视网膜图像中血管自动检测中的重要性，提高其响应非常必要。该滤波器可能会根据控制其响应的参数在许多方面有所不同。在本文中，使用遗传算法在DRIVE数据库的测试集上找到了优化匹配滤波器灵敏度的新参数。接收器操作曲线（ROC）下的面积用作遗传算法的适应度函数。为了评估改进后的匹配滤波器，计算出最大平均准确率（MAA）为0.9422，ROC下的平均面积为0.9582。
