isolation of vessels in retinal color images

Identifying retinal blood vessels is widely used for diagnosing eye diseases such as diabetic retinopathy, and glaucoma. currently, doctors manually extract these vessels, which is a challenging and time-consuming process that often leads to errors. in this paper, a new method is proposed for retinal blood vessel extraction, which includes three basic parts. first, the noise in the image is removed. next, the center lines of the vessel are extracted. finally, the blood vessels of the retinal images are extracted using the area expansion and noise removal method. the proposed method is applied to the images of the drive test set and its efficiency is evaluated using four different metrics: sensitivity, specificity, accuracy, and precision. the average results for accuracy, specificity, sensitivity, and accuracy in the proposed method are 0.92896, 0.98965, 0.91756, and 0.96578, respectively.

isolation of vessels in retinal color images

identifying retinal blood vessels is widely used for diagnosing eye diseases such as diabetic retinopathy, and glaucoma. currently, doctors manually extract these vessels, which is a challenging and time-consuming process that often leads to errors. in this paper, a new method is proposed for retinal blood vessel extraction, which includes three basic parts. first, the noise in the image is removed. next, the center lines of the vessel are extracted. finally, the blood vessels of the retinal images are extracted using the area expansion and noise removal method. the proposed method is applied to the images of the drive test set and its efficiency is evaluated using four different metrics: sensitivity, specificity, accuracy, and precision. the average results for accuracy, specificity, sensitivity, and accuracy in the proposed method are 0.92896, 0.98965, 0.91756, and 0.96578, respectively.