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首页> 外文会议>Proceedings of the 2016 IEEE International Conference on Wireless Communications, Signal Processing and Networking >Automatic glaucoma detection by using funduscopic images
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Automatic glaucoma detection by using funduscopic images

机译：使用眼底镜图像自动检测青光眼

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This paper describes an automatic system to identify glaucoma disease from funduscopic images using digital image processing. Glaucoma is caused by the increased pressure of the eye and damages the optic nerve. Since glaucoma does not show early symptoms, it should be diagnosed by the doctor. Through this new detection technique, doctors can quickly and easily identify patient's condition and carryout the treatment necessary. This method also has the added advantage if being affordable. Here glaucoma is identified through cup (optical disc's inner circle) to disc (outer circle) ratio (CDR) calculation and by the orientation of the blood vessels. In this system firstly, cup and disc are extracted using average and maximum grey level pixels respectively with the use of histogram. Then contours are found, which in turn are used to draw the best fitting circle, thus finding the radius of cup and disc. After calculating CDR, the abnormal image can be recognized if CDR exceeds the threshold value. Otherwise it is a normal image. The system extracts the blood vessels and through their orientation glaucoma is identified.
机译：本文介绍了一种使用数字图像处理从眼底镜图像识别青光眼疾病的自动系统。青光眼是由眼压升高引起的，并损害了视神经。由于青光眼未显示早期症状，应由医生诊断。通过这种新的检测技术，医生可以快速轻松地识别患者的病情并进行必要的治疗。如果负担得起的话，这种方法还具有额外的优势。在这里，青光眼通过杯（光盘的内圈）与光盘（外圈）之比（CDR）的计算以及血管的方向来识别。在该系统中，首先，使用直方图分别使用平均和最大灰度像素提取杯子和光盘。然后找到轮廓，然后使用轮廓绘制最佳拟合圆，从而找到杯子和圆盘的半径。在计算出CDR之后，如果CDR超过阈值，则可以识别出异常图像。否则，它是正常图像。该系统提取血管，并通过其方向识别青光眼。

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